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The growing demand for sustainable and energy-efficient buildings has highlighted the need for reliable and accurate methods to detect fenestration deterioration and assess UV radiation transmission. Traditional detection techniques, such as spectrophotometers and radiometers, discussed in Part I, are often expensive and invasive, necessitating more accessible and cost-effective solutions. This study, which is Part II, provides an in-depth exploration of the concepts and methodologies underlying UV bandpass-filtered imaging, advanced image processing techniques, and the mechanisms of pixel transformation equations. The aim is to lay the groundwork for a unified approach to detecting ultraviolet (UV) radiation transmission in fenestration glazing. By exploiting the capabilities of digital imaging devices, including widely accessible smartphones, and integrating them with robust segmentation techniques and mathematical transformations, this research paves the way for an innovative and potentially democratized approach to UV detection in fenestration glazing. However, further research is required to optimize and tailor the detection methods and approaches using digital imaging, UV photography, image processing, and computer vision for specific applications in the fenestration industry and detecting UV transmission. The complex interplay of various physical phenomena related to UV radiation, digital imaging, and the unique characteristics of fenestration glazing necessitates the development of a cohesive framework that synergizes these techniques while addressing these intricacies. While extensively reviewing existing techniques, this paper highlights these challenges and sets the direction for future research in the UV imaging domain.

The morphology of granular materials can be characterized two or three-dimensionally by different measurement techniques such as micro-computed tomography (μCT), static and dynamic image analysis (SIA and DIA). Because there are fundamental differences in the working principles among these techniques, their efficacy in characterizing the morphology of granular particles needs to be precisely examined but has not yet been scientifically evaluated. In this study, a systematic evaluation of the efficacy of four DIA devices and a light microscope (LM) with reference to μCT was made by selecting statistically representative samples of three standard sands which covered a wide range of particle form and angularity. Morphological data of these sands were used and probability distributions obtained from the different imaging techniques were compared with μCT results using a precise quantitative measure based on the information theory. The results revealed that most of the DIA devices chosen were capable of providing accurate measurements for the coarse descriptors such as aspect ratio in sands across a broad particle size range, whereas some devices require improvement in their camera resolution to produce accurate measurements for fine sands. Modifying device configuration and/or computational algorithm to either use the captured image with the largest area or obtain an average from multiple random projections in the order of 100 can improve the accuracy of morphology characterization in DIA devices. LM with proper imaging and image processing can provide results comparable to μCT. [ABSTRACT FROM AUTHOR]

3D concrete printing (3DCP) is an innovative technology for constructing complex freeform structures that are difficult or expensive to build using conventional construction methods. The printing of double-curved shells and aesthetically pleasing geometries for façade panels and roof elements requires a detailed investigation of the load-carrying capacity and failure mode during complex loading. Moreover, integrating reinforcement into printed elements is one of the major challenges in 3DCP for manufacturing structural components. Textile reinforcement has high formability and tensile strength and can be used as an in-process reinforcing method during printing. In this study, one layer of alkali-resistant glass textile was used to reinforce the 3D printed and mould-cast high-performance concrete curved members. The commonly used concrete printing nozzle was modified to allow ease in textile placement along the printing path. Further, the feasibility of the modified nozzle was evaluated by printing two different curved structures and was validated. In addition, two different curvatures of curved elements, with and without textile reinforcement were printed to study the effect of textile reinforcement and geometry when subjected to a point load in the middle. The deformation behaviour, crack development, and propagation were monitored using digital image correlation. It was observed that the textile reinforcement enhances the interlayer bonding leading to slower crack propagation and enhanced load-carrying capacity. An increase of about 10 % in the peak load-carrying capacity of 3D printed specimens was observed with the addition of textile reinforcement when compared to their mould-cast. Also, 3D printed specimens was observed to have larger deformation ductility compared to mould-cast specimens. Further, the textile aligns better with increasing curvature which enhances the resistance of membrane forces more uniformly resulting in a 15.5 % increase in the ultimate moment capacity. In addition, the first crack load and the ultimate load were predicted based on the arch equations and the results showed that the current method predicts the capacity with reasonable accuracy. • In-process reinforcement with textiles during printing is a potential reinforcing method. • Modified nozzle aligns textile reinforcement easily along any desired printing path. • Textile reinforcement improves interlayer bridging and orients better for higher curvatures. • Ultimate moment capacity and crack propagation are improved significantly with textile reinforcement. [ABSTRACT FROM AUTHOR]

This work proposes the synthesis of a new polymer with imprinted ions (IIP) for the pre-concentration of uranium in natural waters using digital imaging as a detection technique. The polymer was synthesized using 2-(5-bromo-2-pyridylazo)-5-diethylaminophenol (Br-PADAP) for complex formation, ethylene glycol dimethacrylate (EGDMA) as a crosslinking reagent, methacrylic acid (AMA) as functional monomer, and 2,2′-azobisisobutyronitrile as a radical initiator. The IIP was characterized by Fourier transform infrared spectroscopy and scanning electron microscopy (FTIR). Uranium determination was performed using digital imaging (ID), and some experimental conditions (sample pH, eluent concentration, and sampling flow rate) were optimized using a two-level full factorial design and Doelhert response surface methodology. Thus, using the optimized conditions, the system allowed the determination of uranium with detection and quantification limits of 2.55 and 8.51 µg L−1, respectively, and a pre-concentration factor of 8.2. All parameters were determined using a 25 mL sample volume. The precision expressed as relative deviation (RSD%) was 3.5% for a solution with a concentration of 50 µg L−1. Given this, the proposed method was used for the determination of uranium in four samples of natural waters collected in the city of Caetité, Bahia, Brazil. The concentrations obtained ranged from 35 to 75.4 μg L−1. The accuracy was evaluated by the addition/recovery test, and the values found ranged between 91 and 109%.

This paper brings forth preliminary results of recent re-examination of the cave shrine at Jebel Qeili, the site best known for the rock carving shoving Meroitic Prince Shorakaror. The painted depictions in the cave shrine were examined, described, and published by H. A. MacMichael and other scholars in the 20th century. Their descriptions and reproductions are summarised and commented upon. Then they are confronted with the results of recent documentation. Using the modern digital imaging it was possible to improve the previous observations and partly re-evaluate the painted depiction of the god Amun. [ABSTRACT FROM AUTHOR]

So far, tofu waste application as an electrocatalyst support requires carbonization. This study aims to evaluate porous tofu waste performance as an organic catalyst support without carbonization. The pre-treated tofu waste suspension by acidification using organic oxalic acid was electrolyzed in water solution. Elemental, phase, and morphology characterizations were also performed on tofu waste, supported by digital imaging of tofu waste revealing mesopores and macropores on its structure. The pore area size ranging from 43 to 935 nm2 has been activated by turmeric, thereby increasing the adsorption rate around tofu waste. Methoxyphenyl as an electron donor phenolic compound of turmeric behaves as an ORR agent. Bicnat addition, alkalizing liquid parts of tofu waste suspension, helps to loosen the bonds in water molecules. Pore activation by turmeric and bicnat carbonation synergetically destabilizes water molecule to increase hydrogen production 3-fold. This result is very favorable for converting waste into an alternative energy source. [ABSTRACT FROM AUTHOR]

Background: Otitis media includes several common inflammatory conditions of the middle ear that can have severe complications if left untreated. Correctly identifying otitis media can be difficult and a screening system supported by machine learning would be valuable for this prevalent disease. This study investigated the performance of a convolutional neural network in screening for otitis media using digital otoscopic images labelled by an expert panel. Methods: Five experienced otologists diagnosed 347 tympanic membrane images captured with a digital otoscope. Images with a majority expert diagnosis (n = 273) were categorized into three screening groups Normal, Pathological and Wax, and the same images were used for training and testing of the convolutional neural network. Expert panel diagnoses were compared to the convolutional neural network classification. Different approaches to the convolutional neural network were tested to identify the best performing model. Results: Overall accuracy of the convolutional neural network was above 0.9 in all except one approach. Sensitivity to finding ears with wax or pathology was above 93% in all cases and specificity was 100%. Adding more images to train the convolutional neural network had no positive impact on the results. Modifications such as normalization of datasets and image augmentation enhanced the performance in some instances. Conclusions: A machine learning approach could be used on digital otoscopic images to accurately screen for otitis media. [ABSTRACT FROM AUTHOR]

Introduction: Atherosclerosis of the external division of the carotid artery contributes to approximately 20% among all the reasons leading to stroke. The strategies for the prevention of stroke remain underutilized despite the advancements in healthcare. Dentists can contribute in the prevention of stroke by identifying patients at risk from the details revealed in radiographic imaging. Aim: The aim of this study is to determine the prevalence of carotid artery calcifications (CACs) detected on digital panoramic radiographs in Riyadh and its relationship with cardiovascular disorders. Methodology: A retrospective cross-sectional study was conducted in Riyadh Elm University using digital panoramic radiographs. A total of 158 panoramic radiographs were analyzed with patients aged ≥18 years. The presence of CAC was determined and confirmed by an oral radiologist. Medical records were retrieved and collected from the digital data base after ethical approval. Chi-square test of independence was performed to examine the relationship between variables (age, gender, and medical problems) and the presence of calcification. Results and Discussion: From the data scrutinized, 158 panoramic radiographs were included for the study. 111 radiographs did not have any calcifications. 47 radiographs depicted the presence of soft tissue calcification, out of which 20 radiographs were of CAC and the remaining contributed to other soft tissue calcifications seen in the neck region. There was significant correlation between age and calcification, P = 0.003 with the highest prevalence in 40–69 years. Correlation between gender, CAC, and medically compromised conditions associated with cardiovascular systems was not significant. Conclusion: The prevalence of CAC in the Riyadh population was 1.12%. CAC comprised of 12.66% among all the soft tissue calcifications of the neck in this study. Patients are not aware of the underlying cardiovascular risk that CAC can pose. Dentists' diagnostic efficiency in analyzing CAC, which is a risk factor for cardiovascular events, can reduce further morbidities or mortality rates enhancing the quality of life and life span.

Aim: This study assessed the validity and reliability of color selection by smartphone photography using two smartphone applications and Adobe Photoshop software. Settings and Design: In vitro comparative study. Materials and Methods: The validity and reliability of dental tooth shade recognition (DTSR), Chromatcher, and Adobe Photoshop were evaluated for color selection of shade tabs. The iPhone 7 camera in automatic mode was used for photography. Images were captured using Smile Lite with/without polarized filter and with camera flash. To assess the reliability, nine Vita Lumin Vacuum shade tabs were chosen and each was photographed for 10 times using Smile Lite. The reliability of DTSR, Chromatcher, and Photoshop in shade-taking was calculated. To assess their validity, 16 shade tabs of Vita Lumin Vacuum and 26 shade tabs of Vita 3D Master were photographed using the aforementioned lighting conditions. The color of photographs was calibrated and shade-taking was performed and compared with the shade suggested by SpectroShade as reference. Statistical Analysis Used: Data were analyzed using Two-way analysis of variance and Bonferroni post hoc test. Results: The reliability of Photoshop, DTSR, and Chromatcher was 98.88%, 63.3%, and 100%, respectively. The validity of Photoshop was significantly higher than other software programs (P < 0.05). Chromatcher had higher validity than DTSR (P < 0.05). Conclusion: Shade-taking by calibrated smartphone pictures and Adobe Photoshop has high validity and reliability.

Improving drought endurance in wheat needs high-throughput screening of yield components including seed volume, area, and weight, all of which are very effortful, time-consuming, and visually mostly infeasible. Imaging-based screening presents an opportunity for more exact/rapid analysis of seed morphometric traits. Therefore, this study was aimed at evaluating the phenotypic diversity of wheat seeds under rain-fed and well-watered conditions by using image analysis. From our observations, the criteria Feret (largest axis length) and MaxR (radius of the enclosing circle centered at the middle of mass) exhibited that grain length is less affected by drought. In the rain-fed environment, seed weight had the highest correlation with seed volume (r = 0.76**) and area (r = 0.76**). The correlation of 1000-grain weight with aspect ratio (r = -0.22**) and Rroundness (r = -0.21**) was negative and also non-significant (P > 0.05). The PCA and cluster analysis highlights the MinR (radius of the inscribed circle centered at the middle of mass), Area, Circ (Circularity), ArEquivD (area equivalent diameter), thickness, and seed volume characteristics can be used as useful parameters to identify genotypes suitable for planting in a rain-fed environment. The relative importance of traits for 1000-grain weight in the neural network displayed that the greatest impact in the rain-fed environment was related to seed volume, area, and MBCRadius (radius of the minimal bounding circle). Overall, our findings permitted the formation of a morphometric seed database for the conservation and characterisation of wheat germplasm. [ABSTRACT FROM AUTHOR]

To compare digital and manual mathematical methods in determining the volume of the maxillary sinus when utilizing CBCT scans, as well as to determine any differences in maxillary sinus volume regarding gender, patient’s edentulous status and age. A retrospective CBCT study of 247 patients was conducted (336 maxillary sinuses) to measure the maxillary sinus volume (MSV) and the supero-inferior and bucco-palatal dimensions of 639 residual ridges and the inferior cortical thickness of the maxillary sinus, at the Imam Abdulrahman bin Faisal University Dental Hospital, Dammam, Saudi Arabia. The MSV was done digitally by using OsiriX MD imaging software version (10.0), and mathematically by means of the pyramid equation: (Superoinferior x Anteroposterior x Mediolateral /3). Comparative and descriptive statistical analyses were performed using SPSS statistics version 22. The association between exposure and outcome was assessed using the student’s t-test. Examiners’ reliability and reproducibility were assessed by Cronbach’s alpha, Intraclass correlation and Cohen’s kappa tests. P-value of <0.05 was considered to be statistically significant. There was a significant difference in the MSV between sinuses measured digitally (OsiriX MD software) and mathematically (13.87 cm3 and 9.51 cm3 respectively). Most sub-sinus residual ridge sites (79.6%) had a height of ≥5 mm. Digital measurements of sinus volume are significantly more reliable than mathematical measurements. There were no significant differences in MSV regarding gender, patient’s edentulous status and age. [ABSTRACT FROM AUTHOR]

Introduction: The use of thermography in the medical field has been experiencing a renaissance due to advances in the infrared thermographic imaging technology, which improves thermographic equipment and promises cost saving and increased safety. Dermatology is one of the most promising fields of application among the medical areas with potential for the use of thermography. Objective: To review the findings on this subject and to describe the use of such technique for dermatology and aesthetic applications. Methods: A bibliographic survey was carried out, selecting relevant publications and guidelines, focused on monitoring medical diagnostic applications and benefits of thermography for dermatology, inflammatory skin diseases, and aesthetic applications. Results: Inflammatory skin diseases lead to changes of the IRT image. A quantification of treatment effects and monitoring changes on skin can be possible by repeated measurements over time. Conclusion: Infrared imaging is a noninvasive, powerful tool in the diagnosis and clinical management of skin conditions and monitoring of aesthetic procedures. [ABSTRACT FROM AUTHOR]

Segregation is one of the quality standards that must be monitored during the fabrication and placement of Portland cement concrete. Segregation refers to separation of coarse aggregate from the cement paste, resulting in inhomogeneous mixture. This study introduces a digital imaging based technique to quantify the segregation of Portland cement concrete from 2D digital images of cut sections. In the previous studies, segregation was evaluated based on the existence of coarse aggregate fraction at different geometrical regions of a sample cross section without considering its distribution characteristics. However, it is shown that almost all particle fractions can form clusters and increase the degree of segregation, thus deteriorating the structural performance of concrete. In the proposed methodology, a segregation index is developed by based on the spatial distribution of different size fractions of coarse aggregate within a sample cross section. It is shown that degradation in mixture’s homogeneity is controlled by the combined effect of particle distribution and their relative proportions in the mixture. Hence, a segregation index characterizing the mixture inhomogeneity is developed by considering not only spatial distribution of aggregate particles, but also their size fractions in the mixture. The proposed methodology can be successfully used as a quality control tool for monitoring the segregation level in hardened concrete samples.

The three-dimensional (3-D) micro-scale surface imaging system based on the digital fringe projection technique for the assessments of microfiber and metric screw is presented in this paper. The proposed system comprises a digital light processing (DLP) projector, a set of optical lenses, a microscope, and a charge coupled device (CCD). The digital seven-step fringe patterns from the DLP projector pass through a set of optical lenses before being focused on the target surface. A set of optical lenses is designed for adjustment and size coupling of fringe patterns. A high-resolution CCD camera is employed to picture these distorted fringe patterns. The wrapped phase map is calculated by seven-step phase-shifting calculation from these distorted fringe patterns. The unwrapping calculation with quality guided path is introduced to compute the absolute phase values. The dimensional calibration methods are used to acquire the transformation between real 3-D shape and the absolute phase value. The capability of complex surface measurement for our system is demonstrated by using ISO standard screw M1.6. The experimental results for microfiber with 3 μm diameter indicate that the spatial and vertical resolutions can reach about 3 μm in our system. The proposed system provides a fast digital imaging system to examine the surface features with high-resolution for automatic optical inspection industry.

The overall objective of this research is to check the abilities of two non-destructive techniques, the digital imaging (DI) and laser light backscattering imaging (LLBI), on detection of α-solanine toxicant in potatoes. Potato samples were classified in healthy and toxic categories based on the amount of α-solanine. For quantifying α-solanine in potato tubers, high-performance liquid chromatography (HPLC) has been used. The results of classification showed that single layer perceptron neural networks can classify potatoes with the accuracies of 94.28% and 98.66% by DI and LLBI systems (Donald cultivar), respectively. It can be said that LLBI systems might take precedent over DI systems due to their high accuracy, rapidity, and industrial capability.

The fringe projection profilometry with sinusoidal patterns based on phase-shifting algorithms is commonly distorted by the nonlinear intensity response of commercial projector. In order to solve this issue, sinusoidal width modulation is presented to generate binary sinusoidal patterns for defocusing the projection. However, the residual errors in the phase maps are usually notable for highly accurate three-dimensional shape measurements. In this paper, we propose the fringe patterns of the sinusoidal, square, and triangular periodic waveforms with seven-step phase-shifting algorithm to further improve the accuracy of three-dimensional profile reconstruction. The absolute phase values are calculated by using quality guided path unwrapping. We learn that by properly selecting fringe patterns according to the target shape, the undesired harmonics of the measured surface have negligible effect on the phase values. The experiments are presented to verify the imaging performances of three fringe patterns for different testing targets. The triangular fringe patterns are suitable for the shape measurements of complex targets with curved surfaces. The results provide a great possibility for high-accuracy shape measurement technique with wider measuring depth range.

The evolution in microsurgery using high-definition three-dimensional (3D) cameras has provided the opportunity to replace conventional operating microscopes (OM), improving ergonomics for microsurgeons. Several 3D exoscope systems have already demonstrated good surgical field visualization in a 3D space in performing microvascular anastomosis with favorable maneuverability and non-inferiority compared to OM. We present the application of the 4K-3D ORBEYE system (Olympus Inc., Tokyo, Japan) in performing lymphaticovenular anastomosis to treat lower limb lymphedema and the challenges and tips to manage small vessels measuring <0.8 mm. This system provided a good intraoperative outcome with greater ergonomics and a non-inferiority magnification compared to traditional microscopes. Our findings need further studies to confirm the feasibility; however, the 4K-3D ORBEYE represents a valid possibility to assist microsurgeons in lymphatic surgery., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Caretto et al.)

A leukocyte differential of peripheral blood can be performed using digital imaging coupled with cellular pre-classification by artificial neural networks. Platelet and erythrocyte morphology can be assessed and counts estimated. Systems from a single vendor have been used in clinical practice for several years, with other vendors' systems, in a development. These systems perform comparably to traditional manual optical microscopy, however, it is important to note that they are designed and intended to be operated by a trained morphologist. These systems have several benefits including increased standardization, efficiency, and remote-review capability., Competing Interests: Disclosure The author has been a paid speaker for Sysmex, however, this was on a subject which is not related to this article. Dr K.A. Bowers has not disclosures., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Introduction: Artificial intelligence (AI) is an emerging modern technology within the health care sectors in the current era and it is the ability of computer software to mimic human judgment. Artificial intelligence (AI)-based modern image analysis methods have significant promise for enhancing the accuracy and efficacy of pathology diagnostic processes as well as for the discovery of new biomarkers. Objectives: In this article, we will discuss Artificial Intelligence, its usage in pathology in various ways such as for screening of various diseases, detection of prognostic markers or biomarkers, and various treatment modalities. Materials and Methods: Data were collected and analyzed from the recently published literature and electronic database searches of Cochrane and included the articles the year 2017 to 2021 by reading the title and the abstract. Artificial intelligence (AI), has a lot of potential for aiding in diagnosis with the advancement of information technology. For this purpose, few machine learning algorithms have been created to date. Given their capacity to evaluate complicated data in a quantitative and standardised manner to further improve the precision and scope of diagnoses, artificial intelligence (AI) or machine learning technologies hold great promise for the field of pathology. Conclusion: The application of Artificial Intelligence tools in pathology has sharply increased in this era and it is anticipated to revolutionize the pathology field in the years ahead and can change the way the field of pathology is managed and make them not only more systematic but also effective in meeting the needs of the current age of precision medicine. [ABSTRACT FROM AUTHOR]

Although pathologists have their own viewing habits while diagnosing, viewing behaviors leading to the most accurate diagnoses are under-investigated. Digital whole slide imaging has enabled investigators to analyze pathologists’ visual interpretation of histopathological features using mouse and viewport tracking techniques. In this study, we provide definitions for basic viewing behavior variables and investigate the association of pathologists' characteristics and viewing behaviors, and how they relate to diagnostic accuracy when interpreting whole slide images. We use recordings of 32 pathologists’ actions while interpreting a set of 36 digital whole slide skin biopsy images (5 sets of 36 cases; 180 cases total). These viewport tracking data include the coordinates of a viewport scene on pathologists’ screens, the magnification level at which that viewport was viewed, as well as a timestamp. We define a set of variables to quantify pathologists' viewing behaviors such as zooming, panning, and interacting with a consensus reference panel’s selected region of interest (ROI). We examine the association of these viewing behaviors with pathologists’ demographics, clinical characteristics, and diagnostic accuracy using cross-classified multilevel models. Viewing behaviors differ based on clinical experience of the pathologists. Pathologists with a higher caseload of melanocytic skin biopsy cases and pathologists with board certification and/or fellowship training in dermatopathology have lower average zoom and lower variance of zoom levels. Viewing behaviors associated with higher diagnostic accuracy include higher average and variance of zoom levels, a lower magnification percentage (a measure of consecutive zooming behavior), higher total interpretation time, and higher amount of time spent viewing ROIs. Scanning behavior, which refers to panning with a fixed zoom level, has marginally significant positive association with accuracy. Pathologists’ training, clinical experience, and their exposure to a range of cases are associated with their viewing behaviors, which may contribute to their diagnostic accuracy. Research in computational pathology integrating digital imaging and clinical informatics opens up new avenues for leveraging viewing behaviors in medical education and training, potentially improving patient care and the effectiveness of clinical workflow.

Background: the taste sensation contributes to evaluate the quality of nutrients, distinguishing between safe and hazardous foods, determining food preferences and food intake. Nowadays taste disorders among geriatric age group is a common health problem which may results in undernutrition and impaired the quality of life. Measurement of papillae number or density, therefore, can provide information about taste function of population. Objectives: to estimate taste scores for basic tastes (sweet, sour, salt, bitter and density of fungiform papilla by digital tongue image analysis among geriatric patients. To correlate the density of fungiform papillae with taste scores of basic tastes. Material and Method: 60 elderly individuals of either sex were included for the study, subjective assessment was done for taste perception and later a blue dye which was Food drug administration approved was used to identify the fungiform papillae. The images were taken using a 48-megapixel camera and analyzed on Adobe Photoshop for clarity of images. Results: mean and standard deviation of total score was 11.22±1.9 and mean standard deviation of fungiform papillae density was 13.3±2.01. The density of fungiform papillae was correlated with taste scores of basic tastes and strong positive correlation (r= 0.79) was seen, which was also statistically significant (p<0.001) Conclusion: identification of fungiform papillae and assessing density proved to be a noninvasive tool and this result can be adapted in a positive way by dieticians and medical practitioners for improving the food intake of the elderly and improving their health status for a better tomorrow. [ABSTRACT FROM AUTHOR]

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Mathematical models for describing the shape of eggs find application in various fields of practice. The article proposes a method and tools for a detailed study of the shape and peripheral contours of digital images of eggs that are suitable for grouping and sorting. A scheme has been adapted to determine the morphological characteristics of eggs, on the basis of which an algorithm has been created for obtaining their 3D models, based on data from color digital images. The deviation from the dimensions of the major and minor axes measured with a caliper and the proposed algorithm is 0.5–1.5 mm. A model of a correction factor has been established by which the three-dimensional shape of eggs can be determined with sufficient accuracy. The results obtained in this work improve the assumption that the use of algorithms to determine the shape of eggs strongly depends on those of the bird species studied. It is approved with data for Mallard eggs which have a more elliptical shape and correspondingly lower values of correction coefficient 'c' (c = 1.55–4.96). In sparrow (c = 9.55–11.19) and quail (c = 11.71–13.11) eggs, the form tends to be ovoid. After testing the obtained model for eggs from three bird species, sparrow, mallard, and quail, the coefficient of the determination of proposed model was R2 = 0.96. The standard error was SE = 0.08. All of the results show a p-value of the model less than α = 0.05. The proposed algorithm was applied to create 3D egg shapes that were not used in the previous calculations. The resulting error was up to 9%. This shows that in the test, the algorithm had an accuracy of 91%. An advantage of the algorithm proposed here is that the human operator does not need to select points in the image, as is the case with some of the algorithms developed by other authors. The proposed methods and tools for three-dimensional transformation of egg images would be applicable not only for the needs of poultry farming, but also in ornithological research when working with different shaped varieties of eggs. Experimental results show that the proposed algorithm has sufficient accuracy. [ABSTRACT FROM AUTHOR]

The mathematical theory of CT was proposed by J. Radon in 1917. It was declared that the projection of whole data sets was needed to reconstruct CT images. Therefore, according to J. Radon's original theory, local cone beam CT (local CBCT) was impossible to achieve. In this paper, I discuss how local CBCT was discovered and developed. Its development required many technical elements, such as a turntable and X-ray television system, for basic experiments such as those on which narrow collimation theory and multifunctional panoramic tomography were based. These experiments endured many failures during development. Now, local CBCT is extremely popular in dental practice because local CBCT has a low radiation dose and high resolution. This paper introduces the technical elements and outlines the important stages during the development of local CBCT in the 1990s. [ABSTRACT FROM AUTHOR]

Background: Rural clinics still have X-ray facilities that produce physical films, which are sent to the nearest hospital for evaluation. Purchasing digitalization facilities is costly, thus, sending digitized films to the radiologist may be a solution. This can be achieved via digital photo capture. However, there can be different output resolutions that may not be optimized for online diagnosis. This paper investigates if digitized X-ray films can be enhanced using image processing techniques of Contrast-Limited Adaptive Histogram Equalization (CLAHE), Normalized-CLAHE (N-CLAHE) and Min-Max Normalized-CLAHE (MMCLAHE). Methods: We collected and digitized 21 X-ray films with low, medium, and high resolutions and implemented the CLAHE, N-CLAHE and MMCLAHE image enhancement. These methods introduced a limit to clip the histogram of image intensities so as to reduce any noise amplification before file compression with the Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT). Quantitative metrics of the Peak Signal-to-Noise Ratio (PSNR) and Mean-Squared Error (MSE) were used to compare the accuracies between digitized and processed X-ray films. A qualitative evaluation was performed by a medical practitioner to validate the accuracy of enhanced digitized X-ray. Results: It had been found that both CLAHE and MMCLAHE provided good average PSNR values of 31dB - 32dB and produced low MSE values compared to N-CLAHE. The results of qualitative evaluation attained 89.9% correct diagnosis on nine randomly selected images. Generally, the evaluation indicated that the results fulfill the acceptable criteria for further evaluation and there seemed to be no pathological differences observed. Conclusion: This paper presented a proof of concept on an implementation of the CLAHE technique and its variations on digitized X-ray films. This paper had shown potential improvements with the proposed enhancement methods that may contribute to an increase efficiency in healthcare processes at rural clinics.

Chicken meat is the most widely consumed commodity by the public because it contains high protein and low fat. The freshness of food needs to be considered by producers and consumers. Therefore, many people have difficulty determining the freshness of chicken meat. Freshness assessment using conventional methods is usually based on chemical, physical, and microbiological parameters analysis. Some disadvantages of freshness assessment using traditional methods are time-consuming, expensive, and destructive. In recent decades, the development and implementation of meat quality analysis methods have increased. This paper aims to examine various methods of non-destructive detection of chicken meat freshness which have several advantages, including requiring quick time analysis, less sample preparation, low cost, and non-destructive measurements. In this paper, we explain various principles and technological applications used in assessing the freshness of chicken meat, including smart packaging, digital imaging, electronic nose and gas sensors, and spectroscopy. Ultimately, developing chicken meat freshness evaluation technology will help all customers and stakeholders monitor the product more effectively and efficiently.