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The purpose of this study was to implement a state-of-the-art convolutional neural network used to synthesize artificial T1-weighted (T1w) full-dose images from corresponding noncontrast and low-dose images (using various settings of input sequences) and test its performance on a patient population acquired prospectively.In this monocentric, institutional review board-approved study, a total of 138 participants were included who received an adapted imaging protocol with acquisition of a T1w low dose after administration of 10% of the standard dose and acquisition of a T1w full dose after administration of the remaining 90% of the standard dose of a gadolinium-containing contrast agent. A total of 83 participants formed the training sample (51.7 ± 16.5 years, 36 women), 25 the validation sample (55.3 ± 16.4 years, 11 women), and 30 the test sample (55.0 ± 15.0 years, 9 women). Four input settings were differentiated: only the T1w noncontrast and T1w low-dose images (standard setting), only the T1w noncontrast and T1w low-dose images with a prolonged postinjection time of 5 minutes (5-minute setting), multiple noncontrast sequences (T1w, T2w, diffusion) and the T1w low-dose images (extended setting), and only noncontrast sequences (T1w, T2w, diffusion) were used (zero-dose setting). For each setting, a deep neural network was trained to synthesize artificial T1w full-dose images, which were assessed on the test sample using an objective evaluation based on quantitative metrics and a subjective evaluation through a reader-based study. Three readers scored the overall image quality, the interchangeability in regard to the clinical conclusion compared with the true T1w full-dose sequence, the contrast enhancement of lesions, and their conformity to the respective references in the true T1w full dose.Quantitative analysis of the artificial T1w full-dose images of the standard setting provided a peak signal-to-noise ratio of 33.39 ± 0.62 (corresponding to an average improvement of the low-dose sequences of 5.2 dB) and a structural similarity index measure of 0.938 ± 0.005. In the 4-fold cross-validation, the extended setting yielded similar performance to the standard setting in terms of peak signal-to-noise ratio ( P = 0.20), but a slight improvement in structural similarity index measure ( P < 0.0001). For all settings, the reader study found comparable overall image quality between the original and artificial T1w full-dose images. The proportion of scans scored as fully or mostly interchangeable was 55%, 58%, 43%, and 3% and the average counts of false positives per case were 0.42 ± 0.83, 0.34 ± 0.71, 0.82 ± 1.15, and 2.00 ± 1.07 for the standard, 5-minute, extended, and zero-dose setting, respectively. Using a 5-point Likert scale (0 to 4, 0 being the worst), all settings of synthesized full-dose images showed significantly poorer contrast enhancement of lesions compared with the original full-dose sequence (difference of average degree of contrast enhancement-standard: -0.97 ± 0.83, P =

Modern research in the life sciences is unthinkable without computational methods for extracting, quantifying and visualising information derived from microscopy imaging data of biological samples. In the past decade, we observed a dramatic increase in available software packages for these purposes. As it is increasingly difficult to keep track of the number of available image analysis platforms, tool collections, components and emerging technologies, we provide a conservative overview of software that we use in daily routine and give insights into emerging new tools. We give guidance on which aspects to consider when choosing the platform that best suits the user's needs, including aspects such as image data type, skills of the team, infrastructure and community at the institute and availability of time and budget.

Elucidating the developmental process of an organism will require the complete cartography of cellular lineages in the spatial, temporal, and molecular domains. We present Zebrahub, a comprehensive dynamic atlas of zebrafish embryonic development that combines single-cell sequencing time course data with light-sheet microscopy-based lineage reconstructions. Zebrahub is a foundational resource to study developmental processes at both transcriptional and spatiotemporal levels. It is publicly accessible as a web-based resource, providing an open-access collection of datasets and tools. Using this resource we shed new light on the pluripotency of Neuro-Mesodermal Progenitors (NMPs). We find that NMPs are pluripotent only during early axis elongation before becoming exclusively mesodermal progenitors. We attribute this restriction in NMP cell fate to emerging morphodynamic features that compartmentalize tissue motion.

The dataset contains comprehensive image data for a total of nine mice, which underwent normal tissue brain irradiation with 90MeV protons. In particular, the image data comprise cone-bem computed tomographies (CBCT), Monte Carlo beam transport simulations based on those CTs, regular magnetic resonance imaging (MRI) follow-up (≥26 weeks), a co-aligned DSURQE mouse brain atlasand scanned whole-brain tissue sections with histochemical and immunofluorescent markers for morphology (H&E), cell nuclei (DAPI), astrocytes (GFAP), microglia (Iba1), the intermediate filament protein Nestin, proliferation (Ki67), neurons (NeuN) and oligodendrocytes (OSP). The volumetric image data (i.e. CBCT, MRI and brain atlas) were co-aligned using the ImageJ plugin Big Warp. The CBCT data was used as spatial reference to allow for mask-based, slice-wise alignment of CBCT and light microscopy image data in 3D with the scriptable registration tool Elastix. We provide the data in raw format and as aligned data sets, as well as their spatial transformations.

Vertebral Modic type 1 (MT1) degeneration may mimic infectious disease on conventional spine magnetic resonance imaging (MRI), potentially leading to additional costly and invasive investigations. This study evaluated the diagnostic performance of the proton density fat fraction (PDFF) for distinguishing MT1 degenerative endplate changes from infectious spondylitis. A total of 31 and 22 patients with equivocal diagnosis of MT1 degeneration and infectious spondylitis, respectively, were retrospectively enrolled in this IRB-approved retrospective study and examined with a chemical-shift encoding (CSE)-based water-fat 3D six-echo modified Dixon sequence in addition to routine clinical spine MRI. Diagnostic reference standard was established according to histopathology or clinical and imaging follow-up. Intravertebral PDFF [%] and PDFFratio (i.e., vertebral endplate PDFF/normal vertebrae PDFF) were calculated voxel-wise within the single most prominent edematous bone marrow lesion per patient and examined for differences between MT1 degeneration and infectious spondylitis. Mean PDFF and PDFFratio of infectious spondylitis were significantly lower compared to MT1 degenerative changes (mean PDFF, 4.28 ± 3.12% vs. 35.29 ± 17.15% [p < 0.001]; PDFFratio, 0.09 ± 0.06 vs. 0.67 ± 0.37 [p < 0.001]). The areas under the curve (AUC) and diagnostic accuracies were 0.977 (p < 0.001) and 98.1% (cut-off at 12.9%) for PDFF and 0.971 (p < 0.001) and 98.1% (cut-off at 0.27) for PDFFratio. Our data suggest that quantitative evaluation of vertebral PDFF can provide a high diagnostic accuracy for differentiating erosive MT1 endplate changes from infectious spondylitis.

OBJECTIVES Quantitative T1 relaxometry is the benchmark in imaging potential gadolinium deposition and known to be superior to semiquantitative signal intensity ratio analyses. However, T1 relaxometry studies are rare, commonly limited to a few target structures, and reported results are inconsistent.We systematically investigated quantitative T1 relaxation times (qT1) of a variety of brain nuclei after serial application of gadobutrol. MATERIALS AND METHODS Retrospectively, qT1 measurements were performed in a patient cohort with a mean number of 11 gadobutrol applications (n = 46) and compared with a control group with no prior gadolinium-based contrast agent administration (n = 48). The following target structures were evaluated: dentate nucleus, globus pallidus, thalamus, hippocampus, putamen, caudate, amygdala, and different white matter areas. Subsequently, multivariate regression analysis with adjustment for age, presence of brain metastases and previous cerebral radiotherapy was performed. RESULTS No assessed site revealed a significant correlation between qT1 and number of gadobutrol administrations in multivariate regression analysis. However, a significant negative correlation between qT1 and age was found for the globus pallidus as well as anterior and lateral thalamus (P < 0.05 each). CONCLUSIONS No T1 relaxation time shortening due to gadobutrol injection was found in any of the assessed brain structures after serial administration of 11 doses of gadobutrol.

We here present an excerpt of a 3D+time lightsheet microscopy dataset. We acquired this developing Tribolium castaneum embryo(sample line provided by Akanksha Jain, Tomancak lab, MPI CBG Dresden, Germany) for about one week with variabletemporal resolution. To simplify post-processing, we exported individual timepoints of this dataset with a frame delay of approximal 5 minutes. The actual acquisition time and image-index are given in the metadata.csv file. For example,the image with the filename "lund_i000002_oi_000007.tif" has index 2 and original index 7, according to metadata.csv, it was acquired 780safter start of acquisition. It is the 8th (index 7) image stack that was acquired from this sample. Furthermore, some datasets such as "lund_i000398_oi_002374.tif" and "lund_i000399_oi_002374.tif" are obviously the same dataset because the microscope was acquiring just one stack every 10 minutes. Additionally, we provide the original metadata files ("C0opticsprefused*" files) written by the microscope control / image acquisitionsoftwareClearControl [1]. The script for exporting the dataset ("export_dclij.py") is also provided. It uses the beetlesafari library [2, 3]. A quick overview as animated gif ("Lund.gif") is also provided. It shows a maximum intensity projection along Z over the whole one-week timelapse. More details: Duration: 36 h Frame delay 5 min (except duplicated frames) Voxel size:0.6934 x0.6934 x3.0 microns^3 (x, y, z) [1]https://github.com/clearcontrol [2]https://github.com/haesleinhuepf/beetlesafari [3]https://doi.org/10.5281/zenodo.5863867

BACKGROUND AND AIMS: NAFLD is initiated by steatosis and can progress through fibrosis and cirrhosis to HCC. The RNA binding protein human antigen R (HuR) controls RNAs at the posttranscriptional level; hepatocyte HuR has been implicated in the regulation of diet-induced hepatic steatosis. The present study aimed to understand the role of hepatocyte HuR in NAFLD development and progression to fibrosis and HCC. APPROACH AND RESULTS: Hepatocyte-specific, HuR-deficient mice and control HuR-sufficient mice were fed either a normal diet or an NAFLD-inducing diet. Hepatic lipid accumulation, inflammation, fibrosis, and HCC development were studied by histology, flow cytometry, quantitative PCR, and RNA sequencing. The liver lipidome was characterized by lipidomics analysis, and the HuR-RNA interactions in the liver were mapped by RNA immunoprecipitation sequencing. Hepatocyte-specific, HuR-deficient mice displayed spontaneous hepatic steatosis and fibrosis predisposition compared to control HuR-sufficient mice. On an NAFLD-inducing diet, hepatocyte-specific HuR deficiency resulted in exacerbated inflammation, fibrosis, and HCC-like tumor development. A multi-omic approach, including lipidomics, transcriptomics, and RNA immunoprecipitation sequencing revealed that HuR orchestrates a protective network of hepatic-metabolic and lipid homeostasis-maintaining pathways. Consistently, HuR-deficient livers accumulated, already at steady state, a triglyceride signature resembling that of NAFLD livers. Moreover, up-regulation of secreted phosphoprotein 1 expression mediated, at least partially, fibrosis development in hepatocyte-specific HuR deficiency on an NAFLD-inducing diet, as shown by experiments using antibody blockade of osteopontin. CONCLUSIONS: HuR is a gatekeeper of liver homeostasis, preventing NAFLD-related fibrosis and HCC, suggesting that the HuR-dependent network could be exploited therapeutically., Hepatology, 75 (4), ISSN:0270-9139, ISSN:1527-3350

This chapter introduces GPU-accelerated image processing in ImageJ/Fiji. The reader is expected to have some pre-existing knowledge of ImageJ Macro programming. Core concepts such as variables, for-loops, and functions are essential. The chapter provides basic guidelines for improved performance in typical image processing workflows.

Light microscopy allows observing cellular features and objects with sub-micrometer resolution. As such, light microscopy has been playing a fundamental role in the life sciences for more than a hundred years. Fueled by the availability of mass-produced electronics and hardware, publicly shared documentation and building instructions, open-source software, wide access to rapid prototyping and 3D printing, and the enthusiasm of contributors and users involved, the concept of open microscopy has been gaining incredible momentum, bringing new sophisticated tools to an expanding user base. Here, we will first discuss the ideas behind open science and open microscopy before highlighting recent projects and developments in open microscopy. We argue that the availability of well-designed open hardware and software solutions targeting broad user groups or even non-experts, will increasingly be relevant to cope with the increasing complexity of cutting-edge imaging technologies. We will then extensively discuss the current and future challenges of open microscopy., Comment: 28 pages, 2 figures

Tooth classes are a mammalian innovation that has contributed to the evolutionary success of mammals. However, our understanding of how tooth classes have evolved and diversified remains limited. Here, we use the evolutionary radiation of noctilionoid bats, the most diverse clade of mammals in terms of diet type, as a model system to show how the tooth developmental program evolved during the adaptation to new diet types. We combined morphological, developmental, cellular, and modeling approaches, to investigate the developmental differences between two tooth classes, molars and premolars and the mechanisms driving their diversification. We demonstrate that tooth classes develop through independent developmental cascades that deviate from classical models. Then we showed that the dramatic diversification of tooth number and size is driven by the modulation of the growth rate of the jaw, explaining the rapid gain/loss of teeth during the evolution of this clade. Finally, we propose a mathematical model that recapitulates the successive appearance of tooth buds and supports the hypothesis that growth acts as a key driver of the evolution of tooth number and size by tinkering with reaction/diffusion processes. Our results demonstrate developmental independence between mammalian tooth classes and provide a mechanism to explain their rapid diversification. More broadly, these results reveal how simple modifications of one developmental mechanism by another can drive the evolution of repeated structures during adaptive radiations.

We present Labkit, a user-friendly Fiji plugin for the segmentation of microscopy image data. It offers easy to use manual and automated image segmentation routines that can be rapidly applied to single- and multi-channel images as well as to timelapse movies in 2D or 3D. Labkit is specifically designed to work efficiently on big image data and enables users of consumer laptops to conveniently work with multiple-terabyte images. This efficiency is achieved by using ImgLib2 and BigDataViewer as the foundation of our software. Furthermore, memory efficient and fast random forest based pixel classification inspired by the Waikato Environment for Knowledge Analysis (Weka) is implemented. Optionally we harness the power of graphics processing units (GPU) to gain additional runtime performance. Labkit is easy to install on virtually all laptops and workstations. Additionally, Labkit is compatible with high performance computing (HPC) clusters for distributed processing of big image data. The ability to use pixel classifiers trained in Labkit via the ImageJ macro language enables our users to integrate this functionality as a processing step in automated image processing workflows. Last but not least, Labkit comes with rich online resources such as tutorials and examples that will help users to familiarize themselves with available features and how to best use Labkit in a number of practical real-world use-cases.

Background Conventional stented valves (CV) remain gold standard for aortic valve disease. Bovine prostheses have been improved and rapid deployment valves (RDV) have arrived in the recent decade. We compare clinical and hemodynamic short-term outcome of six bovine valves. Methods We retrospectively evaluated 829 consecutive patients (all-comers) receiving bovine aortic valve replacement (AVR). Four CV from different manufacturers (Mitroflow, Crown, Perimount, Trifecta) and two RDV (Perceval, Intuity) were compared in terms of pre-, intra-, and postprocedural data. A risk model for mortality was created. Results All valves reduced gradients. From 23 mm, all CV showed acceptable gradients. Twenty-one millimeter Mitroflow/Perceval and 19 mm Crown showed above-average gradients. As baseline data differed, we performed propensity matching between aggregated isolated CV and RDV groups. Cardiopulmonary bypass (CPB), clamp, and surgery times were shorter with RDV (87.4 ± 34.0 min vs 111.0 ± 34.2, 54.3 ± 21.1 vs 74.9 ± 20.4, 155.2 ± 42.9 vs 178.0 ± 46.8, p Conclusion Isolated bovine AVR has low mortality. Valves ≥ 23 mm show comparable gradients while the valve model matters

Our objective was to evaluate the diagnostic performance of a convolutional neural network (CNN) trained on multiple MR imaging features of the lumbar spine, to detect a variety of different degenerative changes of the lumbar spine. One hundred and forty-six consecutive patients underwent routine clinical MRI of the lumbar spine including T2-weighted imaging and were retrospectively analyzed using a CNN for detection and labeling of vertebrae, disc segments, as well as presence of disc herniation, disc bulging, spinal canal stenosis, nerve root compression, and spondylolisthesis. The assessment of a radiologist served as the diagnostic reference standard. We assessed the CNN’s diagnostic accuracy and consistency using confusion matrices and McNemar’s test. In our data, 77 disc herniations (thereof 46 further classified as extrusions), 133 disc bulgings, 35 spinal canal stenoses, 59 nerve root compressions, and 20 segments with spondylolisthesis were present in a total of 888 lumbar spine segments. The CNN yielded a perfect accuracy score for intervertebral disc detection and labeling (100%), and moderate to high diagnostic accuracy for the detection of disc herniations (87%; 95% CI: 0.84, 0.89), extrusions (86%; 95% CI: 0.84, 0.89), bulgings (76%; 95% CI: 0.73, 0.78), spinal canal stenoses (98%; 95% CI: 0.97, 0.99), nerve root compressions (91%; 95% CI: 0.89, 0.92), and spondylolisthesis (87.61%; 95% CI: 85.26, 89.21), respectively. Our data suggest that automatic diagnosis of multiple different degenerative changes of the lumbar spine is feasible using a single comprehensive CNN. The CNN provides high diagnostic accuracy for intervertebral disc labeling and detection of clinically relevant degenerative changes such as spinal canal stenosis and disc extrusion of the lumbar spine.

Fast-paced innovations in imaging have resulted in single systems producing exponential amounts of data to be analyzed. Computational methods developed in computer science labs have proven to be crucial for analyzing these data in an unbiased and efficient manner, reaching a prominent role in most microscopy studies. Still, their use usually requires expertise in bioimage analysis, and their accessibility for life scientists has therefore become a bottleneck. Open-source software for bioimage analysis has developed to disseminate these computational methods to a wider audience, and to life scientists in particular. In recent years, the influence of many open-source tools has grown tremendously, helping tens of thousands of life scientists in the process. As creators of successful open-source bioimage analysis software, we here discuss the motivations that can initiate development of a new tool, the common challenges faced, and the characteristics required for achieving success.

NR+ is a highly effective vitamin B3 type supplement due to its unique ability to replenish NAD+ levels. While NR+ chloride is already on the market as a nutritional supplement, its synthesis is challenging, expensive, and low yielding, making it cumbersome for large-scale industrial production. Here we report the novel crystalline NR+ salts, d/l/dl-hydrogen tartrate and d/l/dl-hydrogen malate. Their high-yielding, one-pot manufacture does not require specific equipment and is suitable for multi-ton scale production. These new NR+ salts seem ideal for nutritional applications due to their bio-equivalence compared to the approved NR+ chloride. In addition, the crystal structures of all stereoisomers of NR+ hydrogen tartrate and NR+ hydrogen malate and a comparison to the known NR+ halogenides are presented.

Modern life science relies heavily on fluorescent microscopy and subsequent quantitative bio-image analysis. The current rise of graphics processing units (GPUs) in the context of image processing enables batch processing large amounts of image data at unprecedented speed. In order to facilitate adoption of this technology in daily practice, we present an expert system based on the GPU-accelerated image processing library CLIJ: The CLIJ-assistant keeps track of which operations formed an image and suggests subsequent operations. It enables new ways of interaction with image data and image processing operations because its underlying GPU-accelerated image data flow graphs (IDFGs) allow changes to parameters of early processing steps and instantaneous visualization of their final results. Operations, their parameters and connections in the IDFG are stored at any point in time enabling the CLIJ-assistant to offer an undo-function for virtually unlimited rewinding parameter changes. Furthermore, to improve reproducibility of image data analysis workflows and interoperability with established image analysis platforms, the CLIJ-assistant can generate code from IDFGs in programming languages such as ImageJ Macro, Java, Jython, JavaScipt, Groovy, Python and C++ for later use in ImageJ, Fiji, Icy, Matlab, QuPath, Jupyter Notebooks and Napari. We demonstrate the CLIJ-assistant for processing image data in multiple scenarios to highlight its general applicability. The CLIJ-assistant is open source and available online: https://clij.github.io/assistant/

The dauer larva of Caenorhabditis elegans, destined to survive long periods of food scarcity and harsh environment, does not feed and has a very limited exchange of matter with the exterior. It was assumed that the survival time is determined by internal energy stores. Here, we show that ethanol can provide a potentially unlimited energy source for dauers by inducing a controlled metabolic shift that allows it to be metabolized into carbohydrates, amino acids, and lipids. Dauer larvae provided with ethanol survive much longer and have greater desiccation tolerance. On the cellular level, ethanol prevents the deterioration of mitochondria caused by energy depletion. By modeling the metabolism of dauers of wild‐type and mutant strains with and without ethanol, we suggest that the mitochondrial health and survival of an organism provided with an unlimited source of carbon depends on the balance between energy production and toxic product(s) of lipid metabolism., Exogenous ethanol supports the survival of Caenorhabditis elegans dauer larvae by inducing a metabolic shift that drives its conversion into sugars, amino acids, and storage lipids, thus promoting mitochondrial integrity and stress resistance. Excessive production of lipids out of ethanol, however, appears to limit the survival due to a buildup of toxic lipids, suggesting that the balance between energy production and lipid metabolism determines the survival in the presence of an unlimited source of carbon.

Background Transcatheter heart valve (THV) as valve-in-ring is increasingly used in the mitral position. Semi-rigid rings may serve as a more appropriate scaffold for proper anchoring of a THV as they may change from their oval to a round shape thereby fitting to the implanted THV. Methods One rigid and five semi-rigid rings of four manufacturers, Edwards Physio I and II, Sorin 3D Memo, Medtronic Simulus, and St. Jude Medical (SJM) Saddle and SJM Sequin, with sizes 28 to 36 mm and Edwards Sapien III THV 23, 26, and 29 mm were used. Preevaluation comprised insertion/inflation of the THV into the ring and visual inspection for the paravalvular gap ≥ 4 mm2. Only valves not showing paravalvular gap were then submitted to hemodynamic evaluation with a pulse duplicator. Cusp movement was assessed with a high-speed-camera. Mean transvalvular gradients (TVGs) were measured. Results SJM Saddle ring of all sizes and SJM Sequin ring 34 showed marked gaps combined with all THV sizes, thus not undergoing hemodynamic testing. It was further shown that ring sizes ≥ 36 mm did not allow for a proper fit of even the largest THV into the ring of all the manufacturers and were consequently not hemodynamically evaluated. The 23 mm THV was too small for any ring size. The lowest gradients were achieved with the 26 mm THV in 30 and 32 mm and the 29 mm THV in 32 and 34 mm rings. Conclusion Not all currently available annuloplasty rings are ideal scaffolds for THV placement. It appears that a more proper fit can be achieved with semi-rigid rings than with rigid ones. Note that 23 mm THV appeared to be too small for an adequate anchoring in even the smallest available ring. Thus, 26 mm as well as 29 mm THV fit properly in ring sizes between 28 and 34 mm. Surgeons may consider to choose from those ring brands and sizes which allow for good placement of a THV in view of possible valve degeneration in the later course.

Objectives: To analyse the implementation, applicability and accuracy of the pretest probability calculation provided by NICE clinical guideline 95 for decision making about imaging in patients with chest pain of recent onset. Methods: The definitions for pretest probability calculation in the original Duke clinical score and the NICE guideline were compared. We also calculated the agreement and disagreement in pretest probability and the resulting imaging and management groups based on individual patient data from the Collaborative Meta-Analysis of Cardiac CT (CoMe-CCT). Results: 4,673 individual patient data from the CoMe-CCT Consortium were analysed. Major differences in definitions in the Duke clinical score and NICE guideline were found for the predictors age and number of risk factors. Pretest probability calculation using guideline criteria was only possible for 30.8 % (1,439/4,673) of patients despite availability of all required data due to ambiguity in guideline definitions for risk factors and age groups. Agreement regarding patient management groups was found in only 70 % (366/523) of patients in whom pretest probability calculation was possible according to both models. Conclusions: Our results suggest that pretest probability calculation for clinical decision making about cardiac imaging as implemented in the NICE clinical guideline for patients has relevant limitations. Key Points: • Duke clinical score is not implemented correctly in NICE guideline 95. • Pretest probability assessment in NICE guideline 95 is impossible for most patients. • Improved clinical decision making requires accurate pretest probability calculation. • These refinements are essential for appropriate use of cardiac CT.

OpenSPIM is an Open Access platform for Selective Plane Illumination Microscopy (SPIM) and allows hundreds of laboratories around the world to generate and process light-sheet data in a cost-effective way due to open-source hardware and software. While setting up a basic OpenSPIM configuration can be achieved expeditiously, correctly assembling and operating more complex OpenSPIM configurations can be challenging for routine standard OpenSPIM users. Detailed instructions on how to equip an OpenSPIM with two illumination sides and two detection axes (X-OpenSPIM) are provided, and a solution is also provided on how the temperature can be controlled in the sample chamber. Additionally, it is demonstrated how to operate it by implementing an ArduinoUNO microcontroller and introducing μOpenSPIM, a new software plugin for OpenSPIM, to facilitate image acquisition. The new software works on any OpenSPIM configuration comes with drift correction functionality, on-the-fly image processing, and gives users more options in the way time-lapse movies are initially set up and saved. Step-by-step guides are also provided within the Supporting Information and on the website on how to align the lasers, configure the hardware, and acquire images using μOpenSPIM. With this, current OpenSPIM users are empowered in various ways, and newcomers striving to use more advanced OpenSPIM systems are helped.

Background and purpose: Magnetic resonance imaging (MRI) plays an important role in the field of MR-guided radiotherapy or personalised radiation oncology. The application of quantitative image analyses like radiomics as well as automated tissue characterisation is frequently disturbed by the effect of intensity non-uniformity. We present a novel fully automated physical correction model (PCM) for the reduction of intensity non-uniformity. Materials and methods: The proposed algorithm is based on a 3D physically motivated correction model, which maximises the image information expressed by the Shannon entropy. The PCM was evaluated using the coefficient of variation (cv) on 176 MRI datasets of the human brain and abdomen acquired on 1.5 Tesla and 3 Tesla MR scanners. The resulting cv was compared to the cv of the original images and to the results of the established N4 algorithm. Results: The PCM algorithm significantly improved the image quality of all considered 1.5 and 3.0 Tesla MR scans compared to the original images (p