Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
943
datasets available to search
ShareScore release 0.9.0
Dataset results
943 results for “pancreas”
Full summary statistics of mixQTL for GTEx v8 Pancreas
The mixQTL method is described in paper doi.org/10.1101/2020.04.22.050666. Please cite the original paper if using the data.
Pancreas cancer segmentation on portal-venous phase CTs
<p>This dataset consists of reference segmentations for 91 abdominal CTs delineating the pancreas and pancreas adenocarcinoma (PDA). The CTs were downloaded from freely available public archives for pancreas AI applications- <a href="https://wiki.cancerimagingarchive.net/display/Public/CPTAC-PDA#339482584dc5f53338634b35a3500cbed18472e0">The Cancer Imaging Archive (TCIA) CPTAC-PDA</a> (n=60) and <a href="https://drive.google.com/drive/folders/1HqEgzS8BV2c7xYNrZdEAnrHk7osJJ--2">Medical Segmentation Decathlon</a> (n=420) and evaluated by two radiologists for image quality, phase of image acquisition, presence of biliary stents and etiology of the pancreatic lesion. Volumetric pancreas and PDA segmentations was done on the portal-venous phase CTs on 3D Slicer software, by a radiologist with 4-year post residency experience. The PDA segmentations were subsequently verified by an expert abdominal radiologist with 11-years post residency experience. Segmentations were performed only on CTs that did not have expert segmentations as a part of original dataset.</p> <p>For the CPTAC-PDA dataset, segmentations were performed on 42 out of 60 CTs after excluding 18 CTs for the following reasons: presence of biliary stent (n=10), missing slices through pancreas (n=4), post-pancreatectomy status (n=1), incorrect region of scan (n=1) and unavailable portal-venous phase (n=2). </p> <p>For the MSD dataset, segmentations were performed on 49 out of 139 ‘testing’ subset CTs after excluding 90 CTs for the following reasons: presence of biliary stent (n=38), non-PDA pathology [n=36 for IPMN, n=14 for PNET) and post-treatment status (n=2). </p> <p>The uploaded files are in NIfTI format. In addition, a metadata has been uploaded containing the following information for each segmented CT: location of tumor in pancreas, T-stage, single largest diameter of tumor, presence or absence of pancreatic atrophy, dilatation of main pancreatic duct and common bile duct. </p> <p>This dataset has been referenced and elaborated in the paper-<a href="https://pubmed.ncbi.nlm.nih.gov/33840636/">https://pubmed.ncbi.nlm.nih.gov/33840636/</a>.</p>
Dataset: CODEX highly multiplexed tissue imaging in pancreas
<p><strong>Human pancreas</strong></p> <p>This dataset was acquired using CODEX, multiplexed single-cell imaging technology for spatial profiling, where all image data is in .tif format and it includes an associated imaging metadata .csv file. The combination of the targets present in this experiment define some of the main cell types and anatomical structures in human pancreas tissue.</p> <p>This dataset is a 12-highly multiplexed experiment performed on a human pancreas 5 μm section including the nuclear marker Hoechst and antibodies conjugated with oligo-sequences directed against the individual markers. Images were acquired using a Leica DMi8 widefield microscope, a digital CMOS camera (Hamamatsu, ORCA-Flash4.0 V3), and a 20x (0.75) NA dry objective. The light source was a SOLA-SM-II. All images were captured at a 16-bit depth with the following dimensions: x (0.325 μm), y (0.325 μm), and z (1.5 μm). In addition, images were processed, tiled and merged using the CODEX® Processor application (CODEX Processor 1.7.0.6).</p>
Data From: Global huntingtin knockout in adult mice leads to fatal neurodegeneration that spares the pancreas
Open the record for dataset details and reuse information.
Antibody panel used for multiplexed antibody-based imaging of Human Pancreas Analysis Program (HPAP) samples by CODEX
<p>This data file details antibodies applied to human pancreas tissue samples from the Human Pancreas Analysis Program (HPAP; RRID:SCR_016202) of the <a href="https://hirnetwork.org/">Human Islet Research Network</a> (HIRN; RRID:SCR_014393). Images will be uploaded for interactive analysis on <a href="https://pancreatlas.org/datasets">Pancreatlas</a> (RRID:SCR_018567) and made available for download via <a href="https://hpap.pmacs.upenn.edu/">PANC-DB</a>. Workflow is documented on protocols.io: <a href="https://dx.doi.org/10.17504/protocols.io.36wgq7dryvk5/v1">dx.doi.org/10.17504/protocols.io.36wgq7dryvk5/v1</a>.</p><p>Table format adapted from Radtke AJ, Quardokus EM, Saunders DC (2022), <a href="https://doi.org/10.5281/zenodo.7386417">SOP: Construction of Organ Mapping Antibody Panels for Multiplexed Antibody-Based Imaging of Human Tissues</a>. See also: Saunders D; Reihsmann R. <a href="https://doi.org/10.48539/HBM754.BHVR.258">OMAP-13: Organ Mapping Antibody Panel (OMAP) for Multiplexed Antibody-Based Imaging of Human Pancreas with CODEX, v1.0</a>.</p>
Pancreas patients dicom
<p>This dataset contains the dicom data for 6 pancreas patients. Images and annotations are included. For details, please refer to https://github.com/xuqifan897/EndtoEnd</p>
Pancreas-CT-SEG: DICOM-converted manual segmentations of pancreas for the Pancreas-CT collection
<p>This dataset contributes DICOM-converted annotations of the pancreas to the publicly available National Cancer Institute Imaging Data Commons [1] Pancreas-CT collection (<a href="https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=Community&collection_id=pancreas_ct">https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=Community&collection_id=pancreas_ct</a>). The Pancreas-CT [2] collection was initially released by The Cancer Imaging Archive (TCIA) [2,3,4]. While the images in this collection are stored in the standard DICOM format, the collection is also accompanied by 80 manual segmentations of the pancreas in the NIFTI format. Converting these NIFTI manual annotations to DICOM allows users to visualize the CT images and corresponding pancreas annotations in public DICOM-based viewers. The DICOM segmentation format includes additional metadata describing the contained segmented structure using standard SNOMED-CT terminology, and allowing users to easily map them to the reference DICOM CT images. The converted DICOM objects can be stored in any DICOM server that supports those objects (including Google Healthcare DICOM stores), and the DICOM Segmentations can be visualized using off-the-shelf tools, such as OHIF Viewer.</p> <p>To visualize and explore segmentations in this collection use this link to open it in IDC Portal: <a href="https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=Pancreas-CT-SEG" target="_blank" rel="noopener">https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=Pancreas-CT-SEG</a>.</p> <p>Conversion from NIFTI to DICOM SEG modality was performed using the dcmqi toolkit (https://github.com/QIICR/dcmqi)[4]. Resulting objects were validated using dicom3tools dciodvfy (<a href="https://www.dclunie.com/dicom3tools.html">https://www.dclunie.com/dicom3tools.html</a>). Details describing the conversion process are provided in this GitHub repository: <a href="https://github.com/ImagingDataCommons/idc-dicom-seg-conversions" target="_blank" rel="noopener">https://github.com/ImagingDataCommons/idc-dicom-seg-conversions</a>.</p>
TCIA full and low dose CT images and volumetric normal pancreas segmentations
<p>This publicly available CT dataset was downloaded from 50 portal venous phase abdominal CT scans (3mm-slice thickness) performed in 50 patients with liver metastases— from The Cancer Imaging Archive (TCIA).These CT scans were acquired with routine radiation dose levels per standard clinical protocols on SOMATOM Definition Flash CT scanner (Siemens Healthcare, Forchheim, Germany).Each study had been postprocessed to include a second reconstructed CT dataset at a simulated 25% radiation dose level. The mean (standard deviation [SD]) radiation dose for the full dose and the reduced dose CT datasets were 14.7 mSv (8 mSv) and 3.7 mSv (2 mSv), respectively. After a curation process by radiologists, 9 of 50 cases were excluded [chronic calcific pancreatitis (n = 1), postsurgical changes in pancreas (n = 2) and pancreatic lesions (n = 6)]. Volumetric pancreas segmentations were done on all the remaining 41 cases [16 males and 25 females, mean (SD) patient age: 60.8 years (14.7 yrs)] independently by the two radiologists (R1 and R2). Segmentations were first done on the full dose CT dataset and then repeated on the reduced dose CT dataset by both R1 and R2 after a gap of at least 24 hours to allow for memory extinction.</p>
M7824 (MSB0011359C) in Combination With Gemcitabine in Adults With Previously Treated Advanced Adenocarcinoma of the Pancreas
ClinicalTrials.gov study NCT03451773. IPD Sharing: NO. Countries: 1. Publications: 3.
The Aging Endocrine Pancreas: Characterization of the Entero-insular Axis Physiology in the Elderly
ClinicalTrials.gov study NCT00843479. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Summer Camp Study: Blood Glucose Control With a Bi-Hormonal Bionic Endocrine Pancreas
ClinicalTrials.gov study NCT01833988. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
A Clinical Study to Investigate if SAR425899 Binds to the Liver and Pancreas in Overweight to Obese Type 2 Diabetes Mellitus Patients
ClinicalTrials.gov study NCT03350191. IPD Sharing: YES. Countries: 1. Publications: 1.
Dose Escalation Trial of AZD1775 and Gemcitabine (+Radiation) for Unresectable Adenocarcinoma of the Pancreas
ClinicalTrials.gov study NCT02037230. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Cabozantinib and Pembrolizumab in Metastatic Pancreas
ClinicalTrials.gov study NCT05052723. IPD Sharing: NO. Countries: 1. Publications: 1.
The Bio-Inspired Artificial Pancreas for the Home
ClinicalTrials.gov study NCT03740698. IPD Sharing: NO. Countries: 1. Publications: 5.
Rapamycin Versus Mycophenolate Mofetil in Kidney-Pancreas Recipients
ClinicalTrials.gov study NCT00533442. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Safety of Artificial Pancreas Therapy in Preschoolers, Age 2-6
ClinicalTrials.gov study NCT04084171. IPD Sharing: YES. Countries: 1. Publications: 1.
Bionic Pancreas in Children With Hyperinsulinism and Post-Pancreatectomy Diabetes
ClinicalTrials.gov study NCT03303196. IPD Sharing: Not stated. Countries: 1. Publications: 6.
Vorinostat With XRT and 5-FU for Locally Advanced Adenocarcinoma of the Pancreas
ClinicalTrials.gov study NCT00948688. IPD Sharing: NO. Countries: 1. Publications: 0.
Integration of Continuous Glucose Monitoring Into a BiHormonal Closed-Loop Artificial Pancreas
ClinicalTrials.gov study NCT01161862. IPD Sharing: Not stated. Countries: 1. Publications: 2.
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.