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217 results for “image contrast”
Data from: Data for evaluation of fast kurtosis imaging, b-value optimization and exploration of diffusion MRI contrast
Here we describe and provide diffusion magnetic resonance imaging (dMRI) data that was acquired in neural tissue and a physical phantom. Data acquired in biological tissue includes: fixed rat brain (acquired at 9.4T) and spinal cord (acquired at 16.4T) and in normal human brain (acquired at 3T). This data was recently used for evaluation of diffusion kurtosis imaging (DKI) contrasts and for comparison to diffusion tensor imaging (DTI) parameter contrast. The data has also been used to optimize b-values for ex vivo and in vivo fast kurtosis imaging. The remaining data was obtained in a physical phantom with three orthogonal fiber orientations (fresh asparagus stems) for exploration of the kurtosis fractional anisotropy. However, the data may have broader interest and, collectively, may form the basis for image contrast exploration and simulations based on a wide range of dMRI analysis strategies.
Data from: Quantification and optimization of ADF-STEM image contrast for beam sensitive materials
Many functional materials are difficult to analyze by Scanning Transmission Electron Microscopy (STEM) on account of their beam sensitivity and low contrast between different phases. The problem becomes even more severe when thick specimens need to be investigated, a situation that is common for materials that are ordered from the nanometer to micrometer length scales or when performing dynamic experiments in a TEM liquid cell. Here we report a method to optimize annular dark-field (ADF) STEM imaging conditions and detector geometries for thick and beam-sensitive low-contrast specimen using the example of a carbon nanotube/polymer nanocomposite. We carried-out Monte Carlo simulations as well as quantitative ADF-STEM imaging experiments to predict and verify optimum contrast conditions. The presented method is general, can be easily adapted to other beam-sensitive and/or low-contrast materials, as shown for a polymer vesicle within a TEM liquid-cell, and can act as an expert guide on whether an experiment is feasible and to determine the best imaging conditions.
Data from: Validation of perfusion quantification with 3D gradient echo dynamic contrast-enhanced magnetic resonance imaging using a blood pool contrast agent in skeletal swine muscle
The purpose of our study was to validate perfusion quantification in a low-perfused tissue by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with shared k-space sampling using a blood pool contrast agent. Perfusion measurements were performed in a total of seven female pigs. An ultrasonic Doppler probe was attached to the right femoral artery to determine total flow in the hind leg musculature. The femoral artery was catheterized for continuous local administration of adenosine to increase blood flow up to four times the baseline level. Three different stable perfusion levels were induced. The MR protocol included a 3D gradient-echo sequence with a temporal resolution of approximately 1.5 seconds. Before each dynamic sequence, static MR images were acquired with flip angles of 5°, 10°, 20°, and 30°. Both static and dynamic images were used to generate relaxation rate and baseline magnetization maps with a flip angle method. 0.1 mL/kg body weight of blood pool contrast medium was injected via a central venous catheter at a flow rate of 5 mL/s. The right hind leg was segmented in 3D into medial, cranial, lateral, and pelvic thigh muscles, lower leg, bones, skin, and fat. The arterial input function (AIF) was measured in the aorta. Perfusion of the different anatomic regions was calculated using a one- and a two-compartment model with delay- and dispersion-corrected AIFs. The F-test for model comparison was used to decide whether to use the results of the one- or two-compartment model fit. Total flow was calculated by integrating volume-weighted perfusion values over the whole measured region. The resulting values of delay, dispersion, blood volume, mean transit time, and flow were all in physiologically and physically reasonable ranges. In 107 of 160 ROIs, the blood signal was separated, using a two-compartment model, into a capillary and an arteriolar signal contribution, decided by the F-test. Overall flow in hind leg muscles, as measured by the ultrasound probe, highly correlated with total flow determined by MRI, R = 0.89 and P = 10−7. Linear regression yielded a slope of 1.2 and a y-axis intercept of 259 mL/min. The mean total volume of the investigated muscle tissue corresponds to an offset perfusion of 4.7mL/(min ⋅ 100cm3). The DCE-MRI technique presented here uses a blood pool contrast medium in combination with a two-compartment tracer kinetic model and allows absolute quantification of low-perfused non-cerebral organs such as muscles.
Change-Aware Sampling and Contrastive Learning for Satellite Images (Part 3)
<p>Part 3 of compressed CACo 1M data</p>
Change-Aware Sampling and Contrastive Learning for Satellite Images (Part 4)
<p>Part 4 of compressed CACo 1M data</p>
Change-Aware Sampling and Contrastive Learning for Satellite Images (Part 2)
<p>Part 2 of compressed CACo 1M data</p>
Change-Aware Sampling and Contrastive Learning for Satellite Images (Part 1)
<p>Part 1 of compressed CACo 1M data</p>
DAPI and Phase Contrast Images Dataset
<p>Data was acquired on an Olympus IX83 microscope using a 20x/0.4 Ph2 Objective.</p> <p>Kohler illimination was established before acquistion started.</p> <p>Sample consists of cultured HeLa Cells on #1.5 (170 um) coverslips, 12mm diameter.</p> <p> </p> <p>A single coverlsip was imaged in a 10x10 grid with no overlap (total: 100 images)</p> <p>Each image was acquired sequentially in</p> <ul> <li><strong>Phase Contrast</strong> (50ms exposure time, using a 535nm LED)</li> <li><strong>DAPI</strong> 100 ms exposure time</li> </ul>
Contrastive learning-based histopathological feature infers molecular subtypes and clinical outcomes of breast cancer from unannotated whole slide images
<p>The breast cancer cohort came from the Changzhou Second People's Hospital (CZSPH) in Jiangsu, China. This cohort collected 91 FFPE WSIs from 90 breast cancer patients, including 15 recurrence cases within 5 years.</p>
Radiomics and Artificial Intelligence Analysis by T2 weighted imaging and Dynamic Contrast Enhanced Magnetic resonance imaging to predict Breast Cancer Histological Outcome
<p>Radiomics features obtained by MR images to predict Breast Cancer Histological Outcome.</p>
Non-Contrast Perfusion Using Arterial Spin Labeled MR Imaging for Assessment of Therapy Response in Metastatic Renal Cell Carcinoma
ClinicalTrials.gov study NCT04831138. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Prospective Case Collection Study of Contrast-Enhanced Mammography Imaging Acquired on a New Investigational Device
ClinicalTrials.gov study NCT06636539. IPD Sharing: NO. Countries: 1. Publications: 0.
Study to Find the Appropriate Dose of a New Gadolinium-based Contrast Agent (GBCA) for Adults Undergoing Magnetic Resonance Imaging (MRI) for Known or Highly Suspected Brain and/or Spinal Cord Conditi
ClinicalTrials.gov study NCT04307186. IPD Sharing: NO. Countries: 4. Publications: 0.
Post-marketing Safety Study in Patients With Moderate Renal Insufficiency Who Receive Omniscan for Contrast-enhanced Magnetic Resonance Imaging (MRI)
ClinicalTrials.gov study NCT00908310. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Mixed Cohort, Multicentre Exploratory Study of Non-invasive Quantitative Assessment of Renal Graft Function With Non-contrast Functional Magnetic Resonance Imaging
ClinicalTrials.gov study NCT07333495. IPD Sharing: NO. Countries: 1. Publications: 0.
Bone Marrow Angiogenesis in Acute Myeloid Leukemia - Evaluated by Dynamic Contrast Enhanced Magnetic Resonance (MR) Image
ClinicalTrials.gov study NCT00172562. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Feasibility of Ultrasound Microbubble Contrast-Enhanced (CEUS) Sentinel Lymph Node Imaging With Guided Biopsy in Breast Cancer Patients
ClinicalTrials.gov study NCT02321527. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Contrast-Enhanced Subharmonic Ultrasound Imaging in Improving Characterization of Adnexal Masses in Patients Undergoing Surgery
ClinicalTrials.gov study NCT03297112. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Iodixanol Versus Iopamidol in Patients Undergoing Contrast-Enhanced Computed Tomographic Imaging of Abdomen/Pelvis
ClinicalTrials.gov study NCT01376089. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Use of Dynamic Contrast-Enhanced Magnetic Resonance Imaging to Assess Tumor-Associated Vasculature in Patients With Metastatic Breast Cancer
ClinicalTrials.gov study NCT00071357. IPD Sharing: Not stated. Countries: 1. Publications: 3.
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.