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A deep learning-based framework for segmenting invisible clinical target
  volumes with estimated uncertainties for post-operative prostate cancer
  radiotherapy

A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy

28 April 2020
Anjali Balagopal
D. Nguyen
H. Morgan
Yaochung Weng
M. Dohopolski
Mu-Han Lin
A. Sadeghnejad-Barkousaraie
Y. Gonzalez
A. Garant
N. Desai
R. Hannan
Steve B. Jiang
ArXivPDFHTML

Papers citing "A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy"

9 / 9 papers shown
Title
AI-Assisted Decision-Making for Clinical Assessment of Auto-Segmented Contour Quality
AI-Assisted Decision-Making for Clinical Assessment of Auto-Segmented Contour Quality
Biling Wang
Austen Maniscalco
T. Bai
Siqiu Wang
M. Dohopolski
...
Chenyang Shen
D. Nguyen
Junzhou Huang
Steve B. Jiang
Xinlei Wang
50
0
0
01 May 2025
A review of uncertainty quantification in medical image analysis:
  probabilistic and non-probabilistic methods
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods
Ling Huang
S. Ruan
Yucheng Xing
Mengling Feng
48
22
0
09 Oct 2023
Deep Learning (DL)-based Automatic Segmentation of the Internal Pudendal
  Artery (IPA) for Reduction of Erectile Dysfunction in Definitive Radiotherapy
  of Localized Prostate Cancer
Deep Learning (DL)-based Automatic Segmentation of the Internal Pudendal Artery (IPA) for Reduction of Erectile Dysfunction in Definitive Radiotherapy of Localized Prostate Cancer
Anjali Balagopal
M. Dohopolski
Y. Kwon
S. Montalvo
H. Morgan
...
Xiao Liang
Xinran Zhong
Mu-Han Lin
N. Desai
Steve B. Jiang
15
0
0
03 Feb 2023
Prior Guided Deep Difference Meta-Learner for Fast Adaptation to
  Stylized Segmentation
Prior Guided Deep Difference Meta-Learner for Fast Adaptation to Stylized Segmentation
Anjali Balagopal
D. Nguyen
T. Bai
M. Dohopolski
Mu-Han Lin
Steve B. Jiang
OOD
23
1
0
19 Nov 2022
Trustworthy clinical AI solutions: a unified review of uncertainty
  quantification in deep learning models for medical image analysis
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
Benjamin Lambert
Florence Forbes
A. Tucholka
Senan Doyle
Harmonie Dehaene
M. Dojat
34
81
0
05 Oct 2022
PSA-Net: Deep Learning based Physician Style-Aware Segmentation Network
  for Post-Operative Prostate Cancer Clinical Target Volume
PSA-Net: Deep Learning based Physician Style-Aware Segmentation Network for Post-Operative Prostate Cancer Clinical Target Volume
Anjali Balagopal
H. Morgan
M. Dohopolski
Ramsey Timmerman
J. Shan
...
D. Nguyen
R. Hannan
A. Garant
N. Desai
Steve B. Jiang
24
38
0
15 Feb 2021
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
376
10,639
0
19 Feb 2017
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Zhuowen Tu
Kaiming He
348
10,237
0
16 Nov 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
289
9,167
0
06 Jun 2015
1