Our goal is to investigate using only case-level labels extracted automatically from radiology reports to construct a multi-disease classifier for CT scans with deep learning method. We chose four lung diseases as a start: atelectasis, pulmonary …
The idea of the project is to apply 2D U-net to Segment the RIO using the publicly available data from ISIC Challenge 2017 and classification of the segmented region for classification of lesion. Multiple OTS model ( Resnet, VGG, Densenet) were used …
Lung diseases classification in 2D using chest CT cases and Analysis the multi-channel effect on classification. This work is been done during summer internship July-Aguest 2018, Duke University Medical Center.