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这是一个用于机器学习等图像处理方法研究的医学图像数据集列表。
此列表仅供参考之用，请确保您尊重这里所列数据的所有使用限制。


EchoNet-Dynamic

A Large New Cardiac Motion Video Data Resource for Medical Machine Learning, from Stanford. Overview: echonet.github.io/dynam Access: echonet.github.io/dynam


The National Library of Medicine presents MedPix®
Database of 53,000 medical images from 13,000 patients with annotations. Requires registration.
Information: medpix.nlm.nih.gov/home


ABIDE: The Autism Brain Imaging Data Exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.
Function MRI images for 539 individuals suffering from ASD and 573 typical controls. These 1112 datasets are composed of structural and resting state functional MRI data along with an extensive array of phenotypic information. Requires registration.
Paper: ncbi.nlm.nih.gov/pubmed
Information: fcon_1000.projects.nitrc.org
Preprocessed version: preprocessed-connectomes-project.org


Alzheimer's Disease Neuroimaging Initiative (ADNI)
MRI database on Alzheimer's patients and healthy controls. Also has clinical, genomic, and biomaker data. Requires registration.
Paper: neurology.org/content/7
Access: adni.loni.usc.edu/data-


CT Colongraphy for Colon Cancer (Cancer Imaging Archive)

CT scan for diagnosing of colon cancer. Includes data for patients without polyps, 6-9mm polyps, and greater than 10 mm polyps. Access: wiki.cancerimagingarchive.net


Digital Retinal Images for Vessel Extraction (DRIVE)
The DRIVE database is for comparative studies on segmentation of blood vessels in retinal images. It consists of 40 photographs out of which 7 showing signs of mild early diabetic retinopathy.
Paper: ieeexplore.ieee.org/doc
Access: isi.uu.nl/Research/Data


AMRG Cardiac Atlas

The AMRG Cardiac MRI Atlas is a complete labelled MRI image set of a normal patient's heart acquired with the Auckland MRI Research Group 's Siemens Avanto scanner. The atlas aims to provide university and school students, MR technologists, clinicians...


Congenital Heart Disease (CHD) Atlas

The Congenital Heart Disease (CHD) Atlas represents MRI data sets, physiologic clinical data and computer models from adults and children with various congenital heart defects. The data have been acquired from several clinical centers including Rady...


DETERMINE

Defibrillators to Reduce Risk by Magnetic Resonance Imaging Evaluation, is a prospective, multicenter, randomized clinical trials in patients with coronary artery diseases and mild-to-moderate left ventricular dysfunction. The primary objective...


MESA

Multi-Ethnic Study of Atherosclerosis, is a large-scale cardiovascular population study (>6,500 participants) conducted in six centres in the USA. It aims to investigate the manifestation of subclinical to clinical cardiovascular disease before...


OASIS

The Open Access Series of Imaging Studies (OASIS) is a project aimed at making MRI data sets of the brain freely available to the scientific community. Two datasets are available: a cross-sectional and a longitudinal set.

  • Cross-sectional MRI Data in Young, Middle Aged, Nondemented and Demented Older Adults: This set consists of a cross-sectional collection of 416 subjects aged 18 to 96. For each subject, 3 or 4 individual T1-weighted MRI scans obtained in single scan sessions are included. The subjects are all right-handed and include both men and women. 100 of the included subjects over the age of 60 have been clinically diagnosed with very mild to moderate Alzheimer’s disease (AD). Additionally, a reliability data set is included containing 20 nondemented subjects imaged on a subsequent visit within 90 days of their initial session.
  • Longitudinal MRI Data in Nondemented and Demented Older Adults: This set consists of a longitudinal collection of 150 subjects aged 60 to 96. Each subject was scanned on two or more visits, separated by at least one year for a total of 373 imaging sessions. For each subject, 3 or 4 individual T1-weighted MRI scans obtained in single scan sessions are included. The subjects are all right-handed and include both men and women. 72 of the subjects were characterized as nondemented throughout the study. 64 of the included subjects were characterized as demented at the time of their initial visits and remained so for subsequent scans, including 51 individuals with mild to moderate Alzheimer’s disease. Another 14 subjects were characterized as nondemented at the time of their initial visit and were subsequently characterized as demented at a later visit.

Access: oasis-brains.org/


Isic Archive - Melanoma

This archive contains 23k images of classified skin lesions. It contains both malignant and benign examples.

Each example contains the image of the lesion, meta data regarding the lesion (including clasisfication and segmentation) and meta data regarding the patient.

The data can be viewed in this link: isic-archive.com (in the gallery section)
It can be downloaded through the site or by using this repository:
github.com/GalAvineri/I


SCMR Consensus Data

The SCMR Consensus Dataset is a set of 15 cardiac MRI studies of mixed pathologies (5 healthy, 6 myocardial infarction, 2 heart failure and 2 hypertrophy), which were acquired from different MR machines (4 GE, 5 Siemens, 6 Philips). The main objectives...


Sunnybrook Cardiac Data

The Sunnybrook Cardiac Data (SCD), also known as the 2009 Cardiac MR Left Ventricle Segmentation Challenge data, consist of 45 cine-MRI images from a mixed of patients and pathologies: healthy, hypertrophy, heart failure with infarction and heart...

Access: cardiacatlas.org/studie


Lung Image Database Consortium (LIDC)

Preliminary clinical studies have shown that spiral CT scanning of the lungs can improve early detection of lung cancer in high-risk individuals. Image processing algorithms have the potential to assist in lesion detection on spiral CT studies, and to assess the stability or change in lesion size on serial CT studies. The use of such computer-assisted algorithms could significantly enhance the sensitivity and specificity of spiral CT lung screening, as well as lower costs by reducing physician time needed for interpretation.

The intent of the Lung Imaging Database Consortium (LIDC) initiative was to support a consortium of institutions to develop consensus guidelines for a spiral CT lung image resource and to construct a database of spiral CT lung images. 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. The database is available to researchers and users through the Internet and has wide utility as a research, teaching, and training resource.

Specifically, the LIDC initiative aims were to provide:

  • a reference database for the relative evaluation of image processing or CAD algorithms and
  • a flexible query system that will provide investigators the opportunity to evaluate a wide range of technical parameters and de-identified clinical information within this database that may be important for research applications.

This resource will stimulate further database development for image processing and CAD evaluation for applications that include cancer screening, diagnosis, and image guided intervention, and treatment. Therefore, the NCI encourages investigator-initiated grant applications that utilize the database in their research. NCI also encourages investigator-initiated grant applications that provide tools or methodology that may improve or complement the mission of the LIDC.

Access: wiki.cancerimagingarchive.net


TCIA Collections

Cancer imaging data sets across various cancer types (e.g. carcinoma, lung cancer, myeloma) and various imaging modalities. The image data in The Cancer Imaging Archive (TCIA) is organized into purpose-built collections of subjects. The subjects typically have a cancer type and/or anatomical site (lung, brain, etc.) in common. Each link in the table below contains information concerning the scientific value of a collection, information about how to obtain any supporting non-image data which may be available, and links to view or download the imaging data. 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.

Access: cancerimagingarchive.net


Belarus tuberculosis portal

Tuberculosis (TB) is a major problem of Belarus Public Health. Recently situation has been complicated with emergence and development of MDR/XDR TB and HIV/TB which require long-term treatment. Many and the most severe cases usually disseminate across the country to different TB dispensaries. The ability of leading Belarus TB specialists to follow such patients will be greatly improved by using a common database containing patients’ radiological images, lab work and clinical data. This will also significantly improve adherence to the treatment protocol and result in a better record of the treatment outcomes. Criteria for inclusion clinical cases in the database of the portal - patients admitted to the MDR-TB department of RSPC of Pulmonology and Tuberculosis with diagnosed or suspected of MDR-TB, which conducted CT – study (± 2 months from the date of registration) Belarus dataset have both chest X-rays and CT scans of the same patient.

Access: tuberculosis.by/


DDSM: Digital Database for Screening Mammography

The Digital Database for Screening Mammography (DDSM) is a resource for use by the mammographic image analysis research community. Primary support for this project was a grant from the Breast Cancer Research Program of the U.S. Army Medical Research and Materiel Command. The DDSM project is a collaborative effort involving co-p.i.s at the Massachusetts General Hospital (D. Kopans, R. Moore), the University of South Florida (K. Bowyer), and Sandia National Laboratories (P. Kegelmeyer). Additional cases from Washington University School of Medicine were provided by Peter E. Shile, MD, Assistant Professor of Radiology and Internal Medicine. Additional collaborating institutions include Wake Forest University School of Medicine (Departments of Medical Engineering and Radiology), Sacred Heart Hospital and ISMD, Incorporated. The primary purpose of the database is to facilitate sound research in the development of computer algorithms to aid in screening. Secondary purposes of the database may include the development of algorithms to aid in the diagnosis and the development of teaching or training aids. The database contains approximately 2,500 studies. Each study includes two images of each breast, along with some associated patient information (age at time of study, ACR breast density rating, subtlety rating for abnormalities, ACR keyword description of abnormalities) and image information (scanner, spatial resolution, ...). Images containing suspicious areas have associated pixel-level "ground truth" information about the locations and types of suspicious regions. Also provided are software both for accessing the mammogram and truth images and for calculating performance figures for automated image analysis algorithms.

Access: marathon.csee.usf.edu/M


INbreast: Database for Digital Mammography

The INbreast database is a mammographic database, with images acquired at a Breast Centre, located in a University Hospital (Hospital de São João, Breast Centre, Porto, Portugal). INbreast has a total of 115 cases (410 images) of which 90 cases are from women with both breasts (4 images per case) and 25 cases are from mastectomy patients (2 images per case). Several types of lesions (masses, calcifications, asymmetries, and distortions) are included. Accurate contours made by specialists are also provided in XML format.

Access: medicalresearch.inescporto.pt


mini-MIAS: MIAS MiniMammographic Database

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. Films taken from the UK National Breast Screening Programme have been digitised to 50 micron pixel edge with a Joyce-Loebl scanning microdensitometer, a device linear in the optical density range 0-3.2 and representing each pixel with an 8-bit word. The database contains 322 digitised films and is available on 2.3GB 8mm (ExaByte) tape. It also includes radiologist's "truth"-markings on the locations of any abnormalities that may be present. The database has been reduced to a 200 micron pixel edge and padded/clipped so that all the images are 1024x1024. Mammographic images are available via the Pilot European Image Processing Archive (PEIPA) at the University of Essex.

Access: peipa.essex.ac.uk/info/


Prostate

Prostate cancer (CaP) has been reported on a worldwide scale to be the second most frequently diagnosed cancer of men accounting for 13.6% (Ferlay et al. (2010)). 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. (2010)).

Magnetic resonance imaging (MRI) provides imaging techniques allowing to diagnose and localize CaP. The I2CVB provides a multi-parametric MRI dataset to help at the development of computer-aided detection and diagnosis (CAD) system. Access: i2cvb.github.io/

Access: ehealthlab.cs.ucy.ac.cy

  • MRI Lesion Segmentation in Multiple Sclerosis Database
  • Emergency Tele-Orthopedics X-ray Digital Library
  • IMT Segmentation
  • Needle EMG MUAP Time Domain Features


DICOM image sample sets

These datasets are exclusively available for research and teaching. You are not authorized to redistribute or sell them, or use them for commercial purposes.

All these DICOM files are compressed in JPEG2000 transfer syntax.

Access: osirix-viewer.com/resou


SCR database: Segmentation in Chest Radiographs

The automatic segmentation of anatomical structures in chest radiographs is of great importance for computer-aided diagnosis in these images. The SCR database has been established to facilitate comparative studies on segmentation of the lung fields, the heart and the clavicles in standard posterior-anterior chest radiographs.

In the spirit of cooperative scientific progress, we freely share the SCR database and are committed to maintaining a public repository of results of various algorithms on these segmentation tasks. On these pages, instructions can be found on downloading the database and uploading results, and benchmark results of various methods can be inspected.

Access: isi.uu.nl/Research/Data


Medical Image Databases & Libraries

Access: omnimedicalsearch.com/i

General Category

  • e-Anatomy.org - Interactive Atlas of Anatomy - e-anatomy is an anatomy e-learning web site. More than 1500 slices from normal CT and MR exams were selected in order to cover the entire sectional anatomy of human body. Images were labeled using Terminologia Anatomica. A user-friendly interface allows to cine through multi-slice image series combined with interactive textual information, 3D models and anatomy drawings.
  • Medical Pictures and Definitions - Welcome to the largest database of medical pictures and definitions on the Internet. There are many sites sites that provide medical information but very few that provide medical pictures. As far as we know we are the only one that provides a medical picture database with basic information about each term pictured. Editor's Note: Nice website with free access & no pesky registration to 1200+ health and medical related images with definitions.
  • Nucleus Medical Art - Medical Illustrations, Medical Art. Includes 3D animations. "Nucleus Medical Art, Inc. is a leading creator and distributor of medical illustrations, medical animations, and interactive multimedia for publishing, legal, healthcare, entertainment, pharmaceutical, medical device, academia and other markets, both in the U.S. and abroad. Editors Note: Great website.
  • Medical Image Databases on the Internet (UTHSCSA Library) - A directory of links to websites with topic specific medical related images.
  • Surgery Videos - A National Library of Medicine MedlinePlus collection of links to 100s and 100s of different surgical procedures. You must have RealPlayer media player on your computer to view these videos which are free of charge.
  • The ADAM Medical Encyclopedia with Illustrations. Perhaps one of the best illustrated medical works on the internet today, the ADAM Medical Encyclopedia includes over 4,000 articles about diseases, tests, symptoms, injuries, and surgeries. It also contains an extensive library of medical photographs and illustrations to back up those 4,000 articles. These illustrations and articles are free to the public.
  • Hardin MD - Medical and Disease Pictures, is a Free and established resource that has been offered by the University of Iowa for quite some time. The home page is in directory style where users will have to drill down to find the images they are looking for, many of which go offsite. Nevertheless, Hardin MD is an excellent gateway to 1,000s of detailed medical photos and illustrations.
  • Health Education Assets Library (HEAL) - Health on the Net Foundation Media Gallery Headquartered in Switzerland, (HON) is an international body that seeks to encourage ethical provision of online health information. "HONmedia (the image gallery) is an unique repository of over 6'800 medical images and videos, pertaining to 1,700 topics and themes. This peerless database has been created manually by HON and new image links are constantly being added from the world-wide Web. HON encourages users to make their own image links available via the Submit an image link." Library includes anatomical images, visual affects of diseases and conditions and procedures.
  • 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. We welcome public health professionals, the media, laboratory scientists, educators, students, and the worldwide public to use this material for reference, teaching, presentation, and public health messages. The content is organized into hierarchical categories of people, places, and science, and is presented as single images, image sets, and multimedia files.
  • Images from the History of Medicine - This system provides access to the nearly 60,000 images in the prints and photograph collection of the History of Medicine Division (HMD) of the U.S. National Library of Medicine (NLM). The collection includes portraits, pictures of institutions, caricatures, genre scenes, and graphic art in a variety of media, illustrating the social and historical aspects of medicine.
  • Pozemedicale.org - Collection of medical images in Spanish, Italian, Portuguese and Italian.
  • Old Medical Pictures: Hundreds of fascinating and interesting old, but high quality photographs and images from the late 19th and early 20th century.


Subject Speciality Image Libraries and Collections

  • Anatomy of the Human Body by Henry Gray - The Bartleby.com edition of Gray’s Anatomy of the Human Body features 1,247 vibrant engravings—many in color—from the classic 1918 publication.
  • 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.
  • DAVE Project - A searchable library of gastrointestinal endoscopic video clips covering a wide spectrum endoscopic imaging.
  • Dermnet - Browsable collection of over 8,000 high quality, dermatology images.
  • Interactive Dermatology Atlas - Image reference source for common and uncommon skin problems.
  • 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.
  • GastroLab Endoscopy Archives Was initiated in 1996 with the goal of maintaining an endoscopic image gallery free to use for all interested health care personals.
  • MedPix Is a Radiology and Medical Picture Databases resource tool. The home page interface is confusing and the entire website design is not user-friendly and has a mid 1990s feel to it. However, if you have the time (patience) it could prove to be an important resource for some.
  • OBGYN.net Image Library - This site is devoted entirely to providing access to images of interest to women's health. In addition to providing you with access to OBGYN.net images we also point to other women's health related images on the Internet. Because of the graphic nature of the material some individuals may prefer not to view these images.They are provided for educational purposes only.


VIA Group Public Databases

Documented image databases are essential for the development of quantitative image analysis tools especially for tasks of computer-aided diagnosis (CAD). In collaboration with the I-ELCAP group we have established two public image databases that contain lung CT images in the DICOM format together with documentation of abnormalities by radiologists. Please access the links below for more details:

Access: via.cornell.edu/databas


CVonline: Image Databases

Access: homepages.inf.ed.ac.uk/


The USC-SIPI Image Database

The USC-SIPI image database is a collection of digitized images. It is maintained primarily to support research in image processing, image analysis, and machine vision. The first edition of the USC-SIPI image database was distributed in 1977 and many new images have been added since then.

The database is divided into volumes based on the basic character of the pictures. Images in each volume are of various sizes such as 256x256 pixels, 512x512 pixels, or 1024x1024 pixels. All images are 8 bits/pixel for black and white images, 24 bits/pixel for color images. The following volumes are currently available:

Textures 	Brodatz textures, texture mosaics, etc.
Aerials 	High altitude aerial images
Miscellaneous 	Lena, the mandrill, and other favorites
Sequences 	Moving head, fly-overs, moving vehicles

Access: sipi.usc.edu/database/


Histology dataset: image registration of differently stain slices

The dataset consists of 2D histological microscopy tissue slices, stained with different stains, and landmarks denoting key-points in each slice. The task is image registration - align all slices in particular set of images (consecutive stain cuts) together, for instance to the initial image plane. The main challenges for these images are the following: very large image size, appearance differences, and lack of distinctive appearance objects. The dataset contains 108 image pairs and manually placed landmarks for registration quality evaluation.

Access: cmp.felk.cvut.cz/~borov


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发布于 2021-08-29 00:31
健康医疗大数据
数据集
医学影像

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