The Lighter The Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning

29 June 2022

Papers citing "The Lighter The Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning"

8 / 8 papers shown

Title
Sauron U-Net: Simple automated redundancy elimination in medical image segmentation via filter pruning Juan Miguel Valverde Artem Shatillo Jussi Tohka AAML 13 5 0 27 Sep 2022
Boundary-aware Transformers for Skin Lesion Segmentation Jiacheng Wang Lan Wei Liansheng Wang Qichao Zhou Lei Zhu Jing Qin ViT MedIm 72 128 0 08 Oct 2021
MISSFormer: An Effective Medical Image Segmentation Transformer Xiaohong Huang Zhifang Deng Dandan Li Xueguang Yuan ViT MedIm 87 172 0 15 Sep 2021
TransAttUnet: Multi-level Attention-guided U-Net with Transformer for Medical Image Segmentation Bingzhi Chen Yishu Liu Zheng-Wei Zhang Guangming Lu A. W. Kong MedIm ViT 101 208 0 12 Jul 2021
TransClaw U-Net: Claw U-Net with Transformers for Medical Image Segmentation Yao Chang Menghan Hu Zhai Guangtao Xiao-Ping Zhang MedIm ViT 68 96 0 12 Jul 2021
Convolution-Free Medical Image Segmentation using Transformers Davood Karimi Serge Vasylechko Ali Gholipour ViT MedIm 84 121 0 26 Feb 2021
TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation Yundong Zhang Huiye Liu Qiang Hu ViT MedIm 198 890 0 16 Feb 2021
Bottleneck Transformers for Visual Recognition A. Srinivas Tsung-Yi Lin Niki Parmar Jonathon Shlens Pieter Abbeel Ashish Vaswani SLR 270 979 0 27 Jan 2021