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RSNA Intracranial Hemorrhage Detection
Identify acute intracranial hemorrhage and its subtypes
The dataset for this Kaggle challenge was created on the MD.ai platform in collaboration with the Radiological Society of North America (RSNA) and the American Society of Neuroradiology (ASNR), with data contributions from Stanford University, St. Michael's Hospital, Thomas Jefferson University, and Universidade Federal de São Paulo.
Data
Create high-quality labelled training and validation datasets
Sample Public Datasets
The Cancer Genome Atlas - Lung Adenocarcinoma public
CT PET Chest
From The Cancer Imaging Archive (TCIA): the Cancer Genome Atlas Lung Adenocarcinoma data collection is part of a larger effort to build a research community focused on connecting cancer phenotypes to genotypes by providing clinical images matched to subjects from The Cancer Genome Atlas (TCGA). Clinical, genetic, and pathological data resides in the Genomic Data Commons (GDC) Data Portal while the radiological data is stored on The Cancer Imaging Archive.
Dataset
DICOM
152
625
48,931
+ 621 more...
Users
A
G
Labels
Nodule
Emphysema
NLP Dataset Builder
Stroke
ischemia
edema
gray-white differentiation
hemorrhage
Web-based Annotation Tools
A created bounding box annotation
B created freeform annotation
Develop
API, jupyter integration, and client libraries to facilitate model development
Model Training
Federated Learning
Model Validation
Deploy
Run models in the browser, on-premises, or in your cloud
Run Model Inference
Customers and Partners
MD.ai in the Press
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