Search Results for author:
Found 3 papers, 2 papers with code
A Recent Survey of Vision Transformers for Medical Image Segmentation
This survey paper provides a detailed review of the recent advancements in ViTs and HVTs for medical image segmentation.
MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation
Recently, Transformers have gained popularity in the computer vision community and also in medical image segmentation due to their ability to process global features effectively.
Ranked #1 on
Medical Image Segmentation
on MoNuSAC
Detection of Tumour Infiltrating Lymphocytes in CD3 and CD8 Stained Histopathological Images using a Two-Phase Deep CNN
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.
