ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2410.15360
  4. Cited By
Improving 3D Medical Image Segmentation at Boundary Regions using Local
  Self-attention and Global Volume Mixing

Improving 3D Medical Image Segmentation at Boundary Regions using Local Self-attention and Global Volume Mixing

20 October 2024
Daniya Najiha Abdul Kareem
M. Fiaz
Noa Novershtern
Jacob Hanna
Hisham Cholakkal
ArXivPDFHTML

Papers citing "Improving 3D Medical Image Segmentation at Boundary Regions using Local Self-attention and Global Volume Mixing"

4 / 4 papers shown
Title
MISSFormer: An Effective Medical Image Segmentation Transformer
MISSFormer: An Effective Medical Image Segmentation Transformer
Xiaohong Huang
Zhifang Deng
Dandan Li
Xueguang Yuan
ViT
MedIm
87
168
0
15 Sep 2021
MLP-Mixer: An all-MLP Architecture for Vision
MLP-Mixer: An all-MLP Architecture for Vision
Ilya O. Tolstikhin
N. Houlsby
Alexander Kolesnikov
Lucas Beyer
Xiaohua Zhai
...
Andreas Steiner
Daniel Keysers
Jakob Uszkoreit
Mario Lucic
Alexey Dosovitskiy
239
2,554
0
04 May 2021
Convolution-Free Medical Image Segmentation using Transformers
Convolution-Free Medical Image Segmentation using Transformers
Davood Karimi
Serge Vasylechko
Ali Gholipour
ViT
MedIm
84
121
0
26 Feb 2021
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
1