09/30/2021 |
Yunxiang Li |
GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation |
X-ray & Fundus |
2D |
PyTorch |
MLMI 2021 ![arXiv](https://camo.githubusercontent.com/9126f8842d566c2e921ed049387f95023706d2dbb6f04ddfcea65860dd003502/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130392e31343831332d6233316231622e737667) |
09/15/2021 |
Xiaohong Huang |
MISSFormer: An Effective Medical Image Segmentation Transformer |
CT |
2D |
N/A |
![arXiv](https://camo.githubusercontent.com/00fa1d28e9e44cb2086be3f4eb4cd65782309a3e2ebb1ca10114dadd9552e9f3/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130392e30373136322d6233316231622e737667) |
09/07/2021 |
Hong-Yu Zhou |
nnFormer: Interleaved Transformer for Volumetric Segmentation |
CT |
3D |
PyTorch |
![arXiv](https://camo.githubusercontent.com/5b70e7151e542fb81b1482a0e14176c817ea3d537c187e075d992638436aeb59/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130392e30333230312d6233316231622e737667) |
07/28/2021 |
Madeleine K. Wyburd |
TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations |
MRI |
2D |
PyTorch |
MICCAI 2021 ![arXiv](https://camo.githubusercontent.com/206a7ed3b850f66e1104e116bba9fc196e4e59deb0261e48f5c50862f9d502cc/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130372e31333534322d6233316231622e737667) |
07/19/2021 |
Guoping Xu |
LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation |
CT |
2D |
N/A |
![arXiv](https://camo.githubusercontent.com/b4c6255251cd9577043542e09e28213a3af7bdcd11ec13bb37632075cceb1ddc/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130372e30383632332d6233316231622e737667) |
07/12/2021 |
Bingzhi Chen |
TransAttUnet: Multi-level Attention-guided U-Net with Transformer for Medical Image Segmentation |
X-ray & CT ... |
2D |
N/A |
![arXiv](https://camo.githubusercontent.com/db159b82e52bd08abb77952199770f094976a4feaa14b7edee71403187227691/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130372e30353237342d6233316231622e737667) |
07/12/2021 |
Chang Yao |
TransClaw U-Net: Claw U-Net with Transformers for Medical Image Segmentation |
CT |
2D |
N/A |
![arXiv](https://camo.githubusercontent.com/4b19b5def01bd46950783662fca2825d893f793ed8ac8392d2358c44bf6bea4b/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130372e30353138382d6233316231622e737667) |
07/02/2021 |
Yunhe Gao |
UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation |
CT |
2D |
PyTorch (unofficial) |
MICCAI 2021 ![arXiv](https://camo.githubusercontent.com/fbf6a2b17ee295162aaf028cc4db797bfbf290d77da265cf0e2aebe836b0d734/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130372e30303738312d6233316231622e737667) |
06/28/2021 |
Yuanfeng Ji |
Multi-Compound Transformer for Accurate Biomedical Image Segmentation |
Colonoscopy & Pathology ... |
2D |
PyTorch |
MICCAI 2021 ![arXiv](https://camo.githubusercontent.com/62dec69101cb58a264000685448f5134c82f5185eef5d5fea6acd9c47fae1163/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130362e31343338352d6233316231622e737667) |
06/12/2021 |
Ailiang Lin |
DS-TransUNet: Dual Swin Transformer U-Net for Medical Image Segmentation |
Colonoscopy & Histology ... |
2D |
N/A |
![arXiv](https://camo.githubusercontent.com/573226172c638bae4b8919f6c589a49f88fe40ccb263c42d784d3eccf823732c/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130362e30363731362d6233316231622e737667) |
06/02/2021 |
Shaohua Li |
Medical Image Segmentation Using Squeeze-and-Expansion Transformers |
Fundus & Colonoscopy & MRI |
2D & 3D |
PyTorch |
IJCAI 2021 ![arXiv](https://camo.githubusercontent.com/3ee611fa6e42c2fcd4ec7d7de468a2222f5aaf89f0ba633d010d5ccf6a1c5edf/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130352e30393531312d6233316231622e737667) |
05/12/2021 |
Hu Cao |
Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation |
CT |
2D |
PyTorch |
![arXiv](https://camo.githubusercontent.com/4c66c39caec0734c7aa8aad82087b7c01e5b4de71456c1ca94b3fbb53644b604/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130352e30353533372d6233316231622e737667) |
04/29/2021 |
Zhuangzhuang Zhang |
Pyramid Medical Transformer for Medical Image Segmentation |
Microscopic |
2D |
N/A |
![arXiv](https://camo.githubusercontent.com/65b6df05de967583c50215102a0c528d709caff3464667a138700e1a79c117af/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130342e31343730322d6233316231622e737667) |
04/28/2021 |
Eunji Jun |
Medical Transformer: Universal Brain Encoder for 3D MRI Analysis |
MRI |
3D |
N/A |
![arXiv](https://camo.githubusercontent.com/24b9cc9ba20ec3ba11c0156e3f1e9f5674a608a0c4c1434c782fe81c3c425071/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130342e31333633332d6233316231622e737667) |
03/18/2021 |
Ali Hatamizadeh |
UNETR: Transformers for 3D Medical Image Segmentation |
CT & MRI |
3D |
PyTorch |
![arXiv](https://camo.githubusercontent.com/d224260abebf8bcf6cbd91bb451edb109649672630c9a1746c0e766acecad7ad/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130332e31303530342d6233316231622e737667) |
03/10/2021 |
Olivier Petit |
U-Net Transformer: Self and Cross Attention for Medical Image Segmentation |
CT |
2D |
N/A |
![arXiv](https://camo.githubusercontent.com/c230a1cb8e7b40aed336513349dd1163f9f0780d39f7fd1f8704c6a4a5275077/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130332e30363130342d6233316231622e737667) |
03/07/2021 |
Wenxuan Wang |
TransBTS: Multimodal Brain Tumor Segmentation Using Transformer |
MRI |
3D |
PyTorch |
MICCAI 2021 ![arXiv](https://camo.githubusercontent.com/2d0662a2744b866949120de7a48536dc413e3b1d9d45e4812fb5112f60837cd1/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130332e30343433302d6233316231622e737667) |
03/05/2021 |
Boxiang Yun |
SpecTr: Spectral Transformer for Hyperspectral Pathology Image Segmentation |
HSI |
3D |
PyTorch |
![arXiv](https://camo.githubusercontent.com/598e573f77ce85a0eb305c41ba24000c111ad5c548db8d4e375975b9ab5342e4/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130332e30333630342d6233316231622e737667) |
03/04/2021 |
Yutong Xie |
CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation |
CT |
3D |
PyTorch |
MICCAI 2021![arXiv](https://camo.githubusercontent.com/4aee1deaa83f62d0742eae5653f401e9ea07deef606a855f841b65e07423081b/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130332e30333032342d6233316231622e737667) |
02/26/2021 |
Davood Karimi |
Convolution-Free Medical Image Segmentation using Transformers |
CT & MRI |
3D |
N/A |
![arXiv](https://camo.githubusercontent.com/3ed61749eb4e8e79aa43956e20421b40b40f759de2ac8ae91ae3a534a080c628/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130322e31333634352d6233316231622e737667) |
02/21/2021 |
Jeya Maria Jose Valanarasu |
Medical Transformer: Gated Axial-Attention for Medical Image Segmentation |
Ultrasound & Microscopic |
2D |
PyTorch |
![arXiv](https://camo.githubusercontent.com/0dfff64737177df7e63a254418f36b3259f00a3d5522480196a7eb7f063c9f29/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130322e31303636322d6233316231622e737667) |
02/16/2021 |
Yundong Zhang |
TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation |
Colonoscopy |
2D |
N/A |
![arXiv](https://camo.githubusercontent.com/dbea7eaf2191ac59db342d5c497ea869df4abff0767c94249c7fb788606a8bf8/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130322e30383030352d6233316231622e737667) |
02/08/2021 |
Jieneng Chen |
TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation |
CT & MRI |
2D |
PyTorch |
![arXiv](https://camo.githubusercontent.com/1011712f7c7861bc80c40fc607e09637931f7812b54f5dc8b00a3e38a0fac2af/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f61725869762d323130322e30343330362d6233316231622e737667) |