Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is
nowadays considered as a core technology of today's Fourth Industrial Revolution (4IR or …

Background Prostate cancer is one of the most common cancers worldwide. Currently,
convolution neural networks (CNNs) are achieving remarkable success in various computer …

Background: Noncontrast CT (NCCT) relies on labor-intensive examinations of CT slices to
identify urolithiasis in the urinary tract, and, despite the use of deep-learning algorithms …

Background Liver segmentation in computed tomography (CT) imaging has been widely
investigated as a crucial step for analyzing liver characteristics and diagnosing liver …

Computed Tomography (CT) imaging is used in Radiation Therapy planning, where the
treatment is carefully tailored to each patient in order to maximize radiation dose to the target …

We aim to optimize the binary detection of Chronic Obstructive Pulmonary Disease (COPD)
based on emphysema presence in the lung with convolutional neural networks (CNN) by …

Objective In this study, we investigate whether a Convolutional Neural Network (CNN) can
generate informative parametric maps from the pre-processed CT perfusion data in patients …

Deep learning has the potential to revolutionize medical practice by automating and
performing important tasks like detecting and delineating the size and locations of cancers in …

Despite considerable strides in developing deep learning models for 3D medical image
segmentation, the challenge of effectively generalizing across diverse image distributions …

This research paper introduces a comprehensive methodology aimed at enhancing the
accuracy of liver cancer tumor identification in ultrasound images through the utilization of a …