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Ultrasound practice is a longstanding tradition for radiology departments, being part of the family of imaging techniques. Ultrasound is widely practiced by non-radiologists but becoming less popular within radiology. The position of ultrasound in radiology is reviewed, and a possible long-term solution to manage radiologist expectations is proposed. An international group of experts in the practice of ultrasound was invited to describe the current organisation of ultrasound within the radiology departments in their own countries and comment on the interaction with non-radiologists and training arrangements. Issues related to regulation, non-medical practitioners, and training principles are detailed. A consensus view was sought from the experts regarding the position of ultrasound within radiology, with the vision of the best scenario for the continuing dominance of radiologists practising ultrasound. Comments were collated from nine different countries. Variable levels of training, practice, and interaction with non-radiologist were reported, with some countries relying on non-physician input to manage the service. All experts recognised there was a diminished desire to practice ultrasound by radiologists. Models varied from practising solely ultrasound and no other imaging techniques to radiology departments being central to the practice of ultrasound by radiologists and non-radiologist, housed within radiology. The consensus view was that the model favoured in select hospitals in Germany would be the most likely setup for ultrasound radiologist to develop and maintain practice. The vision for 20 years hence is for a central ultrasound section within radiology, headed by a trained expert radiologist, with non-radiologist using the facilities. Critical relevance statement The future of ultrasound within the radiology department should encompass all ultrasound users, with radiologists expert in ultrasound, managing the ultrasound section within the radiology department. The current radiology trainees must learn of the importance of ultrasound as a component of the 'holistic' imaging of the patient. Key points: 1. Ultrasound imaging within radiology departments precedes the introduction of CT and MR imaging and was first used over 50 years ago. 2. Non-radiology practitioners deploy ultrasound examinations to either 'problem solve' or perform a comprehensive ultrasound examination; radiologists provide comprehensive examinations or use ultrasound to direct interventional procedures. 3. Radiology does not 'own' ultrasound, but radiologists are best placed to offer a comprehensive patient-focused imaging assessment. 4. A vision of the future of ultrasound within the radiology department is encompassing all ultrasound users under radiologists who are experts in ultrasound, positioned within the radiology department. 5. The current radiology trainee must be aware of the importance of ultrasound as a component of the 'holistic' imaging of the patient. [ABSTRACT FROM AUTHOR]

Recent morphological data on human brain development are quite fragmentary. However, they are highly requested for a number of medical practices, educational programs, and fundamental research in the fields of embryology, cytology and histology, neurology, physiology, path anatomy, neonatology, and others. This paper provides the initial information on the new online Human Prenatal Brain Development Atlas (HBDA). The Atlas will start with forebrain annotated hemisphere maps, based on human fetal brain serial sections at the different stages of prenatal ontogenesis. Spatiotemporal changes in the regional-specific immunophenotype profiles will also be demonstrated on virtual serial sections. The HBDA can serve as a reference database for the neurological research, which provides opportunity to compare the data obtained by noninvasive techniques, such as neurosonography, X-ray computed tomography and magnetic resonance imaging, functional magnetic resonance imaging, 3D high-resolution phase-contrast computed tomography visualization techniques, as well as spatial transcriptomics data. It could also become a database for the qualitative and quantitative analysis of individual variability in the human brain. Systemized data on the mechanisms and pathways of prenatal human glio- and neurogenesis could also contribute to the search for new therapy methods for a large spectrum of neurological pathologies, including neurodegenerative and cancer diseases. The preliminary data are now accessible on the special HBDA website. [ABSTRACT FROM AUTHOR]

Cork spot-like physiological disorder (CSPD) is a newly identified issue in 'Kurenainoyume' apples, yet its mechanism remains unclear. To investigate CSPD, we conducted morphological observations on 'Kurenainoyume' apples with and without pre-harvest fruit-bagging treatment using light-impermeable paper bags. Non-bagged fruit developed CSPD in mid-August, while no CSPD symptoms were observed in bagged fruit. The bagging treatment significantly reduced the proportion of opened lenticels, with only 17.9% in bagged fruit compared to 52.0% in non-bagged fruits. In non-bagged fruit, CSPD spots tended to increase from the lenticels, growing in size during fruit development. The cuticular thickness and cross-sectional area of fresh cells in CSPD spots were approximately 16 µm and 1600 µm², respectively. Healthy non-bagged fruit reached these values around 100 to 115 days after full bloom from mid- to late August. Microscopic and computerized tomography scanning observations revealed that many CSPD spots developed at the tips of vascular bundles. Therefore, CSPD initiation between opened lenticels and vascular bundle tips may be influenced by water stress, which is potentially caused by water loss, leading to cell death and the formation of CSPD spots. [ABSTRACT FROM AUTHOR]

Background: Diaphragmatic hernia (DH) presenting acutely can be a potentially life-threatening condition. Its management continues to be debatable. Methods: A bibliographic search using major databases was performed using the terms "emergency surgery" "diaphragmatic hernia," "traumatic diaphragmatic rupture" and "congenital diaphragmatic hernia." GRADE methodology was used to evaluate the evidence and give recommendations. Results: CT scan of the chest and abdomen is the diagnostic gold standard to evaluate complicated DH. Appropriate preoperative assessment and prompt surgical intervention are important for a clinical success. Complicated DH repair is best performed via the use of biological and bioabsorbable meshes which have proven to reduce recurrence. The laparoscopic approach is the preferred technique in hemodynamically stable patients without significant comorbidities because it facilitates early diagnosis of small diaphragmatic injuries from traumatic wounds in the thoraco-abdominal area and reduces postoperative complications. Open surgery should be reserved for situations when skills and equipment for laparoscopy are not available, where exploratory laparotomy is needed, or if the patient is hemodynamically unstable. Damage Control Surgery is an option in the management of critical and unstable patients. Conclusions: Complicated diaphragmatic hernia is a rare life-threatening condition. CT scan of the chest and abdomen is the gold standard for diagnosing the diaphragmatic hernia. Laparoscopic repair is the best treatment option for stable patients with complicated diaphragmatic hernias. Open repair is considered necessary in majority of unstable patients in whom Damage Control Surgery can be life-saving. [ABSTRACT FROM AUTHOR]

Since the beginning of the COVID-19 pandemic, many works have been published proposing solutions to the problems that arose in this scenario. In this vein, one of the topics that attracted the most attention is the development of computer-based strategies to detect COVID-19 from thoracic medical imaging, such as chest X-ray (CXR) and computerized tomography scan (CT scan). By searching for works already published on this theme, we can easily find thousands of them. This is partly explained by the fact that the most severe worldwide pandemic emerged amid the technological advances recently achieved, and also considering the technical facilities to deal with the large amount of data produced in this context. Even though several of these works describe important advances, we cannot overlook the fact that others only use well-known methods and techniques without a more relevant and critical contribution. Hence, differentiating the works with the most relevant contributions is not a trivial task. The number of citations obtained by a paper is probably the most straightforward and intuitive way to verify its impact on the research community. Aiming to help researchers in this scenario, we present a review of the top-100 most cited papers in this field of investigation according to the Google Scholar search engine. We evaluate the distribution of the top-100 papers taking into account some important aspects, such as the type of medical imaging explored, learning settings, segmentation strategy, explainable artificial intelligence (XAI), and finally, the dataset and code availability. [ABSTRACT FROM AUTHOR]

Defects, such as debonding and foreign matters in transformer insulation paperboard, lead to local field strength concentration, thereby seriously affecting the safe operation of equipment. At present, industrial X-ray computed tomography scanning technology is mostly used to detect such defects. However, the equipment is expensive, the operation is complicated, and radiation hazard exists. In this study, terahertz time domain spectroscopy is introduced to explore the nondestructive testing method of oil-paper insulation defects. Three typical insulation paperboard defects of interface debonding, metal foreign matter mixing, and local carbonization traces were taken as the research objects. An artificial defect model is prepared. The time and frequency domain waveform characteristics of terahertz pulse wave propagating in the defect model are tested and analyzed. The results show that when the thickness of insulation paperboard covering is less than 5 mm, based on the amplitude and delay characteristics of terahertz time-domain signal, the location and size of typical internal defects can be accurately obtained, and time spectrum imaging can be realized. This study proves theoretically and experimentally the feasibility of noncontact and nondestructive testing for the internal defects of insulation paperboard by using terahertz technology. [ABSTRACT FROM AUTHOR]

This paper presents the use of X-ray computed tomography and X-ray fluorescence in the analysis and expert research of the seventeenth century printed book "Eukhologīon albo Molitoslov, ili Trebnik" from Kiev. The main purpose of the survey was to confirm whether the book binding is original or whether it is a rebinding, and whether there are any fragments of the hidden older texts. Commonly used radiography is usually not able to provide sufficient information for these purposes. On the other hand, computed tomography allows a detailed and three-dimensional documentation of the bookbinding technology and the structure of the materials used, including the wooden boards. It will be presented that all elements of the weave are clearly visible, making it possible to show that there are no internal defects in the stitching and materials. It has also been convincingly shown that there are no fragments or layers of older texts in the binding, so no further invasive intervention will be necessary regarding this aspect. The paper also demonstrates the possibility of reading the text in a closed book utilising X-ray computed tomography data; this option may be advantageous for massively damaged manuscripts. It will also be shown, that thanks to detailed tomographic imaging of the wood structure of the boards, a dendrochronological survey can be successfully carried out without invasive intervention into their outer layers. From the CT data it was also found that the pigments of the letters have significantly different densities. Therefore, as part of the survey, elemental analysis of the writing was also carried out using a portable X-ray fluorescence spectrometer to confirm and clarify this finding. [ABSTRACT FROM AUTHOR]

This paper proposes applying a novel deep‐learning model, TBDLNet, to recognize CT images to classify multidrug‐resistant and drug‐sensitive tuberculosis automatically. The pre‐trained ResNet50 is selected to extract features. Three randomized neural networks are used to alleviate the overfitting problem. The ensemble of three RNNs is applied to boost the robustness via majority voting. The proposed model is evaluated by five‐fold cross‐validation. Five indexes are selected in this paper, which are accuracy, sensitivity, precision, F1‐score, and specificity. The TBDLNet achieves 0.9822 accuracy, 0.9815 specificity, 0.9823 precision, 0.9829 sensitivity, and 0.9826 F1‐score, respectively. The TBDLNet is suitable for classifying multidrug‐resistant tuberculosis and drug‐sensitive tuberculosis. It can detect multidrug‐resistant pulmonary tuberculosis as early as possible, which helps to adjust the treatment plan in time and improve the treatment effect. [ABSTRACT FROM AUTHOR]

Historical documents are often severely damaged, making it impossible to open them manually without causing further damage. To address this challenge, computed tomography (CT) has emerged as a non-destructive method to explore the inside in a different way. However, the use of ionising radiation in CT scanning raises concerns about its impact on fragile historical documents. This study presents a methodology that uses a test object to conduct preliminary investigations to evaluate the capability of a CT scanner for digital preservation of historical documents. By assessing the feasibility and determining the setting parameters in advance, the X-ray exposure to historical documents can be minimised. For this purpose, a large dataset of inter-page distances was obtained from CT scans of a specially developed test object. The results obtained show a consistent correlation between the page-to-page distances and the derived modulation depths. This method offers great potential for assessing the separability of the pages of historical documents even before they are exposed to radiation for digitisation. Overall, this study helps to reduce the impact of X-ray radiation on sensitive historical documents during digitisation using CT, with the aim of preserving this fragile cultural heritage for future generations. [ABSTRACT FROM AUTHOR]

There is a growing demand for application of personalized bone implants (endoprostheses or macro-scaffolds, and fixators) which conform to the anatomy of the patient. Hence the need for a CAD procedure that enables fast and sufficiently accurate digital reconstruction of the traumatized bone geometry. Research presented in this paper addresses digital reconstruction of the femoral neck fracture. The results point out that the User-Defined (geometric) Feature (UDF) concept is the most convenient to use in digital reconstruction of numerous variants of the same topology, such as in this kind of bone region. UDF, named FemoNeck, is developed to demonstrate capability of the chosen concept. Its geometry, controlled by a dozen of parameters, can be easily shaped according to the femoral neck region anatomy of a particular patient. That kind of the CAD procedure should use a minimally required set of geometric (anatomical) parameters, which can be easily captured from X-ray or Computed Tomography (CT) images. For the statistical analysis of geometry and UDF development we used CT scans of proximal femur of 24 Caucasian female and male adults. The validation of the proposed method was done by applying it for remodeling of four femoral necks of four different proximal femurs and by comparing the geometrical congruency between the raw polygonal models gained directly from CT scan and reconstructed models. [ABSTRACT FROM AUTHOR]

Objectives: Though recognized as a risk factor, posterior glenoid bone loss has only recently been characterized and is distinctly different than anterior glenoid bone loss patterns. Existing biomechanical studies are limited by employment of anterior glenoid bone loss models which are different in both orientation and morphology than posterior glenoid bone loss, and testing in a single neutral arm position thus not fully accounting for the contribution of capsuloligamentous structures in various at-risk arm positions. The purpose of this study was to evaluate the biomechanical effectiveness of a posterior labral repair in the setting of a clinically relevant bone loss model using 3-dimensional computed tomography modeling of patients with recurrent posterior shoulder instability in various at-risk arm positions. Methods: Ten fresh-frozen cadaveric shoulders (mean age: 55.4 years, range: 39-65) were prepared by removing all tissue except the capsule and distal rotator cuff insertions. A joint coordinate frame was established, the specimens were potted, then mounted to a customized fixture on 6-degrees-of-freedom robotic arm. A posterior labral tear was created, then repaired with 3 horizontal mattress sutures and secured by drilling 6 transosseous holes along the peripheral glenoid face exiting the anterior glenoid neck. The sutures were secured for the labral repair states to the mounted fixture under maximal tension and released for the labral tear states and for creating the sequential bone loss models. Bone loss models were created based off a cohort of CT data on patients undergoing revision posterior labral repair surgery to develop 2 clinically relevant 3D models of glenoid bone loss: the first simulating the mean bone loss in this cohort and represented 7% or small bone loss; the second was the mean + 2SD representing 28% or large bone loss. The bone loss was created on each specimen with a 3mm round burr to match each respective 3D printed template (Figure 1). Each specimen was tested in 7 consecutive states: (1) native anatomy, (2) posterior labral tear (6-9 o'clock), (3) posterior labral repair, (4) mean posterior glenoid bone loss with labral tear, (5) mean posterior glenoid bone loss with labral repair, (6) large posterior glenoid bone loss with labral tear, and (7) large posterior glenoid bone loss with labral repair. Each state underwent 75N of posterior-inferior force and 75N of compression during the four tests at 60 and 90 degrees of flexion and 60 and 90 degrees of scaption. Posterior-inferior translation, lateral translation, and dislocation force were measured for each condition. Statistical analysis was performed using two-factor random-intercepts linear mixed-effects models. Results: Compared to the labral tear state, significant increases in dislocation forces occurred with labral repair independent of bone loss state or arm position with values as follows: 14.8N (60° scaption), 12.2N (90° scaption), 11.1N (60° flexion), and 10.1N (90° flexion) with mean 12.1 ± 2.0N across all arm positions (Figure 2). Dislocation force significantly decreased between no bone loss and small bone loss (mean 12.4 ± 0.7N) and between small bone loss and large bone loss (mean 11.8 ± 2.1N) regardless of labral state in all arm positions (table 1). Posterior-inferior translation significantly decreased with labral repair compared to labral tear states independent of bone loss state in all arm positions (Table 1). Lateral translation of the humeral head significant increased when the labrum was repaired independent of bone loss state in all arm positions except 90° scaption and decreased progressively in all bone loss states in all arm positions (table 1). In the native state, the shoulder significantly translated posterior-inferior in scaption at 60° and 90° elevation compared to flexion (p<0.017) and was most unstable in 60° scaption with 29.9 ± 6.1mm posterior-inferior translation (Figure 3). Conclusions: This is the first study to biomechanically evaluate posterior glenoid bone loss using a clinical model in various at-risk arm positions on a 6 degree-of-freedom robot and through a precise linear effects model has established values for the increase in dislocation force posterior labral repair provides regardless of bone loss. The most significant finding of the study is that independent of bone loss, labral repair reduced posterior dislocation forces by 12.1 ± 2.0N and significantly decreased posterior-inferior translation. With a mean decrease in dislocation force of 12.4 ± 0.7N with small (7%) bone loss, labral repair alone may be enough to restore shoulder stability in most individuals. However, significant increases in posterior bone loss may require bony augmentation for adequate stability based on individual factors such as age and activity level. Table 1. Summary of statistically significance among modeled effects for labrum state and bone loss state. Separate linear mixed-effects models were constructed for each combination shoulder position, elevation and measurement. Numeric results reflect the estimated effect of moving from State A -> State B, as indicated in the column header. Up arrows indicate an increasing effect in the measure of interest, while down arrows indicate a decreasing effect, n.s. represents not statistically significant. Figure 2. Bar plots indicating mean and standard deviation values, stratified by shoulder position, elevation, and experimental status of the labrum and glenoid bone loss. Figure 3. Linear mixed-effects model estimates for shoulder position and elevation upon posterior inferior translation among native shoulders. [ABSTRACT FROM AUTHOR]

Valvular regurgitation represents an important cause of cardiovascular morbidity and mortality. Imaging is pivotal in the evaluation of native valve regurgitation and echocardiography is the primary imaging modality for this purpose. The imaging assessment of valvular regurgitation should integrate quantification of the regurgitation, assessment of the valve anatomy and function, and the consequences of valvular disease on cardiac chambers. In clinical practice, the management of patients with valvular regurgitation largely relies on the results of imaging. It is crucial to provide standards that aim at establishing a baseline list of measurements to be performed when assessing native valve regurgitation. The present document aims to present clinical guidance for the multi-modality imaging assessment of native valvular regurgitation. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, it was crucial for the healthcare sector to detect and classify the virus using X-ray and CT scans. This has underlined the need for advanced Deep Learning and Machine Learning approaches to effectively spot and manage the virus's spread. Indeed, researchers worldwide have dynamically participated in the field by publishing an important number of papers across various databases. In this context, we present a bibliometric analysis focused on the detection and classification of COVID-19 using Deep Learning and Machine Learning techniques, based on X-Ray and CT images. We analyzed published documents of the six prominent databases (IEEE Xplore, ACM, MDPI, PubMed, Springer, and ScienceDirect) during the period between 2019 and November 2023. Our results showed that rising forces in economy and technology, especially India, China, Turkey, and Pakistan, began to compete with the great powers in the field of scientific research, which could be seen from their number of publications. Moreover, researchers contributed to Deep Learning techniques more than the use of Machine Learning techniques or the use of both together and preferred to submit their works to Springer Database. An important result was that more than 57% documents were published as Journal Articles, which was an important portion compared to other publication types (conference papers and book chapters). Moreover, the PubMed journal Multimedia Tools and Applications' tops the list of journals with a total of 29 published articles. [ABSTRACT FROM AUTHOR]

This report describes The University of Texas Student Cluster Competition team’s effort to reproduce the results of “MemXCT: memory-centric X-ray CT reconstruction with massive parallelization” (Hidayetoğlu et al., 2019). The article details a new memory-centric approach that reconstructs X-ray computed tomography (XCT) from noisy raw data. In our reproduction experiments, we utilized Microsoft Azure’s CycleCloud tool to provision, orchestrate, and manage our computing cluster in the cloud. In particular, we scheduled and benchmarked reconstruction workloads using Azure’s CPU-based HC44rs and GPU-based NC12s v2 virtual machine (VM) types to evaluate the scalability properties of the reconstruction approach and the performance differences between architectures. The HC44rs VMs contained 44 Intel Xeon Platinum cores, while the NC12s v2 VM was equipped with two NVIDIA P100 GPUs. We used a recent version of Intel’s compiler stack with the MKL library for our CPU code along with CUDA 11.1 on GPUs. Overall, our results confirm the findings of the original article, demonstrating similar acceleration on GPUs and scalability properties on CPUs. Digital artifacts from these experiments are available at: 10.5281/zenodo.5598108 [ABSTRACT FROM AUTHOR]

Cardiac computed tomography (CT) was initially developed as a non-invasive diagnostic tool to detect and quantify coronary stenosis. Thanks to the rapid technological development, cardiac CT has become a comprehensive imaging modality which offers anatomical and functional information to guide patient management. This is the second of two complementary documents endorsed by the European Association of Cardiovascular Imaging aiming to give updated indications on the appropriate use of cardiac CT in different clinical scenarios. In this article, emerging CT technologies and biomarkers, such as CT-derived fractional flow reserve, perfusion imaging, and pericoronary adipose tissue attenuation, are described. In addition, the role of cardiac CT in the evaluation of atherosclerotic plaque, cardiomyopathies, structural heart disease, and congenital heart disease is revised. [ABSTRACT FROM AUTHOR]

Convolution Neural Networks (CNN) can quickly diagnose COVID-19 patients by analyzing computed tomography (CT) images of the lung, thereby effectively preventing the spread of COVID-19. However, the existing CNN-based COVID-19 diagnosis models do consider the problem that the lung images of COVID-19 patients in the early stage and incubation period are extremely similar to those of the non-COVID-19 population. Which reduces the model's classification sensitivity, resulting in a higher probability of the model misdiagnosing COVID-19 patients as non-COVID-19 people. To solve the problem, this paper first attempts to apply triplet loss and center loss to the field of COVID-19 image classification, combining softmax loss to design a jointly supervised metric loss function COVID Triplet-Center Loss (COVID-TCL). Triplet loss can increase inter-class discreteness, and center loss can improve intra-class compactness. Therefore, COVID-TCL can help the CNN-based model to extract more discriminative features and strengthen the diagnostic capacity of COVID-19 patients in the early stage and incubation period. Meanwhile, we use the extreme gradient boosting (XGBoost) as a classifier to design a COVID-19 images classification model of CNN-XGBoost architecture, to further improve the CNN-based model's classification effect and operation efficiency. The experiment shows that the classification accuracy of the model proposed in this paper is 97.41%, and the sensitivity is 97.61%, which is higher than the other 7 reference models. The COVID-TCL can effectively improve the classification sensitivity of the CNN-based model, the CNN-XGBoost architecture can further improve the CNN-based model's classification effect. [ABSTRACT FROM AUTHOR]

Purpose: Complex multifragmentary fractures of the pelvis and lower limb are a major challenge for operative orthopaedic surgery. The successful metallic osteosynthesis of the fractures requires an extensive planning process, which can be dramatically improved with the 3D printed anatomical models -- replicas of the bones with high fidelity generated from CT and MRI imaging studies. The models represent the spatial properties of the skeleton with a dimensional error of approximately 8 μm/mm. They can be manufactured easily and with high reproducibility with commercial or open-access software and FDM 3D printing. Orthopaedic surgeons use the preoperative models as a highly accurate physical model of complex fractures and allow them to choose and prepare the optimal operation window, surgical tools, metallic implants, and as a template for recontouring (pre-bending) of fixation plates, which will be used during the surgery. The approach provides a new level of personalisation in operative orthopaedic surgery and significantly reduces the duration of the operation, the amount of blood loss and the intraoperative X-rays. The proper anatomical repositioning of the fracture is achieved at a higher rate in the surgeries, which are planned with 3D-printed anatomical models. The planning of surgical operations with 3D-printed models increases the overall effectiveness of the surgery, reduces the rate of post-surgical complications, and allows for a patient-specific approach. The paper will describe the methods for manufacturing accurate 3D-printed anatomical models representing complex fractures and their application for preoperative planning of orthopaedic operation. Design/methodology/approach: The anatomical 3D models were generated from CT datasets with open-access medical informatics software (3D Slicer) and 3D printed on an FDM 3D printer with minimal thermal deformation (Polylactate, PLA). The finished models were used for preoperative planning of complex orthopaedic operations, including high-energy multifragmentary hip, knee and ankle fractures. The preoperative planning included selecting surgical access, preparing tools and implants, and contouring (pre-bending) metal plates for metallic osteosynthesis. Several parameters, such as operation time, blood loss, intraoperative X-rays, and the achievement of anatomical reduction of the fractures, were observed in order to measure the quality of the operations. Findings: Accurate anthropomorphic 3D models representing the spatial properties of the bones can be generated from tomographic imaging studies easily and accurately, even with open-source software. They can be utilised as a tool for preoperatively planning complex orthopaedical operations of the lower limb. Using 3D-printed models allows a patient-specific approach, which leads to good anatomical reduction and favourable functional results in complex surgeries regarding the pelvis, acetabulum, tibial plateau, and calcaneus. Practical implications: The methods described in the paper are routinely used for the preoperative planning of complex orthopaedical operations regarding the lower limb. In the future, they will be combined with the implementation of 3D-printed personalised titanium implants to achieve good anatomical reduction even for the most challenging multigragmental fractures. Originality/value: In the paper, we described the technical aspects and clinical considerations for the preoperative planning of complex orthopaedical operations, which can assist engineers and clinicians alike in implementing the useful method in clinical practice. [ABSTRACT FROM AUTHOR]

Key Clinical Message: The phenomenon of vessel pedicle ossification is a noteworthy aspect of the repair and reconstruction of maxillofacial defects. Imaging findings typically reveal high‐density shadows within the vascular pedicle pathway, which may be managed through conservative observation or surgical intervention as deemed appropriate. Vessel pedicle ossification is a relatively uncommon complication associated with the reconstruction of oral and maxillofacial tissue defects using free tissue flap repair. In this paper, we report a case of pedicle ossification and conduct a comprehensive review of previous literature. A 39‐year‐old man presented with a limited ability to open his mouth 6 months after fibular flap reconstruction of the mandible. Plain film X‐ray and computed tomography (CT) indicated pedicle ossification. Two years after the initial operation, the restriction in the patient's ability to open his mouth had not worsened, although there were more pronounced radiographic abnormalities. [ABSTRACT FROM AUTHOR]

Objectives: There is significant controversy regarding ideal medial patellofemoral ligament reconstruction (MPFLR) femoral tunnel position in the pediatric setting. The authors identified 3 main gaps in knowledge. First, the position of the radiographic MPFLR start point (Schottle's point) relative to the medial distal femoral epiphysis is not well defined. Second, although anatomic studies have suggested tunnel trajectories that avoid physeal contact, these trajectories are not based upon the widely used Schottle's point, providing limited intraoperative utility. Third, prior studies provide conflicting data regarding position of the MPFL origin relative to the distal femoral physis, particularly in younger patients. The purpose of this study was to determine the proximity of Schottle's point to the medial distal femoral physis and the medial epicondyle using a digitally reconstructed radiographs (DRR) and three-dimensional computed tomography (CT) models. Methods: The institutional picture archiving and communication system (PACS) was queried for CT imaging studies of pediatric knees with open physes. CT data were imported to a Python based, open-source image processing software and were transformed to create true lateral digitally reconstructed radiographs (DRR) (Figure 1) and 3-dimensional (3D) renderings of the distal femur (Figure 2). Schottle's point and the medial epicondyle were registered using fiducial markers and 3D distance measurements were then obtained from Schottle's point on the medial cortex to 1) the medial epicondyle, 2) the physeal point directly superior to Schottle's point, and 3) the shortest distance to the medial physis on the cortical surface. A 6-millimeter circle was used to simulate reaming diameter and physeal intersections were tabulated. Results: 49 pediatric knee CT scans with open physes were included in the data. Average patient age was 13.0 ± 2.3 years (range: 6-17 years). Mean minimum distance from the medial physis to Schottle's point was 9.9 mm ± 3.0mm (range: 3.4-16.1 mm) (Figure 3). In 49 of 49 cases (100%), Schottle's point was distal to the physis. Schottle's point was localized at a mean distance of 7.5mm ± 3.14mm posterior to the medial epicondyle and 6.1mm ± 2.9mm superior to the medial epicondyle. Using a 6mm reaming diameter, 3 (6%) femurs in our study would have violation of the medial distal femoral physis. Moving the start point 3mm distally would result in 0 of 49 (0%) having physeal injury. Conclusions: Historically, characterizing the position of the origin of the MPFL on the medial condyle relative to the medial distal femoral physis has been challenging. Prior cadaveric studies have suggested the MPFL originates proximal to the physis in younger patients (<7 years). However, more recent cadaveric studies have challenged this idea, finding the bony landmarks of the MPFL origin to be distal to the physis. Although these studies have sparked significant discussion regarding the pediatric MPFL origin, they have small numbers of specimens. Using a more surgically relevant approach, the present study demonstrates that Schottle's point is consistently distal to the distal femoral physis. Prior studies have suggested anterior and distal drill trajectories that may minimize physeal injury. Although useful, these studies do not assess drilling path relative to the commonly used radiographically identified starting point, Schottle's point. The present study complements this prior work by addressing the radiographic start point upon which the drill trajectory is based intraoperatively. Based on the present study, the use of Schottle's point without distalization would lead to physeal injury in 6% of cases. Further, prior cadaveric anatomic studies are subject to limitations of the availability and expense of pediatric specimens and are therefore limited to small sample sizes. The methodology of the present study, by using readily available fine cut CT data, is not subject to such constraints. The present investigation offers a larger sample size than any previously published pediatric MPFL anatomic study and uses a highly accurate and repeatable methodology. This unique methodology may be more broadly applicable to the study of pediatric procedures near the physis. The radiographically defined surgical start point for MPFL femoral tunnel placement (Schottle's point), is consistently distal to the medial distal femoral physis. Mean minimum distance from Schottle's point to the physis on the medial cortex is 9.9mm. Using Schottle's point for the start of tunnel drilling leads to physis violation in 6% of cases, when using a 6mm reamer. Distalization of the start point by 3mm leads to avoidance of physeal injury in all cases. Figure 1. Digitally Reconstructed Radiograph with Identification of Schottle's Point Figure 2. 3D Rendering with Physeal Distance Measurement Figure 3. Saggital Plane Plot of Schottle's Point and Closest Point on Medial Physis [ABSTRACT FROM AUTHOR]

This paper focuses on how regulatory bodies respond to artificial intelligence (AI)-enabled medical devices. To achieve this, we present a comparative overview of the United States (USA), European Union (EU), and China. Our search in the governmental database identified 59 AI medical devices approved in China as of July 2023. In comparison to the rules-based regulatory approach in China, the approaches in the USA and EU are more standards-oriented. [ABSTRACT FROM AUTHOR]

This paper proposes a method for obtaining adaptive and high-precision surface meshes directly from Industrial computed tomography (ICT) projection data. Firstly, an adaptive volume octree is recursively constructed from top to bottom using a two-stage geometric error metric function. The CT values and gradient values at the nodes are computed using the Feldkamp–Davis–Kress (FDK) reconstruction algorithm and its derivatives, achieving sub-voxel precision. Next, feature vertices are calculated based on Quadratic error functions (QEFs), and a dual mesh is constructed. Finally, Hermite interpolation is used to determine the iso-surface vertices, and the Convex Contouring lookup table is employed to accurately extract the iso-surface contours, resulting in high-precision and crack-free surface meshes. Experimental results show that the surface meshes generated by the proposed method exhibit superior dimensional accuracy, form and position accuracy, and surface model accuracy compared to traditional methods, and the dimensional accuracy has been enhanced by approximately 10–30%. [ABSTRACT FROM AUTHOR]

Radiological imaging is a globally prevalent diagnostic method, yet the free text contained in radiology reports is not frequently used for secondary purposes. Natural Language Processing can provide structured data retrieved from these reports. This paper provides a summary of the current state of research on Large Language Model (LLM) based approaches for information extraction (IE) from radiology reports. We conduct a scoping review that follows the PRISMA-ScR guideline. Queries of five databases were conducted on August 1st 2023. Among the 34 studies that met inclusion criteria, only pre-transformer and encoder-based models are described. External validation shows a general performance decrease, although LLMs might improve generalizability of IE approaches. Reports related to CT and MRI examinations, as well as thoracic reports, prevail. Most common challenges reported are missing validation on external data and augmentation of the described methods. Different reporting granularities affect the comparability and transparency of approaches. [ABSTRACT FROM AUTHOR]

Objective: To conduct a bibliometric analysis of the prospects and obstacles associated with dual- and multi-energy CT in thoracic disease, emphasizing its current standing, advantages, and areas requiring attention. Methods: The Web of Science Core Collection was queried for relevant publications in dual- and multi-energy CT and thoracic applications without a limit on publication date or language. The Bibliometrix packages, VOSviewer, and CiteSpace were used for data analysis. Bibliometric techniques utilized were co-authorship analyses, trend topics, thematic map analyses, thematic evolution analyses, source's production over time, corresponding author's countries, and a treemap of authors' keywords. Results: A total of 1992 publications and 7200 authors from 313 different sources were examined in this study. The first available document was published in November 1982, and the most cited article was cited 1200 times. Siemens AG in Germany emerged as the most prominent author affiliation, with a total of 221 published articles. The most represented scientific journals were the "European Radiology" (181 articles, h-index = 46), followed by the "European Journal of Radiology" (148 articles, h-index = 34). Most of the papers were from Germany, the USA, or China. Both the keyword and topic analyses showed the history of dual- and multi-energy CT and the evolution of its application hotspots in the chest. Conclusion: Our study illustrates the latest advances in dual- and multi-energy CT and its increasingly prominent applications in the chest, especially in lung parenchymal diseases and coronary artery diseases. Photon-counting CT and artificial intelligence will be the emerging hot technologies that continue to develop in the future. Critical relevance statement: This study aims to provide valuable insights into energy-based imaging in chest disease, validating the clinical application of multi-energy CT together with photon-counting CT and effectively increasing utilization in clinical practice. Key Points: Bibliometric analysis is fundamental to understanding the current and future state of dual- and multi-energy CT. Research trends and leading topics included coronary artery disease, pulmonary embolism, and radiation dose. All analyses indicate a growing interest in the use of energy-based imaging techniques for thoracic applications. [ABSTRACT FROM AUTHOR]

The corrosion of steel rebars is a prevalent factor leading to the diminished durability of reinforced concrete structures, posing a significant challenge to the safety of structural engineering. To tackle this issue, extensive research has been conducted, yielding a variety of theoretical insights and remedial measures. This review paper offers an exhaustive analysis of the passivation processes and corrosion mechanisms affecting steel rebars in reinforced concrete. It identifies key factors such as chloride ion penetration and concrete carbonization that primarily influence rebar corrosion. Furthermore, this paper discusses a suite of strategies designed to enhance the longevity of reinforced concrete structures. These include improving the concrete protective layer's quality and bolstering the rebars' corrosion resistance. As corrosion testing is essential for evaluating steel rebars' resistance, this paper also details natural and accelerated corrosion testing methods applicable to rebars in concrete environments. Additionally, this paper deeply presents an exploration of the use of X-ray computed tomography (X-CT) technology for analyzing the corrosion byproducts and the interface characteristics of steel bars. Recognizing the close relationship between steel bar corrosion research and microstructural properties, this paper highlights the pivotal role of X-CT in advancing this field of study. In conclusion, this paper synthesizes the current state of knowledge and provides a prospective outlook on future research directions on the corrosion of steel rebars within reinforced concrete structures. [ABSTRACT FROM AUTHOR]

Medical image registration has become pivotal in recent years with the integration of various imaging modalities like X-ray, ultrasound, MRI, and CT scans, enabling comprehensive analysis and diagnosis of biological structures. This paper provides a comprehensive review of registration techniques for medical images, with an in-depth focus on 2D-2D image registration methods. While 3D registration is briefly touched upon, the primary emphasis remains on 2D techniques and their applications. This review covers registration techniques for diverse modalities, including unimodal, multimodal, interpatient, and intra-patient. The paper explores the challenges encountered in medical image registration, including geometric distortion, differences in image properties, outliers, and optimization convergence, and discusses their impact on registration accuracy and reliability. Strategies for addressing these challenges are highlighted, emphasizing the need for continual innovation and refinement of techniques to enhance the accuracy and reliability of medical image registration systems. The paper concludes by emphasizing the importance of accurate medical image registration in improving diagnosis. [ABSTRACT FROM AUTHOR]

In this technical report, we focus on reproducing the results reported in the paper “MemXCT: Memory-Centric X-ray CT Reconstruction with Massive Parallelization” [1]. MemXCT is a scalable approach to X-ray Computed Tomography reconstruction which removes redundant computation. We reproduced the single CPU/GPU performance as well as strong scaling experiments. We set up our configurations on Microsoft Azure CycleCloud and have two clusters. One cluster has 4 nodes with 60 CPUs on each node and the other cluster has 4 nodes with 4 NVIDIA V100 GPUs on each node. Both clusters come with InfiniBand. The original author conducted his experiments on Theta and Blue Waters supercomputers. We were able to reproduce part of the results in the original paper, however, failed to produce similar performance on other experiments. This report was submitted as part of the reproducibility challenge in SC20 Student Cluster Competition. Digital artifacts from these experiments are available at: 10.5281/zenodo.5598108. [ABSTRACT FROM AUTHOR]

Oncology has emerged as a crucial field of study in the domain of medicine. Computed tomography has gained widespread adoption as a radiological modality for the identification and characterisation of pathologies, particularly in oncology, enabling precise identification of affected organs and tissues. However, achieving accurate liver segmentation in computed tomography scans remains a challenge due to the presence of artefacts and the varying densities of soft tissues and adjacent organs. This paper compares artificial intelligence algorithms and traditional medical image processing techniques to assist radiologists in liver segmentation in computed tomography scans and evaluates their accuracy and efficiency. Despite notable progress in the field, the limited availability of public datasets remains a significant barrier to broad participation in research studies and replication of methodologies. Future directions should focus on increasing the accessibility of public datasets, establishing standardised evaluation metrics, and advancing the development of three-dimensional segmentation techniques. In addition, maintaining a collaborative relationship between technological advances and medical expertise is essential to ensure that these innovations not only achieve technical accuracy, but also remain aligned with clinical needs and realities. This synergy ensures their applicability and effectiveness in real-world healthcare environments. [ABSTRACT FROM AUTHOR]

KRAS is a pathogenic gene frequently implicated in non-small cell lung cancer (NSCLC). However, biopsy as a diagnostic method has practical limitations. Therefore, it is important to accurately determine the mutation status of the KRAS gene non-invasively by combining NSCLC CT images and genetic data for early diagnosis and subsequent targeted therapy of patients. This paper proposes a Semi-supervised Multimodal Multiscale Attention Model (S2MMAM). S2MMAM comprises a Supervised Multilevel Fusion Segmentation Network (SMF-SN) and a Semi-supervised Multimodal Fusion Classification Network (S2MF-CN). S2MMAM facilitates the execution of the classification task by transferring the useful information captured in SMF-SN to the S2MF-CN to improve the model prediction accuracy. In SMF-SN, we propose a Triple Attention-guided Feature Aggregation module for obtaining segmentation features that incorporate high-level semantic abstract features and low-level semantic detail features. Segmentation features provide pre-guidance and key information expansion for S2MF-CN. S2MF-CN shares the encoder and decoder parameters of SMF-SN, which enables S2MF-CN to obtain rich classification features. S2MF-CN uses the proposed Intra and Inter Mutual Guidance Attention Fusion (I2MGAF) module to first guide segmentation and classification feature fusion to extract hidden multi-scale contextual information. I2MGAF then guides the multidimensional fusion of genetic data and CT image data to compensate for the lack of information in single modality data. S2MMAM achieved 83.27% AUC and 81.67% accuracy in predicting KRAS gene mutation status in NSCLC. This method uses medical image CT and genetic data to effectively improve the accuracy of predicting KRAS gene mutation status in NSCLC. [ABSTRACT FROM AUTHOR]

The article deals with the use of computed tomography, an advanced method for evaluating the quality of aluminium castings. Casting quality is a key factor in ensuring safety and reliability in industrial applications. Computed tomography is a comprehensive method allowing a three-dimensional, high-resolution view of the internal structure of materials. The main focus of this paper is the study of BRACKET REAR aluminium castings, manufactured in two-piece moulds using a high-pressure die-casting technology. In this paper, four castings have been analysed which are produced in one cycle. The focus is on the problem of porosity and open stagnation in the castings. A numerical simulation has also been used to illustrate the occurrence of porosity, which can be used to determine both the occurrence of porosity and the occurrence of unfilled volume. The experimental part of the paper describes the methods used to evaluate the BRACKET REAR castings. The numerical simulation was performed in ProCAST 18.0 to determine the occurrence of porosity in the castings under study. The evaluation of computed tomography was performed in myVGL 3.0 2023 software to analyse the internal defects in the castings. The evaluation focused on assessing internal defects and their subsequent effect on the functionality of the final casting. [ABSTRACT FROM AUTHOR]

Automatic and accurate segmentation of tumor area from rectal CT image plays an extremely key role in the treatment and diagnosis of rectal cancer. This paper proposes the MR-U-Net network model. The improvement is that a pair of encoder and decoder is added longitudinally to the U-shaped structure, which is the network structure of the fifth layer, and a residual module is added horizontally to the encoder and decoder of each layer. This model is used to conduct targeted research on the automatic segmentation method of rectal cancer. [H. Gao et al., Rectal tumor segmentation method based on U-Net improved model, J. Comput. Appl.40(8) (2020) 2392–2397] also improved U-Net and used the same dataset as this paper, but the Dice coefficient of all targets was only 83.15%, and the Dice coefficient of small targets was only 87.17%. This paper evaluates the improved MR-U-Net network model with the three indicators of precision, recall and Dice coefficient, and finds that in comparison to Ref. 4 the precision is 95.13%, 2.29% higher than the former work, recall is 94.28%, higher than the former work by 0.34%, Dice coefficient of all targets is 88.45%, increased by 5.3% compared with the former work, and the small targets Dice coefficient is increased by 1.28%, which is the best optimization state of this paper. Experiments show that for datasets with extremely skewed positive and negative samples, the MR-U-Net network structure after improving the hyperparameters in the optimizer can more accurately segment the rectal CT tumor lesion area. [ABSTRACT FROM AUTHOR]

Signal‐to‐noise ratio and spatial resolution are quantitatively analysed in the context of in‐line (propagation based) X‐ray phase‐contrast imaging. It is known that free‐space propagation of a coherent X‐ray beam from the imaged object to the detector plane, followed by phase retrieval in accordance with Paganin's method, can increase the signal‐to‐noise in the resultant images without deteriorating the spatial resolution. This results in violation of the noise‐resolution uncertainty principle and demonstrates 'unreasonable' effectiveness of the method. On the other hand, when the process of free‐space propagation is performed in software, using the detected intensity distribution in the object plane, it cannot reproduce the same effectiveness, due to the amplification of photon shot noise. Here, it is shown that the performance of Paganin's method is determined by just two dimensionless parameters: the Fresnel number and the ratio of the real decrement to the imaginary part of the refractive index of the imaged object. The relevant theoretical analysis is performed first, followed by computer simulations and then by a brief test using experimental images collected at a synchrotron beamline. More extensive experimental tests will be presented in the second part of this paper. [ABSTRACT FROM AUTHOR]

Mesenteric ischemia diagnosis is challenging, with an overall mortality of up to 50% of cases despite advances in treatment. The main problem that affects the outcome is delayed diagnosis because of non-specific clinical presentation. Multi-Detector CT Angiography (MDCTA) is the first-line investigation for the suspected diagnosis of vascular abdominal pathologies and the diagnostic test of choice in suspected mesenteric bowel ischemia. MDCTA can accurately detect the presence of arterial and venous thrombosis, determine the extent and the gastrointestinal tract involved, and provide detailed information determining the subtype and the stage progression of the diseases, helping clinicians and surgeons with appropriate management. CT (Computed Tomography) can differentiate forms that are still susceptible to pharmacological or interventional treatment (NOM = non-operative management) from advanced disease with transmural necrosis in which a surgical approach is required. Knowledge of CT imaging patterns and corresponding vascular pathways is mandatory in emergency settings to reach a prompt and accurate diagnosis. The aims of this paper are 1. to provide technical information about the optimal CTA (CT Angiography) protocol; 2. to explain the CTA arterial and venous supply to the gastrointestinal tract and the relevant ischemic pattern; and 3. to describe vascular, bowel, and extraintestinal CT findings for the diagnosis of acute mesenteric ischemia. [ABSTRACT FROM AUTHOR]

Trauma and orthopedic surgery commonly rely on intraoperative radiography or fluoroscopy, which are essential for visualizing patient anatomy and safely completing surgical procedures. However, these imaging methods generate ionizing radiation, which in high doses carries a potential health risk to patients and operating personnel. There is an established need for formal training in obtaining precise intraoperative imaging while minimizing radiation exposure. Virtual reality (VR) simulation serves as a promising tool for orthopaedic trainees to develop skills in safe intraoperative imaging, without posing harm to patients, operating room staff, or themselves. This paper aims to provide a brief overview of literature surrounding VR training for intraoperative imaging in orthopaedic surgery. In addition, we discuss areas for improvement and future directions for development in the field. [ABSTRACT FROM AUTHOR]

Background: In planning radiotherapy treatments, computed tomography (CT) has become a crucial tool. CT scans involve exposure to ionizing radiation, which can increase the risk of cancer and other adverse health effects in patients. Ionizing radiation doses for medical exposure must be kept "As Low As Reasonably Achievable". Very few articles on guidelines for radiotherapy-computed tomography scans are available. This paper reviews the current literature on radiation dose optimization based on the effective dose and diagnostic reference level (DRL) for head, neck, and pelvic CT procedures used in radiation therapy planning. This paper explores the strategies used to optimize radiation doses, and high-quality images for diagnosis and treatment planning. Methods: A cross-sectional study was conducted on 300 patients with head, neck, and pelvic region cancer in our institution. The DRL, effective dose, volumetric CT dose index (CTDIvol), and dose-length product (DLP) for the present and optimized protocol were calculated. DRLs were proposed for the DLP using the 75th percentile of the distribution. The DLP is a measure of the radiation dose received by a patient during a CT scan and is calculated by multiplying the CT dose index (CTDI) by the scan length. To calculate a DRL from a DLP, a large dataset of DLP values obtained from a specific imaging procedure must be collected and can be used to determine the median or 75th-percentile DLP value for each imaging procedure. Results: Significant variations were found in the DLP, CTDIvol, and effective dose when we compared both the standard protocol and the optimized protocol. Also, the optimized protocol was compared with other diagnostic and radiotherapy CT scan studies conducted by other centers. As a result, we found that our institution's DRL was significantly low. The optimized dose protocol showed a reduction in the CTDIvol (70% and 63%), DLP (60% and 61%), and effective dose (67% and 62%) for both head, neck, and pelvic scans. Conclusions: Optimized protocol DRLs were proposed for comparison purposes. [ABSTRACT FROM AUTHOR]

Pseudomyxoma peritonei is a rare pathological condition characterized by mucinous tumor tissue implants on the peritoneal surface. Although the cause of Pseudomyxoma peritonei has been extensively studied, the prevailing agreement is that it stems from mucinous tumors that occur in the ovaries or appendix. The tumor tissue typically remains localized to the peritoneum and does not exhibit extraperitoneal spread. Patients with Pseudomyxoma peritonei may present with symptoms such as abdominal pain, bloating, loss of appetite, and shortness of breath. Computerized Tomography is commonly used for diagnostic purposes. The treatment of Pseudomyxoma peritonei typically involves surgical evacuation of the tumoral tissue, followed by cytoreduction and Hyperthermic Intraperitoneal Chemotherapy. While effective treatment options are available, some patients may require repeated surgeries over an extended period. This paper reports on a case study of a patient with a history of recurrent Pseudomyxoma peritonei, necessitating multiple surgical interventions over a decade. The paper concludes with a review of the relevant literature. [ABSTRACT FROM AUTHOR]

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COVID-19 is a highly contagious epidemic, and detection in the incipient phase is essential to curb the expansion of the disease. Chest Xrays are used in detecting COVID-19 infection. Lung's images and CT -Scan photos are available for coronavirus analysis. This paper is composed of deep learning techniques and methods used to detect COVID-19 contamination in the lung images. The methods employed and collected datasets used for testing metrics are summed up. The Analytical metrics utilized by the methods which are completely comparable. Through this work, we have taken a perspective on COVID-19 affected chest x-ray scanners and healthy patients. After sorting and pre-processing the images and implementing the data addition, we applied deep-learning-based CNN models to compare their performance with other models. The aim is to provide a helping hand to the most distressed medical professionals who are analyzing images with two eyes, detect COVID-19. According to this analysis we provide a proposed methodology that uses deep learning, dropout technique with python language on Google Colab platform for reduces over-fitting by this deep learning technology. During the testing phase, I got 98.1% accuracy by increasing convolution layer and dropout layer. Our proposed methodology gives better accuracy than other compared models. The primary goal of this paper is to present research on medical image processing and define and implement the proposed CNN model. [ABSTRACT FROM AUTHOR]

This report analyzes the reproducibility of the paper “MemXCT: Memory-Centric X-ray CT Reconstruction with Massive Parallelization” by Hidayetoğlu et al. in the cloud as part of the SC20 Virtual Student Cluster Competition (VSCC). To reproduce the results from the original work, the ETH Zürich SC20 VSCC team performed a series of CT reconstructions and performed a scaling study using three provided sinograms. All experimental runs were performed during the SC20 VSCC on an HPC cluster hosted in the Microsoft Azure CycleCloud. In this paper, we describe discrepancies in results as a factor of the differences in experiment environments and insufficient parameter tuning. We successfully reproduce the single device performance and partially reproduce the strong scaling behavior. Digital artifacts from these experiments are available at: 10.5281/zenodo.5598108. [ABSTRACT FROM AUTHOR]

Hidayetoğlu et al. propose a novel memory-centric algorithm to reconstruct X-ray CT images in the SC19 article entitled “MemXCT: Memory-Centric X-ray CT Reconstruction with Massive Parallelization”. They formulate the reconstruction with several SpMVs, and propose two memory-centric optimizations to improve cache locality for better memory bandwidth utilization, i.e., a two-level pseudo-Hilbert ordering and a multi-stage input buffering. In this article, we present our results on reproducing that article to show its effectiveness and generality, as part of the SC20 Student Cluster Competition Reproducibility Challenge. We reproduce the execution time and memory bandwidth tests in that article on various architectures, including Intel CPUs, AMD CPUs, and NVIDIA GPUs. We further analyze the bottleneck on different architectures by comparing the achieved memory bandwidth with the peak bandwidth on those architectures. We then reproduce the strong scaling test on CPU and GPU clusters with different scales, and use the proposed algorithm to reconstruct three new X-ray computed tomograms. [ABSTRACT FROM AUTHOR]

Lung disease is one of the most harmful diseases in traditional days and is the same nowadays. Early detection is one of the most crucial ways to prevent a human from developing these types of diseases. Many researchers are involved in finding various techniques for predicting the accuracy of the diseases. On the basis of the machine learning algorithm, it was not possible to predict the better accuracy when compared to the deep learning technique; this work has proposed enhanced artificial neural network approaches for the accuracy of lung diseases. Here, the discrete Fourier transform and the Burg auto-regression techniques are used for extracting the computed tomography (CT) scan images, and feature reduction takes place by using principle component analysis (PCA). This proposed work has used the 120 subjective datasets from public landmarks with and without lung diseases. The given dataset is trained by using an enhanced artificial neural network (ANN). The preprocessing techniques are handled by using a Gaussian filter; thus, our proposed approach provides enhanced classification accuracy. Finally, our proposed method is compared with the existing machine learning approach based on its accuracy. [ABSTRACT FROM AUTHOR]

With over 200 peer-reviewed papers published over the last 20 years, 3D modelling is no longer a gimmick but an established and increasingly common analytical tool for stone artefact analysis. Laser and structured light scanning, photogrammetry, and CT scanning have all been used to model stone artefacts. These have been combined with a variety of different analytical approaches, from geometric morphometrics to custom reduction indices to digital elevation maps. 3D lithic analyses are increasingly global in scope and studies aim to address an ever-broadening breadth of research topics ranging from testing the functional efficiency of artefacts to assessing the cognitive capabilities of hominid populations. While the impact of the computational revolution on lithic analysis has been reviewed, the impact of 3D modelling on lithic analysis has yet to be comprehensively assessed. This paper presents a review of how 3D modelling in particular has impacted the field of stone artefact analysis. It combines a quantitative bibliometric analysis with a qualitative review to assess just how "revolutionary" 3D modelling has been for lithic analysis. It explores trends in the use of 3D modelling in stone artefact analysis, its impact on the wider lithic analysis field, and methodological, regional and theoretical gaps which future research projects could explore. [ABSTRACT FROM AUTHOR]