专栏名称: 机器学习研究会
机器学习研究会是北京大学大数据与机器学习创新中心旗下的学生组织,旨在构建一个机器学习从事者交流的平台。除了及时分享领域资讯外,协会还会举办各种业界巨头/学术神牛讲座、学术大牛沙龙分享会、real data 创新竞赛等活动。
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【学习】一些使用机器学习技术的医疗数据和论文汇总

机器学习研究会  · 公众号  · AI  · 2017-05-15 20:55

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摘要
 

转自:视觉机器人

一些使用机器学习技术的医疗数据和论文汇总包括:自闭症脑成像数据,阿尔茨海默病神经影像,AMRG心脏图集,肺图像数据,各种癌症类型(例如癌,肺癌,骨髓瘤)的癌症成像数据集,白俄罗斯肺结核,乳房X光照相,前列腺癌。

This is a curated list of medical data for machine learning.
This list is provided for informational purposes only, please make sure you respect any and all usage restrictions for any of the data listed here.

1. Medical Imaging Data

The National Library of Medicine presents MedPix®
Database of 53,000 medical images from 13,000 patients with annotations. Requires registration.
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.
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: http://www.ncbi.nlm.nih.gov/pubmed/23774715
Information: http://fcon_1000.projects.nitrc.org/indi/abide/
Preprocessed version: http://preprocessed-connectomes-project.org/abide/


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: http://www.neurology.org/content/74/3/201.short
Access: http://adni.loni.usc.edu/data-samples/access-data/


AMRG Cardiac AtlasThe 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) AtlasThe 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...

DETERMINEDefibrillators 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...

MESAMulti-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...


OASISThe 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: http://www.oasis-brains.org/


SCMR Consensus DataThe 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 DataThe 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: http://www.cardiacatlas.org/studies/


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: http://imaging.cancer.gov/programsandresources/informationsystems/lidc


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: http://www.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: http://tuberculosis.by/


链接:

https://github.com/beamandrew/medical-data


原文链接:

http://weibo.com/5501429448/F3cuYzR5L?ref=home&rid=2_0_202_2667275193170702072&type=comment#_rnd1494837367077

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