Abstract Machine learning, and especially deep learning, is rapidly gaining acceptance and
clinical usage in a wide range of image analysis applications and is regarded as providing …

Motivation Large-scale neuronal morphologies are essential to neuronal ty**, connectivity
characterization and brain modeling. It is widely accepted that automation is critical to the …

Objective. Low-dose computed tomography (LDCT) denoising is an important problem in CT
research. Compared to the normal dose CT, LDCT images are subjected to severe noise …

Atopic dermatitis (AD) is a common skin disease in childhood whose diagnosis requires
expertise in dermatology. Recent studies have indicated that host genes–microbial …

The interest in artificial intelligence (AI) has ballooned within radiology in the past few years
primarily due to notable successes of deep learning. With the advances brought by deep …

Segmentation is the essential requirement in automated computer-aided diagnosis (CAD) of
skin diseases. In this paper, we propose an unsupervised skin lesion segmentation method …

There is a growing interest in examining the wealth of data generated by fusing functional
and structural imaging information sources. These approaches may have clinical utility in …

Vitiligo, alopecia areata, atopic, and stasis dermatitis are common skin conditions that pose
diagnostic and assessment challenges. Skin image analysis is a promising noninvasive …

Attention-deficit/hyperactivity disorder (ADHD) is a complex neurodevelopmental disorder
characterized by symptoms such as inattention, hyperactivity, and impulsivity. Early and …

Conclusion In this editorial, we briefly introduce thirteen exciting machine learning-based
papers selected for this Special Issue. We hope that these timely scholarly works could …