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https://github.com/XindiWu/Awesome-Machine-Learning-in-Biomedical-Healthcare-Imaging
A list of awesome selected resources towards the application of machine learning in Biomedical/Healthcare Imaging, inspired by
https://github.com/XindiWu/Awesome-Machine-Learning-in-Biomedical-Healthcare-Imaging
List: Awesome-Machine-Learning-in-Biomedical-Healthcare-Imaging
Last synced: about 1 month ago
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A list of awesome selected resources towards the application of machine learning in Biomedical/Healthcare Imaging, inspired by
- Host: GitHub
- URL: https://github.com/XindiWu/Awesome-Machine-Learning-in-Biomedical-Healthcare-Imaging
- Owner: XindiWu
- Created: 2019-10-21T19:14:03.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2019-10-22T03:27:52.000Z (about 5 years ago)
- Last Synced: 2024-05-23T06:27:01.761Z (7 months ago)
- Homepage:
- Size: 112 KB
- Stars: 58
- Watchers: 6
- Forks: 14
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-computer-vision - Awesome Machine Learning in Biomedical(Healthcare) Imaging
- ultimate-awesome - Awesome-Machine-Learning-in-Biomedical-Healthcare-Imaging - A list of awesome selected resources towards the application of machine learning in Biomedical/Healthcare Imaging, inspired by. (Other Lists / Monkey C Lists)
README
# Awesome Machine Learning in Biomedical(Healthcare) Imaging
> 🌈A list of awesome selected resources towards the application of machine learning in Biomedical/Healthcare Imaging, inspired by [awesome-php](https://github.com/ziadoz/awesome-php).If you also want to contribute to this list, feel free to send me a pull request or contact me🙌[@XindiWu](mailto:[email protected]).
## Table of Contents
## Courses
### Bioimage Analysis
Harvard: [Bio-Image Analysis Course](https://iccb.med.harvard.edu/bio-image-analysis-course)
Stanford: [Introduction to Bioimaging](https://web.stanford.edu/class/ee169/EE_169.html)
CMU: [Bioimage Informatics](https://www.andrew.cmu.edu/course/42-731/index.html)
Caltech: [Data Analysis in the Biological Sciences](http://bebi103.caltech.edu.s3-website-us-east-1.amazonaws.com/2018/)
### Biomedical Image Analysis
University of Nebraska: [Introduction to Biomedical Imaging and Image Analysis](https://www.unmc.edu/radiology/education/biomedical-imaging.html)
Stanford: [Computational Methods for Biomedical Image Analysis and Interpretation](https://canvas.stanford.edu/courses/98045)
Dartmouth College: [Medical Image Visualization and Analysis](https://engineering.dartmouth.edu/academics/courses/engg199-03)
UCLA: [Signal and Image Processing for Biomedicine](https://sa.ucla.edu/ro/Public/SOC/Results/ClassDetailterm_cd=16W&subj_area_cd=PBMED%20%20&crs_catlg_no=0209%20%20%20%20&class_id=825054200&class_no=%20001%20%20)
MIT: [Biomedical Signal and Image Processing](https://ocw.mit.edu/courses/health-sciences-and-technology/hst-582j-biomedical-signal-and-image-processing-spring-2007/index.htm)
NYU: [Biomedical Imaging II](http://bulletin.engineering.nyu.edu/preview_course_nopop.php?catoid=11&coid=27762)
UCSD: [Introduction to biomedical imaging and sensing](http://circuit.ucsd.edu/~zhaowei/ECE187/info.php)
ILLINOIS: [Biomedical imaging](https://ece.illinois.edu/academics/courses/profile/ECE380)
### Medical image analysis
Johns Hopkins: [Applied Medical Image Processing](https://ep.jhu.edu/programs-and-courses/585.703-applied-medical-image-processing)
UCB: [Medical Imaging Signals and Systems](https://www2.eecs.berkeley.edu/Courses/EEC261/)
Brown University: [Medical Image Analysis](http://vision.lems.brown.edu/content/engn-2500-medical-image-analysis)
MIT: [Principles of Medical Imaging](https://ocw.mit.edu/courses/nuclear-engineering/22-058-principles-of-medical-imaging-fall-2002/)
Purdue: [MEDICAL IMAGING DIAGNOSTIC TECHNOLOGIES](https://engineering.purdue.edu/ProEd/courses/medical-imaging-diagnostic-technologies)
University of Michigan Ann Arbor: [MEDICAL IMAGING SYSTEMS](https://bme.umich.edu/course/biomede-516/)
University of Florida: [Introduction to Biomedical Image Analysis and Imaging Informatics](https://www.bme.ufl.edu/labs/yang/pdf/Syllabus_Yang_BME6938-Revise.pdf)
CMU: [Methods In (Bio)Medical Image Analysis](https://www.cs.cmu.edu/~galeotti/methods_course/)
## Conferences
2019 MICCAI: [22nd International Conference on Medical Image Computing and Computer Assisted Intervention](https://www.miccai2019.org/)
2019 AIME: [Artificial Intelligence in Medicine](http://aime19.aimedicine.info/)
2019 AMIA: [AMIA Symposium](https://www.amia.org/amia2019)
2020 RECOMB: [International Conference on Research in Computational Molecular Biology](https://www.recomb2020.org/)
2020 PSB: [Pacific Symposium on Biocomputing](https://psb.stanford.edu/)
2020 ICHI: [IEEE International Conference on Healthcare Informatics](https://hs-heilbronn.de/ichi2020)
2020 CMIMI: [Conference on Machine Intelligence in Medical Imaging](https://siim.org/page/2019cmimi)
2019 ISBI: [The IEEE International Symposium on Biomedical Imaging](https://biomedicalimaging.org/2019/)
## Journal Collections
BMC: [Artificial intelligence in biomedical imaging](https://www.biomedcentral.com/collections/ai)
JAMA: [Deep Learning and Artificial Intelligence in Health Care](https://sites.jamanetwork.com/machine-learning/)
PLOS: [Machine Learning in Health and Biomedicine](https://collections.plos.org/mlforhealth)
Nature Medicine: [Digital Medicine](https://www.nature.com/collections/egjifhdcih)
IEEE: [Journal of Biomedical and Health Informatics](https://ieeexplore.ieee.org/xpl/topAccessedArticles.jsp?punumber=6221020)
## Datasets
External Link Collections: https://github.com/beamandrew/medical-data
Kaggle: [Medical Image](https://www.kaggle.com/datasets?search=Medical+image)
Kaggle: [Biology Image](https://www.kaggle.com/datasets?search=biology+image)
[The Cancer Imaging Archive (TCIA)](https://www.cancerimagingarchive.net/)
### Radiology (Ultrasound, Mammographs, X-Ray, CT, MRI, fMRI, etc.)
[Center for Invivo Microscopy (CIVM), Embrionic and Neonatal Mouse (H&E, MR)](http://www.civm.duhs.duke.edu/devatlas/)
[user guide](http://www.civm.duhs.duke.edu/devatlas/UserGuide.pdf)[Collaborative Informatics and Neuroimaging Suite (COINS)](https://portal.mrn.org/micis/index.php?subsite=dx)
[Alzheimer’s Disease Neuroimaging Initiative (ADNI)](http://adni.loni.ucla.edu/)
[The Open Access Series of Imaging Studies (OASIS)](http://www.oasis-brains.org/)
[Breast Cancer Digital Repository](https://bcdr.eu/)
[DDSM: Digital Database for Screening Mammography](http://marathon.csee.usf.edu/Mammography/Database.html)
[The Mammographic Image Analysis Society (MIAS) mini-database](http://peipa.essex.ac.uk/info/mias.html)
[Mammography Image Databases 100 or more images of mammograms with ground truth](http://marathon.csee.usf.edu/Mammography/Database.html)
[NLM HyperDoc Visible Human Project color, CAT and MRI image samples - over 30 images](http://www.nlm.nih.gov/research/visible/visible_human.html)
[CT Scans for Colon Cancer](https://wiki.cancerimagingarchive.net/display/Public/CT+COLONOGRAPHY#e88604ec5c654f60a897fa77906f88a6)
### Microscopy (Cell, Cytology, Biology, Protein, Molecular, Fluorescence, etc.)
[BDGP images from the FlyExpress database](www.flyexpress.net)
[The UCSB Bio-Segmentation Benchmark dataset](http://www.bioimage.ucsb.edu/research/biosegmentation)
[Pap Smear database](http://labs.fme.aegean.gr/decision/downloads)
[BIICBU Biological Image Repository](http://ome.grc.nia.nih.gov/iicbu2008/)
[RNAi dataset](http://ome.grc.nia.nih.gov/iicbu2008/rnai/index.html)
[Chinese Hamster Ovary cells (CHO) dataset](http://ome.grc.nia.nih.gov/iicbu2008/hela/index.html#cho)
[Locate Endogenus mouse sub-cellular organelles (END) databaset](http://locate.imb.uq.edu.au/)
[2D HeLa dataset (HeLa) datgaset](http://ome.grc.nia.nih.gov/iicbu2008/hela/index.html)
[Allen Brain Atlas](http://www.brain-map.org/)
[1000 Functional Connectomes Project](http://fcon_1000.projects.nitrc.org/)
[The Cell Centered Database (CCDB)]( http://ccdb.ucsd.edu/index.shtm)
[The Encyclopedia of DNA Elements (ENCODE)](http://genome.ucsc.edu/ENCODE/http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001046)
[The Human Protein Atlas](http://www.proteinatlas.org/)
[DRIVE: Digital Retinal Images for Vessel Extraction](http://www.isi.uu.nl/Research/Databases/DRIVE) / [Ground truth](http://www.cs.rug.nl/~imaging/databases/retina_database/retinalfeatures_database.html)
[El Salvador Atlas of Gastrointestinal VideoEndoscopy Images and Videos of his-res of studies taken from Gastrointestinal](http://www.gastrointestinalatlas.com)
### Histology and Histopathology
[The Histology Image Dataset (histologyDS)](http://www.informed.unal.edu.co/histologyDS)
[The Cancer Genome Atlas (TCGA)](http://cancergenome.nih.gov)
[International Cancer Genome Consortium](http://icgc.org) / [Data portal](http://dcc.icgc.org/)
[Stanford Tissue Microarray Database (TMA)](http://tma.im)
[MITOS dataset](http://ipal.cnrs.fr/ICPR2012/)
[DPA’s Whole Slide Imaging Repository](https://digitalpathologyassociation.org/whole-slide-imaging-repository)
[Atlas of bleast Histology](http://www.webmicroscope.net/atlases/breast/brcatlas_start.asp)
[ITK Analysis of Large Histology Datasets](http://www.na-mic.org/Wiki/index.php/ITK_Analysis_of_Large_Histology_Datasets)
[Histology Photo Album](http://www.histology-world.com/photoalbum/thumbnails.php?album=52)
[Slide Library of Virtual pathology, University of Leeds](http://www.virtualpathology.leeds.ac.uk/)
[Tissue Acquisition and Banking Services (TABS) of the NYU Experimental Pathology Core Facilities](http://pathology.med.nyu.edu/research/core-laboratories/tissue-banking)
[Aperio Images](http://images2.aperio.com/)
[HAPS Histology Image Database](http://hapshistology.wikifoundry.com/)
[NIH: chest x-ray datasets](https://nihcc.app.box.com/v/ChestXray-NIHCC)
## Tasks: (Link: https://paperswithcode.com/area/medical)
Medical Image Segmentation
EEG
Electrocardiography (ECG)
Drug Discovery
Cancer
Sleep Quality
Medical Image Registration
Disease Prediction
Mortality Prediction
Medical Image Generation
Protein Secondary Structure Prediction
Medical Diagnosis
Length-of-stay prediction
Seizure Detection
Skin
Histopathological Image Classification
Mitosis Detection
Computational Phenotyping
Epidemiology
Lung Disease Classification
Diabetic Retinopathy Detection
X-Ray
Medical Relation Extraction
Metal Artifact Reduction
Photoplethysmography (PPG)
Lung Nodule Classification
Pneumonia Detection
Surgical Skills Evaluation
Readmission Prediction
Automatic Sleep Stage Classification
Eeg Decoding
Skull Stripping
Participant Intervention Comparison Outcome Extraction
Patient Outcomes
Medical Report Generation
Knee Osteoarthritis Prediction
Multi-Label Classification Of Biomedical Texts
breast density classification
Medical Super-Resolution
Molecule Interpretation
Mammogram
Cancer Metastasis Detection
Pain Intensity Regression
Electromyography (EMG)
Surgical Gesture Recognition
Protein Function Prediction
epilepsy prediction
Seizure prediction
White Matter Fiber Tractography
Single-cell modeling
Age-Related Macular Degeneration Classification
Sequential Diagnosis
Ecg Risk Stratification
Diabetes Prediction
Magnetic Resonance Fingerprinting
Tomography
Atrial Fibrillation
Malaria Risk Exposure Prediction
Muscular Movement Recognition
Medical Code Prediction
Motion Correction In Multishot Mri
Chemical Reaction Prediction
Ultrasound
## Competitions:
[Grand Challenges in Biomedical Image Analysis](https://grand-challenge.org/)
[The Cancer Imaging Archive (TCIA) Public Access](https://wiki.cancerimagingarchive.net/display/Public/Challenge+competitions)
[Competitions in Kaggle](https://www.kaggle.com/competitions?sortBy=relevance&group=general&search=medical&page=1&pageSize=20&turbolinks%5BrestorationIdentifier%5D=34d9733a-6ecc-4581-a23d-cc00703b91c8)
[The MICCAI 2014 Machine Learning Challenge](https://competitions.codalab.org/competitions/1471)
[The ISBI 2019 Challenges](https://biomedicalimaging.org/2019/challenges/)
[Medical Segmentation Decathlon](http://medicaldecathlon.com/)