4 citations · 10 across the 5 of their papers we have counts for
5 papers
TPMIL: Trainable Prototype Enhanced Multiple Instance Learning for Whole Slide Image Classification
Litao Yang, Deval Mehta, Sidong Liu +3
Digital pathology based on whole slide images (WSIs) plays a key role in cancer diagnosis and clinical practice. Due to the high resolution of the WSI and the unavailability of pat…
Towards Trustable Skin Cancer Diagnosis via Rewriting Model's Decision
Siyuan Yan, Zhen Yu, Xuelin Zhang +5
Deep neural networks have demonstrated promising performance on image recognition tasks. However, they may heavily rely on confounding factors, using irrelevant artifacts or bias w…
Leukocyte Classification using Multimodal Architecture Enhanced by Knowledge Distillation
Litao Yang, Deval Mehta, Dwarikanath Mahapatra +1
Recently, a lot of automated white blood cells (WBC) or leukocyte classification techniques have been developed. However, all of these methods only utilize a single modality micros…
Improved Super Resolution of MR Images Using CNNs and Vision Transformers
Dwarikanath Mahapatra
State of the art magnetic resonance (MR) image super-resolution methods (ISR) using convolutional neural networks (CNNs) leverage limited contextual information due to the limited…
Unsupervised Domain Adaptation Using Feature Disentanglement And GCNs For Medical Image Classification
Dwarikanath Mahapatra
The success of deep learning has set new benchmarks for many medical image analysis tasks. However, deep models often fail to generalize in the presence of distribution shifts betw…