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157
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ShareScore release 0.9.0
Dataset results
157 results for “diagnostic imaging”
ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset
<p>ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 2 consist of two folders with 300 images in each of them as well as annotations. </p> <p>ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 1 consists of two datasets of XCA images for each of two tasks of ARCADE challenge. The first task includes in total 1200 coronary vessel tree images, which are divided into train(1000) and validation(200) groups, images for training are followed with annotations, depicting the division of a heart into 26 different regions based on the Syntax Score methodology[1]. Similarly, the second task includes a different set of 1200 images with same train-val division proportion with annotated regions containing atherosclerotic plaques. This dataset, carefully annotated by medical experts, enables scientists to actively contribute towards the advancement of an automated risk assessment system for patients with CAD. </p> <p>The dataset structure is as follows: top-level directories "syntax" and "stenosis" contain files for the two dataset objectives, namely: i) vessel branch classification according to the SYNTAX methodology; and ii) stenosis detection. Inside both directories, there are 3 subsets of the dataset, such as "train", "val", and "test". Inside each of those folders, there are 2 lower-level directories - "images", and "annotations". Inside the "images" folder there are images in ".png" format, extracted from DICOM recordings. The "annotations" folders contain single ".JSON" files, which are named in correspondence to the objective, i.e. "train.JSON", "val.JSON", and "test.JSON".</p> <p>The structure of ".JSON" contains three top-level fields: "images", "categories", and "annotations". The "images" field contains the unique "id" of the image in the dataset, its "width" and "height" in pixels, and the "file_name" sub-field, which contains specific information about the image. The "categories" field contains a unique "id" from 1 to 26, and a "name", relating it to the SYNTAX descriptions. The "annotations" field contains a unique "id" of the annotation, "image_id" value, relating it to the specific image from the "images" field, and a "category_id" relating it to the specific category from the "categories" field. The "segmentation" sub-field contains coordinates of mask edge points in "XYXY" format. Bounding box coordinates are given in the "bbox" field in the "XYWH" format, where the first 2 values represent the x and y coordinates of the left-most and top-most points in the segmentation mask. The height and width of the bounding box are determined by the difference between the right-most and bottom-most points and the first two values. Finally, the "area" field provides the total area of the bounding box, calculated as the area of a rectangle.</p> <p> </p> <p>The corresponding Dataset Article will be provided later. </p> <p>[1] Syntax score segment definitions. https://syntaxscore.org/index.php/tutorial/definitions/14-appendix-i-segment-definitions</p>
Diagnostic electron microscopy of viruses with low-voltage electron microscopes. Raw image files with brief description.
<p>The zipped data container contains the raw (unprocessed) images that we have used for the preparation of our manuscript entiteled:</p> <p>"Diagnostic electron microscopy of viruses with low-voltage electron microscopes" <a href="https://doi.org/10.1369%2F0022155420929438">https://doi.org/10.1369/0022155420929438</a></p> <p>Lars Möller, Gudrun Holland, Michael Laue</p> <p>Advanced Light and Electron Microscopy (ZBS 4), Centre for Biological Threats and Special Pathogens, Robert Koch Institute, D-13353 Berlin, Germany</p> <p>The brief description of the data set comprises the abstract of the manuscript, the figures (including captions) and a description of the materials and methods used for their generation.</p>
Quantum Cascade Laser Spectral Histopathology: Breast Cancer Diagnostics Using High Throughput Chemical Imaging
<p>Fourier transform infrared (FT-IR) microscopy, coupled with machine learning approaches, has been demonstrated to be a powerful technique for identifying abnormalities in human tissue. The ability to objectively identify the prediseased state, and diagnose cancer with high levels of accuracy, has the potential to revolutionise current histopathological practice. Despite recent technological advances in FT-IR microscopy, sample throughput and speed of acquisition are key barriers to clinical translation. Wide-field quantum cascade laser (QCL) infrared imaging systems with large focal plane array detectors utilising discrete frequency imaging, have demonstrated that large tissue microarrays (TMA) can be imaged in a matter of minutes. However this ground breaking technology is still in its infancy and its applicability for routine disease diagnosis is, as yet, unproven. In light of this we report on a large study utilising a breast cancer TMA comprised of 207 different patients. We show that by using QCL imaging with continuous spectra acquired between 912 and 1800 cm<sup>-1</sup>, we can accurately differentiate between 4 different histological classes. We demonstrate that we can discriminate between malignant and non-malignant stroma spectra with high sensitivity (93.56%) and specificity (85.64%) for an independent test set. Finally, we classify each core in the TMA and achieve high diagnostic accuracy on a patient basis with 100% sensitivity and 86.67% specificity. The absence of false negatives reported here opens up the possibility of utilising high throughput chemical imaging for cancer screening, thereby reducing pathologist workload and improving patient care.</p>
Diagnostic and prediction value of synthetic magnetic resonance imaging in acute ischemic stroke patients
<p>This is the supplementary tables for the above paper, mainly including original statistical analysis data.</p>
Imaging Study to Investigate the Safety and Diagnostic Performance of rhPSMA 7.3 (18F) in Newly Diagnosed Prostate Cancer.
ClinicalTrials.gov study NCT04186819. IPD Sharing: NO. Countries: 4. Publications: 1.
Imaging Study to Investigate Safety and Diagnostic Performance of 18F rhPSMA 7.3 PET Ligand in Suspected Prostate Cancer Recurrence
ClinicalTrials.gov study NCT04186845. IPD Sharing: Not stated. Countries: 3. Publications: 0.
Evaluation of Diagnostic Value of 3-T Magnetic Resonance Imaging (MRI) in Suspected Prostate Cancer
ClinicalTrials.gov study NCT01357512. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Diagnostic Accuracy of Adrenal Imaging for Subtype Diagnosis in Primary Aldosteronism: Systematic Review and Meta-Analysis
<p>Objectives: Accurate subtype classification in primary aldosteronism (PA) is critical in assessing the optimal treatment options. This study aimed to evaluate the diagnostic accuracy of adrenal imaging for unilateral PA classification.</p> <p>Methods: Systematic searches of PubMed, EMBASE, and the Cochrane databases were performed from January 1, 2000, to February 1, 2020, for all studies that used computed tomography (CT) or magnetic resonance imaging (MRI) in determining unilateral PA and validated the results against invasive adrenal vein sampling (AVS). Summary diagnostic accuracies were assessed using a bivariate random-effects model. Subgroup analyses, meta-regression and sensitivity analysis were performed to explore the possible sources of heterogeneity.</p> <p>Result: A total of 25 studies, involving a total of 4669 subjects, were identified. The overall analysis revealed a pooled sensitivity of 68% (95% confidence interval [CI]: 61 to 74) and specificity of 57% (95% CI: 50 to 65) for CT/MRI in identifying unilateral PA. Sensitivity was higher in the contrast-enhanced (CT) group versus the traditional CT group [77% (95% CI: 66 to 85) vs. 58% (95% CI: 50 to 66)]. Subgroup analysis stratified by screening test for PA showed that the sensitivity of the aldosterone-to-renin ratio (ARR) group was higher than that of the non-ARR group [78% (95% CI: 69 to 84) vs. 66% (95% CI: 58 to 72)]. The diagnostic accuracy of PA patients aged ≤40 years was reported in 4 studies, and the overall sensitivity was 71%, with 79% specificity. Meta-regression revealed a significant impact of sample size on sensitivity and of age and study quality on specificity.</p> <p>Conclusion: CT/MRI is not a reliable alternative to invasive AVS without excellent sensitivity or specificity for correctly identifying unilateral PA. Even in young patients (≤40 years), 21% of patients would have undergone unnecessary adrenalectomy based on imaging results alone.</p>
FIGURES 1–4. Piezodorus. Habitus images. 1. P in Systematic relationship between Piezodorus guildinii and P. hybneri (Hemiptera Heteroptera: Pentatomidae) and diagnostic characters to separate species
FIGURES 1–4. Piezodorus. Habitus images. 1. P. guildinii (♂). 2. P. guildinii (♀). 3. P. hybneri (♂). 4. P. hybneri (♀).
Supplementary data for "Engineering PD-1-targeted small protein variants for in vitro diagnostics and in vivo PET imaging"
<p>Supplementary data for "Engineering PD-1-targeted small protein variants for in vitro diagnostics and in vivo PET imaging". The docking.zip file contains ClusPro protein/protein docking results for all binding protein variants using either murine PD-1 structure (3bikB) or human PD-1 AF2 model as receptors. The pymol session contains data and scenes used to generate the Figures in the paper.</p>
Advancing Portable Brain Imaging: The NextMRI Project's Role in Revolutionizing Diagnostic MRI
ClinicalTrials.gov study NCT07037966. IPD Sharing: NO. Countries: 1. Publications: 2.
The Diagnostic Value of Subharmonic Imaging Technology Combined With Liver Stiffness and Platelet Count for High-risk Esophageal and Gastric Varices in Patients With Liver Cirrhosis
ClinicalTrials.gov study NCT07151885. IPD Sharing: NO. Countries: 0. Publications: 8.
Contrast Ultrasound Dispersion Imaging (CUDI) as a Diagnostic Modality in the Diagnosis of Renal Cell Carcinoma
ClinicalTrials.gov study NCT04669613. IPD Sharing: NO. Countries: 1. Publications: 6.
Diagnostic Imaging of Vascular Malformations Using MSOT and ULM
ClinicalTrials.gov study NCT06994260. IPD Sharing: Not stated. Countries: 1. Publications: 6.
Effect of Diagnostic Imaging Utilization Reports
ClinicalTrials.gov study NCT02917837. IPD Sharing: Not stated. Countries: 1. Publications: 10.
Diagnostic Significance of Single Center, Open and Prospective Evaluation of <Sup>18<Sup>F-FDG PET/CT Dynamic Imaging and Genomic Sequencing in Detecting Metastatic Lesions and Differentiating Multipl
ClinicalTrials.gov study NCT03679936. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Diagnostic Value of Novel MR Imaging Techniques for the Primary Staging and Restaging of Rectal Cancer
ClinicalTrials.gov study NCT01721785. IPD Sharing: UNDECIDED. Countries: 1. Publications: 12.
Malignant Myoepithelioma of Bone and Soft Tissues: Diagnostic Imaging and Histology in Relation to Prognosis
ClinicalTrials.gov study NCT06244420. IPD Sharing: NO. Countries: 1. Publications: 2.
Diagnostic Value of Linked Color Imaging for Minimal Change Esophagitis in Nonerosive Reflux Esophagitis and GERD
ClinicalTrials.gov study NCT03068572. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
Deep Learning Magnetic Resonance Imaging Radiomics for Diagnostic Value of Hepatic Tumors in Infants
ClinicalTrials.gov study NCT05170282. IPD Sharing: NO. Countries: 1. Publications: 1.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.