shankara-93 / vinbigdata-chest-x-ray-abnormalities-detection Goto Github PK

In this competition, you’ll automatically localize and classify 14 types of thoracic abnormalities from chest radiographs. You'll work with a dataset consisting of 18,000 scans that have been annotated by experienced radiologists. You can train your model with 15,000 independently-labeled images and will be evaluated on a test set of 3,000 images. These annotations were collected via VinBigData's web-based platform, VinLab. Details on building the dataset can be found in our recent paper “VinDr-CXR: An open dataset of chest X-rays with radiologist's annotations”. If successful, you'll help build what could be a valuable second opinion for radiologists. An automated system that could accurately identify and localize findings on chest radiographs would relieve the stress of busy doctors while also providing patients with a more accurate diagnosis.