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 has rapidly advanced in various fields within the past few years and has
recently gained particular attention in the radiology community. This article provides an …

Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …

The advent of deep learning has brought great change to the community of computer
science and also revitalized numerous fields where traditional machine learning methods …

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

The use of machine learning (ML) has been increasing rapidly in the medical imaging field,
including computer-aided diagnosis (CAD), radiomics, and medical image analysis …

The health care sector is totally different from any other industry. It is a high priority sector
and consumers expect the highest level of care and services regardless of cost. The health …

Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …

Fruit category identification is important in factories, supermarkets, and other fields. Current
computer vision systems used handcrafted features, and did not get good results. In this …

The primary objective of this paper is to build classification models and strategies to identify
breathing sound anomalies (wheeze, crackle) for automated diagnosis of respiratory and …