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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

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A list of awesome selected resources towards the application of machine learning in Biomedical/Healthcare Imaging, inspired by

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# 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/)