no code implementations • 1 Dec 2023 • Asifullah Khan, Zunaira Rauf, Abdul Rehman Khan, Saima Rathore, Saddam Hussain Khan, Sahar Shah, Umair Farooq, Hifsa Asif, Aqsa Asif, Umme Zahoora, Rafi Ullah Khalil, Suleman Qamar, Umme Hani Asif, Faiza Babar Khan, Abdul Majid, Jeonghwan Gwak
This survey paper provides a detailed review of the recent advancements in ViTs and HVTs for medical image segmentation.
This survey presents a taxonomy of the recent vision transformer architectures and more specifically that of the hybrid vision transformers.
To address this issue, we propose a Channel Boosted Hybrid Vision Transformer (CB HVT) that uses transfer learning to generate boosted channels and employs both transformers and CNNs to analyse lymphocytes in histopathological images.
Results: The empirical evaluation on samples from LYSTO dataset shows that the proposed LSTAM-Net can learn variations in the images and precisely remove the hard negative stain artifacts with an F-score of 0. 74.