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Application of belief functions to medical image segmentation: A review

Application of belief functions to medical image segmentation: A review

3 May 2022
Ling Huang
S. Ruan
Thierry Denoeux
    EDL
    MedIm
ArXivPDFHTML

Papers citing "Application of belief functions to medical image segmentation: A review"

8 / 8 papers shown
Title
Mamba Based Feature Extraction And Adaptive Multilevel Feature Fusion For 3D Tumor Segmentation From Multi-modal Medical Image
Mamba Based Feature Extraction And Adaptive Multilevel Feature Fusion For 3D Tumor Segmentation From Multi-modal Medical Image
Zexin Ji
Beiji Zou
Xiaoyan Kui
Hua Li
P. Vera
S. Ruan
Mamba
46
0
0
30 Apr 2025
Has Multimodal Learning Delivered Universal Intelligence in Healthcare?
  A Comprehensive Survey
Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey
Qika Lin
Yifan Zhu
Xin Mei
Ling Huang
Jingying Ma
Kai He
Zhen Peng
Erik Cambria
Mengling Feng
32
16
0
23 Aug 2024
Tell and show: Combining multiple modalities to communicate manipulation
  tasks to a robot
Tell and show: Combining multiple modalities to communicate manipulation tasks to a robot
Petr Vanc
R. Škoviera
Karla Stepanova
17
0
0
02 Apr 2024
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
33
21
0
09 Oct 2023
Deep evidential fusion with uncertainty quantification and contextual
  discounting for multimodal medical image segmentation
Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation
Ling Huang
S. Ruan
P. Decazes
Thierry Denoeux
EDL
MedIm
22
1
0
12 Sep 2023
Transformer in Transformer
Transformer in Transformer
Kai Han
An Xiao
Enhua Wu
Jianyuan Guo
Chunjing Xu
Yunhe Wang
ViT
282
1,518
0
27 Feb 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 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
247
9,042
0
06 Jun 2015
1