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 …

Introduction. The early detection and diagnosis of COVID‐19 and the accurate separation of
non‐COVID‐19 cases at the lowest cost and in the early stages of the disease are among …

Neurodegenerative disorders, such as Alzheimer's disease, are associated with changes in
multiple neuroimaging and biological measures. These may provide complementary …

Recently, medical image registration and fusion processes are considered as a valuable
assistant for the medical experts. The role of these processes arises from their ability to help …

Recent improvements in deep learning radiomics (DLR) extracting high-level features form
medical imaging could promote the performance of computer aided diagnosis (CAD) for …

Background Real-time analysis of patient data during medical procedures can provide vital
diagnostic feedback that significantly improves chances of success. With sensors becoming …

Leveraging available annotated data is an essential component of many modern methods
for medical image analysis. In particular, approaches making use of the “neighbourhood” …

Recently, a machine learning (ML) area called deep learning emerged in the computer-
vision field and became very popular in many fields. It started from an event in late 2012 …

Open Problems in Spectral Dimensionality Reduction Page 1 SPRINGER BRIEFS IN
COMPUTER SCIENCE Harry Strange Reyer Zwiggelaar Open Problems in Spectral …

Coarctation of aorta (CoA) is a critical congenital heart defect (CCHD) that requires accurate
and immediate diagnosis and treatment. Current newborn screening methods to detect CoA …