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Rethinking Annotator Simulation: Realistic Evaluation of Whole-Body PET
  Lesion Interactive Segmentation Methods

Rethinking Annotator Simulation: Realistic Evaluation of Whole-Body PET Lesion Interactive Segmentation Methods

2 April 2024
Zdravko Marinov
Moon S. Kim
Jens Kleesiek
Rainer Stiefelhagen
ArXivPDFHTML

Papers citing "Rethinking Annotator Simulation: Realistic Evaluation of Whole-Body PET Lesion Interactive Segmentation Methods"

5 / 5 papers shown
Title
Adaptive Multi-scale Online Likelihood Network for AI-assisted
  Interactive Segmentation
Adaptive Multi-scale Online Likelihood Network for AI-assisted Interactive Segmentation
Muhammad Asad
Helena Williams
Indrajeet Mandal
S. Ather
Jan Deprest
Jan D'hooge
Tom Kamiel Magda Vercauteren
35
5
0
23 Mar 2023
Guiding the Guidance: A Comparative Analysis of User Guidance Signals
  for Interactive Segmentation of Volumetric Images
Guiding the Guidance: A Comparative Analysis of User Guidance Signals for Interactive Segmentation of Volumetric Images
Zdravko Marinov
Rainer Stiefelhagen
Jens Kleesiek
29
7
0
13 Mar 2023
MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from
  Medical Images Using Deep Learning
MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning
Xiangde Luo
Guotai Wang
Tao Song
Jingyang Zhang
Michael Aertsen
Jan Deprest
Sebastien Ourselin
Tom Kamiel Magda Vercauteren
Shaoting Zhang
43
96
0
25 Apr 2021
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
247
9,042
0
06 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
229
74,467
0
18 May 2015
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