from several different imaging modalities (e.g. The USC-SIPI Image Database You are not authorized to redistribute or sell them, or use them for commercial purposes. (2010)). 1. Keywords: medium, MRI, segmentations, 21 Canine mammary carcinoma whole slide images. Designed and run by a community of researchers from a variety of organizations, our challenges invite participants to propose solutions — fostering collaboration and building communities in the process. Also built a Support Vector Machine Classifier in Python to classify whether a breast cancer tumor is benign or malignant based off the tumors' features. The corpus contains recordings and perceptual evaluations of speech intelligibility over three evaluation moments: before treatment and after treatment (10-weeks and 12-months). The investigators funded under this initiative created a set of guidelines and metrics for database use and for developing a database as a test-bed and showcase for those methods. Keywords: very-large, X-ray, labels, Several collections Keywords: very-large, ultrasound, labels, MRI for 8500 young (9-10yo) subjects (about 4100 for training) There are many sites sites that provide medical information but very few that provide medical pictures. If nothing happens, download the GitHub extension for Visual Studio and try again. Melbourne University AES/MathWorks/NIH Seizure Prediction - Predict seizures in long-term human intracranial EEG recordings, American Epilepsy Society Seizure Prediction Challenge - Predict seizures in intracranial EEG recordings, UPenn and Mayo Clinic's Seizure Detection Challenge - Detect seizures in intracranial EEG recordings, Grasp-and-Lift EEG Detection - Identify hand motions from EEG recordings. 10 3D FLAIR, T1-, and T2-weighted datasets of a single healthy subject Access: http://peipa.essex.ac.uk/info/mias.html. Link: http://emotion-research.net/sigs/speech-sig/is13-compare. Introduction¶ As all we know medical insurance companies are very important in some countries where the medical services are not free. The home page interface is confusing and the entire website design is not user-friendly and has a mid 1990s feel to it. Access: https://www.kaggle.com/c/intel-mobileodt-cervical-cancer-screening/data. The database contains approximately 2,500 studies. To support reproducibility in scientific research, TCIA supports Digital Object Identifiers (DOIs) which allow users to share subsets of TCIA data referenced in a research manuscript. Information: https://medpix.nlm.nih.gov/home, ABIDE: The Autism Brain Imaging Data Exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Keyworks: large, MRI, genetics, clinical, ~120 image volumes (whole body CT and MRI images) Ursem decided to conduct a search to find out if any medical data had been leaked on GitHub. carcinoma, lung cancer, myeloma) and various imaging modalities. This will also significantly improve adherence to the treatment protocol and result in a better record of the treatment outcomes. The challenge results will be presented and discussed at the upcoming Workshop On Biomedical Image Registration (WBIR 2018). Keywords: small, histology, high-resolution, segmentations, Single volume, ultra-high resolution MRI dataset (100-micron) It is maintained primarily to support research in image processing, image analysis, and machine vision. Three of these radiologists were used to create a gold standard, defined as the majority vote of the labels of the radiologists, and the other three were used to obtain the best radiologist performance, defined as the maximum score of the three radiologists with the gold standard as groundtruth. The Multi-Dimensional Human Embryo is a collaboration funded by the National Institute of Child Health and Human Development (NICHD) to produce and make available over the internet a three-dimensional image reference of the Human Embryo based on magnetic resonance imaging. It consists of 40 photographs out of which 7 showing signs of mild early diabetic retinopathy. The Medical Image Computing and Computer Assisted Intervention. If you use DLTK in your work please refer to this citation for the current version: If you use any application from the DLTK Model Zoo, additionally refer to the respective README.md files in the applications' folder to comply with its authors' instructions on referencing. 1500 fully sample knee MRIs and 10K clinical MRIs, and 6.5K brain MRIs. Data: https://archive.ics.uci.edu/ml/datasets/Thyroid+Disease, Breast Cancer Data Set Analyze medical image data using a pre-trained Azure Cognitive Services API or a custom developed Machine Learning model. Information: https://www.propublica.org/series/dollars-for-docs The challenge focuses on pairwise registration of lungs and brains, two problems frequently encountered in clinical settings. Multi-Ethnic Study of Atherosclerosis, is a large-scale cardiovascular population study (>6,500 participants) conducted in six centres in the USA. Embase: more than 38 million articles in healthcare and related fields 3. Function MRI images for 539 individuals suffering from ASD and 573 typical controls. Please note that this post is for my future-self to look back and review the basic techniques of data exploration. Several types of lesions (masses, calcifications, asymmetries, and distortions) are included. Repurpose open data to discover therapeutics for understudied diseases, National Institute of General Medical Sciences (1R01GM134307), Co-PI, PI: Bin Chen, 2019-2024. Areas of Study: Natural languge processing, medical informatics Links: Github. It uses SimpleITK to load and augment input data, and Tensorflow to define and train networks. Embed Embed this gist in your website. A victim receives an unsolicited email containing medical analysis data from a medical office. Access: http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm. ftp://bigbrain.loris.ca | interactive Medical Image Datasets. HON encourages users to make their own image links available via the Submit an image link." Fundus imaging Keywords: medium, fMRI, 229 T1-weighted MRI scans (n=220) with lesion segmentation Keywords: small, MRI, fetal, predict sepsis in an ICU population The KiTS19 challenge is on the semantic segmentation of kidneys and kidney tumors in contrast-enhanced CT scans. Recordings were made in their everyday working environment. Keywords: large, CT, covid, segmentations, Various imaging (longitudinal MRI), Genetics, Clinical data by: Sridhar Ramaswamy. Disclaimer: please remember to solve real clinical problems ☺, 224,316 chest radiographs of 65,240 patients, with labels from reports GitHub; Featured projects. Data request: https://projects.propublica.org/data-store/sets/health-d4d-national-2, DocGraph challenge 2008. "HONmedia (the image gallery) is an unique repository of over 6'800 medical images and videos, pertaining to 1,700 topics and themes. Keywords: small, MRI, brain, fMRI, (ex-vivo) brain MRIs or brains of different animals Statistically, in 2008, the number of new diagnosed cases was estimated to be 899,000 with no less than 258,100 deaths (Ferlay et al. Keywords: very-large, CT, labels, 32000+ CT scans with annotations, meta-data, semantic labels from radiological reports Keywords: large, MRI, fMRI, tests, 2600+ scanned film mammography studies Access: https://stanfordmlgroup.github.io/competitions/mura/, 2019 Kidney and Kidney Tumor Segmentation Challenge (KiTS19). I was the winner of Microsoft … Data UAB. Public Health Image Library (PHIL) Created by a Working Group at the Centers for Disease Control and Prevention (CDC), the PHIL offers an organized, universal electronic gateway to CDC's pictures. Data on 11 Million inpatient visits with diagnosis, procedure codes and outcomes from Texas between 2006 & 2009. Includes 3D animations. Medical Imaging Data. These datasets are exclusively available for research and teaching. CT scan for diagnosing of colon cancer. A dataset for inferring the results of randomized control trials (RCTs). The information was … The primary objective... MESA All gists Back to GitHub. Collection of pubmed abstracts from randomized control trials (RCTs). Access: http://www.osirix-viewer.com/resources/dicom-image-library/, SCR database: Segmentation in Chest Radiographs. Search tool: https://projects.propublica.org/docdollars/ Several thousand patients A researchers discovered at least nine GitHub repositories leaking health data from at least 150,000 patients, most commonly caused by developer errors and improper access controls. Medical insurance data analysis and predicting medical insurance charges. download the GitHub extension for Visual Studio, https://echonet.github.io/dynamic/index.html, https://echonet.github.io/dynamic/index.html#access, http://www.ncbi.nlm.nih.gov/pubmed/23774715, http://fcon_1000.projects.nitrc.org/indi/abide/, http://preprocessed-connectomes-project.org/abide/, http://www.neurology.org/content/74/3/201.short, http://adni.loni.usc.edu/data-samples/access-data/, https://wiki.cancerimagingarchive.net/display/Public/CT+COLONOGRAPHY#dc149b9170f54aa29e88f1119e25ba3e, https://ieeexplore.ieee.org/document/1282003, http://www.isi.uu.nl/Research/Databases/DRIVE/download.php, https://github.com/GalAvineri/ISIC-Archive-Downloader, https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI#, http://marathon.csee.usf.edu/Mammography/Database.html, http://medicalresearch.inescporto.pt/breastresearch/index.php/Get_INbreast_Database, http://www.ehealthlab.cs.ucy.ac.cy/index.php/facilities/32-software/218-datasets, http://www.osirix-viewer.com/resources/dicom-image-library/, http://www.isi.uu.nl/Research/Databases/SCR/, http://www.omnimedicalsearch.com/image_databases.html, http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm, http://cmp.felk.cvut.cz/~borovji3/?page=dataset, https://www.kaggle.com/c/diabetic-retinopathy-detection, https://www.kaggle.com/c/intel-mobileodt-cervical-cancer-screening/data, https://www.kaggle.com/c/melbourne-university-seizure-prediction, https://www.kaggle.com/c/seizure-prediction, https://www.kaggle.com/c/seizure-detection, https://www.kaggle.com/c/grasp-and-lift-eeg-detection, https://www.miccai2019.org/programme/workshops-challenges-tutorials/#tablepress-10, https://www.miccai2018.org/en/WORKSHOP---CHALLENGE---TUTORIAL.html, http://www.miccai2017.org/satellite-events, http://www.miccai2016.org/en/SATELLITE-EVENTS.html, https://www.miccai2015.org/frontend/index.php?page_id=589, https://biomedicalimaging.org/2019/challenges/, https://biomedicalimaging.org/2018/challenges/, http://biomedicalimaging.org/2017/challenges/, http://biomedicalimaging.org/2016/?page_id=416, https://continuousregistration.grand-challenge.org/home/, BIRL: Benchmark on Image Registration methods with Landmark validation, https://stanfordmlgroup.github.io/competitions/mura/, http://www.nature.com/articles/sdata201432, http://datadryad.org/resource/doi:10.5061/dryad.jp917, http://cs.nyu.edu/~dsontag/papers/ChoiChiuSontag_AMIA_CRI16.pdf, http://www.nature.com/articles/sdata201635, http://physionet.org/physiobank/database/mimic3cdb/, https://figshare.com/s/00d69861786cd0156d81, https://github.com/elleros/DSHealth2019_loinc_embeddings, https://www.dshs.texas.gov/thcic/hospitals/Inpatientpudf.shtm, https://www.propublica.org/series/dollars-for-docs, https://projects.propublica.org/docdollars/, https://projects.propublica.org/data-store/sets/health-d4d-national-2, http://thehealthcareblog.com/blog/2012/11/05/tracking-the-social-doctor-opening-up-physician-referral-data-and-much-more/, https://archive.ics.uci.edu/ml/datasets/Liver+Disorders, https://archive.ics.uci.edu/ml/datasets/Thyroid+Disease, https://archive.ics.uci.edu/ml/datasets/Breast+Cancer, https://archive.ics.uci.edu/ml/datasets/Heart+Disease, https://archive.ics.uci.edu/ml/datasets/Lymphography, https://archive.ics.uci.edu/ml/datasets/parkinsons, https://archive.ics.uci.edu/ml/datasets/Parkinsons+Telemonitoring, https://archive.ics.uci.edu/ml/datasets/Parkinson+Speech+Dataset+with++Multiple+Types+of+Sound+Recordings, https://archive.ics.uci.edu/ml/datasets/Parkinson%27s+Disease+Classification, https://archive.ics.uci.edu/ml/datasets/primary+tumor, http://www.ncbi.nlm.nih.gov/pmc/tools/openftlist/, http://www.ncbi.nlm.nih.gov/pmc/tools/ftp/#Data_Mining, https://github.com/Franck-Dernoncourt/pubmed-rct, https://www.ncbi.nlm.nih.gov/research/bionlp/APIs/BioC-PubMed/, https://www.ncbi.nlm.nih.gov/research/bionlp/APIs/BioC-PMC/, https://ebm-nlp.herokuapp.com/annotations, https://github.com/jayded/evidence-inference/tree/master/annotations, http://www.cs.toronto.edu/~complingweb/data/TORGO/torgo.html, http://lrec.elra.info/proceedings/lrec2012/pdf/230_Paper.pdf, http://emotion-research.net/sigs/speech-sig/is2018_compare.pdf, http://emotion-research.net/sigs/speech-sig/is18-compare, http://emotion-research.net/sigs/speech-sig/is2013_compare.pdf, http://emotion-research.net/sigs/speech-sig/is13-compare. Access: http://i2cvb.github.io/, Access: http://www.ehealthlab.cs.ucy.ac.cy/index.php/facilities/32-software/218-datasets, MRI Lesion Segmentation in Multiple Sclerosis Database, Emergency Tele-Orthopedics X-ray Digital Library. Data: http://physionet.org/physiobank/database/mimic3cdb/, Clinical Concept Embeddings Learned from Massive Sources of Medical Data This challenge was held in conjunction with MICCAI 2019. Large data set of brain tumor magnetic resonance scans. Keywords: large, CT, labels, All imaging It also includes radiologist's "truth"-markings on the locations of any abnormalities that may be present. Sign in Sign up Instantly share code, notes, and snippets. The data breach exposed medical records of over 200,000 U.S. patients. It contains both malignant and benign examples. article | more resources Information: http://fcon_1000.projects.nitrc.org/indi/abide/ Follow their code on GitHub. This page provides practical information on how to access / work with the data that will be made available to you within the context of a Data Access Request (DR) from Hartwig Medical Foundation. 8000 diffusion-weighted volumes The Digital Database for Screening Mammography (DDSM) is a resource for use by the mammographic image analysis research community. ~50 children (~10yo) with single follow-up with MRI, fMRI and assesments 1018 cases with some Radiologist Annotations/Segmentations and nodule counts This is a curated list of medical data for machine learning. Because of the graphic nature of the material some individuals may prefer not to view these images.They are provided for educational purposes only. Includes data for patients without polyps, 6-9mm polyps, and greater than 10 mm polyps. Access: http://adni.loni.usc.edu/data-samples/access-data/, CT Colongraphy for Colon Cancer (Cancer Imaging Archive) These were the active challenges at the time of adding, many more past challenges and upcoming challenges are present! The nine files included 200,000 patient records. Data: http://linea.docgraph.org, Liver Disorders Data Set Archived files: http://www.ncbi.nlm.nih.gov/pmc/tools/ftp/#Data_Mining. Mammographic images are available via the Pilot European Image Processing Archive (PEIPA) at the University of Essex. The second is for lung cancer detection. Keywords: medium, CT, covid, 1000+ CTs of COVID19 patients Exposed PII and PHI in Public GitHub Repositories Jelle Ursem is an ethical security researcher who has previously identified many data leaks on GitHub, including by Fortune 500 firms, publicly traded companies, and government organizations. In addition to providing you with access to OBGYN.net images we also point to other women's health related images on the Internet. Cancer imaging data sets across various cancer types (e.g. Bone X-Ray Deep Learning Competition using MURA. Get Started . Paper: http://lrec.elra.info/proceedings/lrec2012/pdf/230_Paper.pdf, Atypical Affect Interspeech Sub-Challenge. What would you like to do? They have collected seven open-access data sets and one private data set (3+1 lung data sets, 4 brain data sets). Built a Naive Bayes Classifier in Python that classifies whether or not a patient has diabetes based off a set of attributes of the patients. Overview: https://echonet.github.io/dynamic/index.html 5000 ICU patients in three separate hospital systems, detailed information about critical care stays for over 200,000 admissions at 200+ hospitals across the US. Texas Public Use Inpatient Data File The image data in The Cancer Imaging Archive (TCIA) is organized into purpose-built collections of subjects. Work fast with our official CLI. Keywords: small, multi-modal, LIDC-IDRI consists of diagonstic and lung cancer screening CTs. The Crookston Collection - A collection of medical slides taken by Dr. John H. Crookston that have been digitized and are available to the public and doctors. The Mammographic Image Analysis Society (MIAS) is an organisation of UK research groups interested in the understanding of mammograms and has generated a database of digital mammograms. As far as we know we are the only one that provides a medical picture database with basic information about each term pictured. Link: https://www.dshs.texas.gov/thcic/hospitals/Inpatientpudf.shtm, Dollars for Doctors Access: https://echonet.github.io/dynamic/index.html#access, The National Library of Medicine presents MedPix® Keywords: very-large, 4703 CXR of COVID19 patients, manually annotated Brixia score Anqi Qiu*, Ta Anh Tuan, Mei Lyn Ong, Yue Li, Anne Rifkin-Graboi, Helen Chen, Birit FP Broekman, Kenneth Kwek, Seang-Mei Saw, Yap-Seng Chong, Peter D. Gluckman, Marielle V. Fortier, Joanna Dawn Holbrook, Michael J. Meaney, "COMT Haplotypes Modulate Associations of Antenatal Maternal Anxiety and Neonatal Cortical Morphology", American Journal of Psychiatry, 172(2):163-72, 2015. Requires registration. Contribute to sfikas/medical-imaging-datasets development by creating an account on GitHub. The task is image registration - align all slices in particular set of images (consecutive stain cuts) together, for instance to the initial image plane. All images are 8 bits/pixel for black and white images, 24 bits/pixel for color images. Tuberculosis (TB) is a major problem of Belarus Public Health. Keywords: very-large, X-ray, labels, 371,920 chest x-rays associated with 227,943 imaging studies Data: https://archive.ics.uci.edu/ml/datasets/primary+tumor, PMC Open Access Subset Zhaonan Qu, Kaixiang Lin, Jayant Kalagnanam, Zhaojian Li, Jiayu Zhou, and Zhengyuan Zhou.