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A Progressively-trained Scale-invariant and Boundary-aware Deep Neural
  Network for the Automatic 3D Segmentation of Lung Lesions

A Progressively-trained Scale-invariant and Boundary-aware Deep Neural Network for the Automatic 3D Segmentation of Lung Lesions

11 November 2018
Bo Zhou
Randolph Crawford
B. Dogdas
G. Goldmacher
Antong Chen
ArXivPDFHTML

Papers citing "A Progressively-trained Scale-invariant and Boundary-aware Deep Neural Network for the Automatic 3D Segmentation of Lung Lesions"

3 / 3 papers shown
Title
Multi-dimension unified Swin Transformer for 3D Lesion Segmentation in
  Multiple Anatomical Locations
Multi-dimension unified Swin Transformer for 3D Lesion Segmentation in Multiple Anatomical Locations
Shaoyan Pan
Yiqiao Liu
Sarah Halek
M. Tomaszewski
Shubing Wang
R. Baumgartner
Jianda Yuan
G. Goldmacher
Antong Chen
MedIm
31
1
0
04 Sep 2023
Weakly-Supervised Universal Lesion Segmentation with Regional Level Set
  Loss
Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss
Youbao Tang
Jinzheng Cai
K. Yan
Lingyun Huang
Guotong Xie
Jing Xiao
Jingjing Lu
Gigin Lin
Le Lu
50
25
0
03 May 2021
A deep learning-facilitated radiomics solution for the prediction of
  lung lesion shrinkage in non-small cell lung cancer trials
A deep learning-facilitated radiomics solution for the prediction of lung lesion shrinkage in non-small cell lung cancer trials
Antong Chen
Jennifer Saouaf
Bo Zhou
Randolph Crawford
Jianda Yuan
Junshui Ma
R. Baumgartner
Shubing Wang
G. Goldmacher
MedIm
21
7
0
05 Mar 2020
1