Digital pathology has enabled us to capture, store, query and analyze scanned biopsy
samples as digital images. The widespread adoption of digital pathology has spurred the …

Cancer refers to a group of diseases characterized by an uncontrolled proliferation of cells
with underlying genetic mutations that can be arranged in solid masses forming tumors. The …

Modeling the sequential information of image sequences has been a vital step of various
vision tasks and convolutional long short-term memory (ConvLSTM) has demonstrated its …

Given the recent success of artificial intelligence (AI) in computer vision applications, many
pathologists anticipate that AI will be able to assist them in a variety of digital pathology …

Multiple Sclerosis (MS) is a demyelinating disease of the central nervous system which
affects nearly 1 million people in the US. Magnetic resonance imaging (MRI), as the most …

UNeXt is a leading medical image segmentation method that employs convolutional and
multi-layer perceptron (MLP) structure for its segmentation network. It outperforms other …

Diagnosis of various pancreatic lesions in CT images is a challenging task owing to a
significant overlap in their imaging appearance. An accurate diagnosis of pancreatic lesions …

This paper aims at bridging the gap between feature selection and feature space size by
utilizing both square and non-square self-organizing maps under different configuration …

Objective: This study aimed to study the gender differences of healthy adults' brains using
resting-state functional magnetic resonance (rs-fMRI). Methods: Forty-four (44) healthy …

The shift towards end-to-end deep learning has brought unprecedented advances in many
areas of computer vision. However, there are cases where the input images are excessively …