Deep learning (DL) algorithms have rapidly become a robust tool for analyzing medical
images. They have been used extensively for medical image segmentation as the first and …

Artificial intelligence is highly regarded as the most promising future technology that will
have a great impact on healthcare across all specialties. Its subsets, machine learning, deep …

Bladder cancer (BCa) is the most common malignancy of the urinary tract and the most
expensive malignancy to treat over the patients' lifetime. In recent years a number of studies …

Background and purpose Delineation of organs at risk (OARs), such as the bladder, rectum
and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target …

Rapid technological advancements in artificial intelligence (AI) methods have fueled
explosive growth in decision tools being marketed by a rapidly growing number of …

This study explores the potential of the VGG-16 architecture, a Convolutional Neural
Network (CNN) model, for accurate brain tumor detection through deep learning. Utilizing a …

Purpose The application of automated image analyses could improve and facilitate
standardization and consistency of quantification in [18F] DCFPyL (PSMA) PET/CT scans. In …

The recent rise of deep learning (DL) and its promising capabilities in capturing non-explicit
detail from large datasets have attracted substantial research attention in the field of medical …

Purpose The alarming increase in diseases of urinary system is a cause of concern for the
populace and health experts. The traditional techniques used for the diagnosis of these …

Precise determination and assessment of bladder cancer (BC) extent of muscle invasion
involvement guides proper risk stratification and personalized therapy selection. In this …