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论文Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review
:fire::fire:This is a collection of awesome articles about Transformer models in medical imaging :fire::fire:
:loudspeaker: Our review paper published on MedIA: Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review :heart:
:loudspeaker: Our review paper published on arXiv: Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review :heart:
Citation
@article{azad2023advances,
title={Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review},
author={Azad, Reza and Kazerouni, Amirhossein and Heidari, Moein and Aghdam, Ehsan Khodapanah and Molaei, Amirali and Jia, Yiwei and Jose, Abin and Roy, Rijo and Merhof, Dorit},
journal={Medical Image Analysis},
volume = {91},
pages={103000},
year={2024},
issn = {1361-8415},
publisher={Elsevier}
}
Contents
Taxonomy
Papers
Image Classification
HATNet: An End-to-End Holistic Attention Network for Diagnosis of Breast Biopsy Images
Sachin Mehta, Ximing Lu, Donald Weaver, Joann G. Elmore, Hannaneh Hajishirzi, Linda Shapiro
[25th Jul, 2020] [MedIA Journal, 2022]
[PDF] [GitHub]
A graph-transformer for whole slide image classification
Yi Zheng, Rushin H. Gindra, Emily J. Green, Eric J. Burks, Margrit Betke, Jennifer E. Beane, Vijaya B. Kolachalama
[19th May, 2022] [TMI Journal, 2022]
[PDF] [GitHub]
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-guided Disease Classification
Moinak Bhattacharya, Shubham Jain, Prateek Prasanna
[23rd Feb., 2022] [ECCV, 2022]
[PDF]
Federated Split Vision Transformer for COVID-19 CXR Diagnosis using Task-Agnostic Training
Sangjoon Park, Gwanghyun Kim, Jeongsol Kim, Boah Kim, Jong Chul Ye
[2nd Nov., 2021] [NeurIPS, 2021]
[PDF]
Vision transformer for classification of breast ultrasound images
Behnaz Gheflati, Hassan Rivaz
[27th Oct., 2021] [EMBC, 2022]
[PDF]
MIL-VT: Multiple Instance Learning Enhanced Vision Transformer for Fundus Image Classification
Shuang Yu, Kai Ma, Qi Bi, Cheng Bian, Munan Ning, Nanjun He, Yuexiang Li, Hanruo Liu, Yefeng Zheng
[21st Sep., 2021] [MICCAI, 2021]
[PDF] [GitHub]
3DMeT: 3D Medical Image Transformer for Knee Cartilage Defect Assessment
Sheng Wang, Zixu Zhuang, Kai Xuan, Dahong Qian, Zhong Xue, Jia Xu, Ying Liu, Yiming Chai, Lichi Zhang, Qian Wang, Dinggang Shen
[21st Sep., 2021] [MICCAI Workshop, 2021]
[PDF]
COVID-Transformer: Interpretable COVID-19 Detection Using Vision Transformer for Healthcare
Debaditya Shome, T. Kar, Sachi Nandan Mohanty, Prayag Tiwari, Khan Muhammad, Abdullah AlTameem, Yazhou Zhang, Abdul Khader Jilani Saudagar
[23rd Sep., 2021] [International Journal of Environmental Research and Public Health, 2021]
[PDF] [GitHub]
Is it Time to Replace CNNs with Transformers for Medical Images?
Christos Matsoukas, Johan Fredin Haslum, Magnus Söderberg, Kevin Smith
[20th Aug., 2021] [ICCV Workshop, 2021]
[PDF] [GitHub]
Vision Transformer for femur fracture classification
Leonardo Tanzi, Andrea Audisio, Giansalvo Cirrincione, Alessandro Aprato, Enrico Vezzetti
[7th Aug., 2021] [Injury Journal, 2022]
[PDF]
xViTCOS: Explainable Vision Transformer Based COVID-19 Screening Using Radiography
Arnab Kumar Mondal, Arnab Bhattacharjee, Parag Singla, A. P. Prathosh
[7th Jul., 2021] [IEEE Journal of Translational Engineering in Health and Medicine, 2021]
[PDF] [Github]
COVID-VIT: Classification of COVID-19 from CT chest images based on vision transformer models
Xiaohong Gao, Yu Qian, Alice Gao
[4th Jul., 2021] [NextComp, 2022]
[PDF] [GitHub]
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification
Zhuchen Shao, Hao Bian, Yang Chen, Yifeng Wang, Jian Zhang, Xiangyang Ji, Yongbing Zhang
[2nd Jun., 2021] [NeurIPS, 2021]
[PDF] [GitHub]
Lesion-Aware Transformers for Diabetic Retinopathy Grading
Rui Sun, Yihao Li, Tianzhu Zhang, Zhendong Mao, Feng Wu, Yongdong Zhang
[1st Jun., 2021] [CVPR, 2021]
[PDF]
POCFormer: A Lightweight Transformer Architecture for Detection of COVID-19 Using Point of Care Ultrasound
Shehan Perera, Srikar Adhikari, Alper Yilmaz
[20th May, 2021] [ICIP, 2022]
[PDF]
Automatic diagnosis of covid-19 using a tailored transformer-like network
Chengeng Liu, Qingshan Yin
[21st Apr., 2021] [CISAT, 2021]
[PDF]
Vision Transformer for COVID-19 CXR Diagnosis using Chest X-ray Feature Corpus
Sangjoon Park, Gwanghyun Kim, Yujin Oh, Joon Beom Seo, Sang Min Lee, Jin Hwan Kim, Sungjun Moon, Jae-Kwang Lim, Jong Chul Ye
[12th Mar., 2021] [arXiv, 2021]
[PDF]
TransMed: Transformers Advance Multi-modal Medical Image Classification
Yin Dai, Yifan Gao
[10th Mar., 2021] [Diagnostics, 2021]
[PDF]
Image Segmentation
TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation
Reza Azad, Moein Heidari, Moein Shariatnia, Ehsan Khodapanah Aghdam, Sanaz Karimijafarbigloo, Ehsan Adeli, Dorit Merhof
[1st Aug., 2022] [MICCAI Workshop, 2022]
[PDF] [GitHub]
HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentation
Moein Heidari, Amirhossein Kazerouni, Milad Soltany, Reza Azad, Ehsan Khodapanah, Aghdam Julien Cohen-Adad, Dorit Merhof
[18th Jul., 2022] [WACV, 2023]
[PDF] [GitHub]
Self Pre-training with Masked Autoencoders for Medical Image Analysis
Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna
[10th Mar., 2022] [arXiv, 2022]
[PDF]
Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
Ali Hatamizadeh, Vishwesh Nath, Yucheng Tang, Dong Yang, Holger Roth, Daguang Xu
[4th Jan., 2022] [MICCAI Workshop]
[PDF] [GitHub]
Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer
Xiangde Luo, Minhao Hu, Tao Song, Guotai Wang, Shaoting Zhang
[9th Dec., 2021] [MIDL, 2022]
[PDF] [Github]
T-AutoML: Automated Machine Learning for Lesion Segmentation using Transformers in 3D Medical Imaging
Dong Yang, Andriy Myronenko, Xiaosong Wang, Ziyue Xu, Holger R. Roth, Daguang Xu
[15th Nov., 2021] [ICCV, 2021]
[PDF]
MISSFormer: An Effective Medical Image Segmentation Transformer
Xiaohong Huang, Zhifang Deng, Dandan Li, Xueguang Yuan
[15th Sep., 2021] [TMI Journal, 2022]
[PDF] [GitHub]
nnFormer: Interleaved Transformer for Volumetric Segmentation
Hong-Yu Zhou, Jiansen Guo, Yinghao Zhang, Lequan Yu, Liansheng Wang, Yizhou Yu
[7th Sep., 2021] [arXiv, 2021]
[PDF] [GitHub]
Medical Image Segmentation Using Squeeze-and-Expansion Transformers
Shaohua Li, Xiuchao Sui, Xiangde Luo, Xinxing Xu, Yong Liu, Rick Goh
[20th May, 2021] [IJCAI, 2021]
[PDF] [GitHub]
Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation
Hu Cao, Yueyue Wang, Joy Chen, Dongsheng Jiang, Xiaopeng Zhang, Qi Tian, Manning Wang
[12th May, 2021] [arXiv, 2021]
[PDF] [GitHub]
UNETR: Transformers for 3D Medical Image Segmentation
Ali Hatamizadeh, Yucheng Tang, Vishwesh Nath, Dong Yang, Andriy Myronenko, Bennett Landman, Holger Roth, Daguang Xu
[18th Mar., 2021] [WACV, 2022]
[PDF] [GitHub]
TransBTS: Multimodal Brain Tumor Segmentation Using Transformer
Jiangyun Li, Wenxuan Wang, Chen Chen, Tianxiang Zhang, Sen Zha, Hong Yu, Jing Wang
[7th Mar, 2021] [MICCAI, 2021]
[PDF] [GitHub]
CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation
Yutong Xie, Jianpeng Zhang, Chunhua Shen, Yong Xia
[4th Mar., 2021] [MICCAI, 2021]
[PDF] [GitHub]
Medical Transformer: Gated Axial-Attention for Medical Image Segmentation
Jeya Maria Jose Valanarasu, Poojan Oza, Ilker Hacihaliloglu, Vishal M. Patel
[21th Feb., 2021] [MICCAI, 2021]
[PDF] [GitHub]
TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation
*Yundong Zhang, Huiye Liu, Qiang
