Computer‐aided diagnosis (CAD) has been a major field of research for the past few
decades. CAD uses machine learning methods to analyze imaging and/or nonimaging …

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 …

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

In medical imaging, segmentation plays a vital role towards the interpretation of X-ray
images where salient features are extracted with the help of image segmentation. Without …

Skin cancer affects the lives of millions of people every year, as it is considered the most
popular form of cancer. In the USA alone, approximately three and a half million people are …

Machine learning is a technique for recognizing patterns that can be applied to medical
images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be …

Training a deep convolutional neural network (CNN) from scratch is difficult because it
requires a large amount of labeled training data and a great deal of expertise to ensure …

The papers in this special section focus on the technology and applications supported by
deep learning. Deep learning is a growing trend in general data analysis and has been …

Deep learning is the state-of-the-art machine learning approach. The success of deep
learning in many pattern recognition applications has brought excitement and high …

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 …