Author: Amine Amyar; Romain Modzelewski; Su Ruan
Title: Multi-task Deep Learning Based CT Imaging Analysis For COVID-19: Classification and Segmentation Document date: 2020_4_21
ID: hiac6ur7_10
Snippet: In this work, we propose a novel multi-task deep learning model for jointly detecting COVID-19 image and segmenting lesions. The main challenges of this work are: 1) the lack of data and annotated data, the databases were collected from multiple sources with a huge variation in images and most of the images are not clean (see Fig 1) , 2) instead of expensive models like ResNet 50 or DenseNet, developing a multitasking approach to reduce overfitti.....
Document: In this work, we propose a novel multi-task deep learning model for jointly detecting COVID-19 image and segmenting lesions. The main challenges of this work are: 1) the lack of data and annotated data, the databases were collected from multiple sources with a huge variation in images and most of the images are not clean (see Fig 1) , 2) instead of expensive models like ResNet 50 or DenseNet, developing a multitasking approach to reduce overfitting and improve results.
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