TuNet: End-to-end Hierarchical Brain Tumor Segmentation using Cascaded Networks

11 October 2019

Papers citing "TuNet: End-to-end Hierarchical Brain Tumor Segmentation using Cascaded Networks"

9 / 9 papers shown

Title
Using Synthetic Images to Augment Small Medical Image Datasets Minh H. Vu L. Tronchin T. Nyholm Tommy Löfstedt MedIm 34 0 0 02 Mar 2025
Deep Neural Patchworks: Coping with Large Segmentation Tasks M. Reisert M. Russe S. Elsheikh E. Kellner Henrik Skibbe 6 8 0 07 Jun 2022
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 ViT MedIm 26 25 0 30 Jan 2022
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 H. Menze Spyridon Bakas Y. Gal Tal Arbel UQCV 22 44 0 19 Dec 2021
A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation Minh H. Vu Gabriella Norman T. Nyholm Tommy Löfstedt MedIm OOD 24 14 0 22 Apr 2021
Spatially Varying Label Smoothing: Capturing Uncertainty from Expert Annotations Mobarakol Islam Ben Glocker UQCV 13 45 0 12 Apr 2021
Multi-Decoder Networks with Multi-Denoising Inputs for Tumor Segmentation Minh H. Vu T. Nyholm Tommy Löfstedt MedIm 22 18 0 16 Nov 2020
Deep Learning Based Brain Tumor Segmentation: A Survey Zhihua Liu Lei Tong Zheheng Jiang Long Chen Feixiang Zhou Qianni Zhang Xiangrong Zhang Ling Li Huiyu Zhou 3DV 24 228 0 18 Jul 2020
Evaluation of Multi-Slice Inputs to Convolutional Neural Networks for Medical Image Segmentation Minh H. Vu G. Grimbergen T. Nyholm Tommy Löfstedt SSeg 31 31 0 19 Dec 2019