The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …

Multiple instance learning (MIL) is a powerful tool to solve the weakly supervised
classification in whole slide image (WSI) based pathology diagnosis. However, the current …

Neural Networks require large amounts of memory and compute to process high resolution
images, even when only a small part of the image is actually informative for the task at hand …

Histopathology image analysis plays an important role in the treatment and diagnosis of
cancer. However, analysis of whole slide images (WSI) with deep learning is challenging …

Computerized identification of lymph node metastasis of breast cancer (BCLNM) from whole-
slide pathological images (WSIs) can largely benefit therapy decision and prognosis …

Colorectal Cancer (CRC) is one of the most common cancer diagnosed in humans.
Outcomes vary significantly among patients with different tumor status. Accurate staging of …

Abstract Background and Objective Whole slide image (WSI) classification and lesion
localization within giga-pixel slide are challenging tasks in computational pathology that …

The classification of gigapixel histopathology images with deep multiple instance learning
models has become a critical task in digital pathology and precision medicine. In this work …

Background Deep learning has revolutionized digital pathology, allowing automatic analysis
of hematoxylin and eosin (H&E) stained whole slide images (WSIs) for diverse tasks. WSIs …