GASNet: Weakly-supervised Framework for COVID-19 Lesion Segmentation

GASNet: Weakly-supervised Framework for COVID-19 Lesion Segmentation

19 October 2020

Jie Zhou

Papers citing "GASNet: Weakly-supervised Framework for COVID-19 Lesion Segmentation"

5 / 5 papers shown

Title
Light In The Black: An Evaluation of Data Augmentation Techniques for COVID-19 CT's Semantic Segmentation Bruno A. Krinski Daniel V. Ruiz E. Todt 3DPC 30 2 0 19 May 2022
COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans Nastaran Enshaei A. Oikonomou M. Rafiee Parnian Afshar Shahin Heidarian Arash Mohammadi Konstantinos N. Plataniotis F. Naderkhani 11 4 0 04 Jul 2021
Lung Infection Quantification of COVID-19 in CT Images with Deep Learning F. Shan Yaozong Gao Jun Wang Weiya Shi N. Shi Miaofei Han Zhong Xue D. Shen Yuxin Shi 97 575 0 10 Mar 2020
CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation D. Jin Ziyue Xu Youbao Tang Adam P. Harrison D. Mollura MedIm 44 185 0 11 Jun 2018
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation Adam Paszke Abhishek Chaurasia Sangpil Kim Eugenio Culurciello SSeg 216 2,050 0 07 Jun 2016