MSD-Net: Multi-Scale Discriminative Network for COVID-19 Lung Infection Segmentation on CT
Since the first patient reported in December 2019, 2019 novel coronavirus disease (COVID-19) has become global pandemic with more than 10 million total confirmed cases and 500 thousand related deaths. Using deep learning methods to quickly identify COVID-19 and accurately segment the infected area c...
Main Authors: | Bingbing Zheng, Yaoqi Liu, Yu Zhu, Fuli Yu, Tianjiao Jiang, Dawei Yang, Tao Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9208691/ |
Similar Items
-
U-Net combined with multi-scale attention mechanism for liver segmentation in CT images
by: Jiawei Wu, et al.
Published: (2021-10-01) -
Silencing of MsD14 Resulted in Enhanced Forage Biomass through Increasing Shoot Branching in Alfalfa (<i>Medicago sativa</i> L.)
by: Lin Ma, et al.
Published: (2022-03-01) -
Lung Segmentation in CT Images: A Residual U-Net Approach on a Cross-Cohort Dataset
by: Joana Sousa, et al.
Published: (2022-02-01) -
Estudo de compostos orgânicos em lixiviado de aterros sanitários por EFS e CG/EM Study of organic compounds in landfill leachate by SPE and GC/MSD
by: Irajá do Nascimento Filho, et al.
Published: (2001-08-01) -
DISCUSSION ON COMPOUNDING METHOD AND EMPIRICAL METHOD APPLYING ON CALCULATING THE STRESS INTENSITY FACTOR IN MSD
by: WU WenLong, et al.
Published: (2015-01-01)