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Multi-Decoder Networks with Multi-Denoising Inputs for Tumor
  Segmentation

Multi-Decoder Networks with Multi-Denoising Inputs for Tumor Segmentation

16 November 2020
Minh H. Vu
T. Nyholm
Tommy Löfstedt
    MedIm
ArXiv (abs)PDFHTML

Papers citing "Multi-Decoder Networks with Multi-Denoising Inputs for Tumor Segmentation"

6 / 6 papers shown
Using Synthetic Images to Augment Small Medical Image Datasets
Using Synthetic Images to Augment Small Medical Image Datasets
Minh H. Vu
L. Tronchin
T. Nyholm
Tommy Löfstedt
MedIm
260
1
0
02 Mar 2025
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
299
184
0
05 Oct 2022
Med-DANet: Dynamic Architecture Network for Efficient Medical Volumetric
  Segmentation
Med-DANet: Dynamic Architecture Network for Efficient Medical Volumetric SegmentationEuropean Conference on Computer Vision (ECCV), 2022
Wenxuan Wang
Chen Chen
Jing Wang
Sen Zha
Yan Zhang
Jiangyun Li
MedIm
298
13
0
14 Jun 2022
TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of
  Medical Images
TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of Medical Images
Jiangyun Li
Wenxuan Wang
Chen Chen
Tianxiang Zhang
Sen Zha
Jing Wang
Hong Yu
ViTMedIm
410
32
0
30 Jan 2022
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in
  Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking
  Results
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta
Angelos Filos
Ujjwal Baid
C. Sako
Richard McKinley
...
Christos Davatzikos
Bjoern Menze
Spyridon Bakas
Y. Gal
Tal Arbel
UQCV
308
70
0
19 Dec 2021
A Data-Adaptive Loss Function for Incomplete Data and Incremental
  Learning in Semantic Image Segmentation
A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image SegmentationIEEE Transactions on Medical Imaging (IEEE TMI), 2021
Minh H. Vu
Gabriella Norman
T. Nyholm
Tommy Löfstedt
MedImOOD
178
18
0
22 Apr 2021
1
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