The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …

Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …

Background Non-contrast head CT scan is the current standard for initial imaging of patients
with head trauma or stroke symptoms. We aimed to develop and validate a set of deep …

Purpose To develop and validate a deep learning–based automatic detection algorithm
(DLAD) for malignant pulmonary nodules on chest radiographs and to compare its …

Medical imaging plays a critical role in various clinical applications. However, due to
multiple considerations such as cost and radiation dose, the acquisition of certain image …

Advances in biological and medical technologies have been providing us explosive
volumes of biological and physiological data, such as medical images …

This review covers computer-assisted analysis of images in the field of medical imaging.
Recent advances in machine learning, especially with regard to deep learning, are hel** …

In order to reduce the potential radiation risk, low-dose CT has attracted an increasing
attention. However, simply lowering the radiation dose will significantly degrade the image …

With time, AI technologies have matured well and resonated in various domains of applied
sciences and engineering. The sub-domains of AI, machine learning (ML), deep learning …

For the last decade, it has been shown that neuroimaging can be a potential tool for the
diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment …