Medical image analysis has a long and distinguished history spanning nearly six decades. As a matter of fact, the evolution of the general field of image analysis largely parallels that of medical image analysis as some of the earliest image analysis techniques were developed in the context of medical applications. Image analysis in general, and medical image analysis in particular, have historically focused on single-channel (monochromatic) images. A notable exception is dermatology, a subfield of medicine where images are typically acquired in color. While color provides enhanced visualization of surface and subsurface structures of the skin, it also presents new challenges for researchers and practitioners as the numerous methods developed for single-channel images are generally inapplicable to multichannel images. In addition, there are remarkable visual similarities among skin diseases, and compared to other medical imaging domains, varying genetics, disease states, imaging equipment, and imaging conditions can significantly alter the appearance of the skin, making automated analysis in this domain highly challenging. This MIA special issue aims to collect state-of-the-art research findings in the field of dermatological image analysis. We are interested in contributions involving a wide a variety of modalities including, but not limited to, clinical photography, dermoscopy, total-body photography, ultrasonography, computed tomography, positron emission tomography, optical coherence tomography, confocal microscopy, infrared imaging, thermal imaging, multispectral imaging, and hyperspectral imaging.

This special issue aims to cover all aspects of dermatological image analysis. Topics of interest include, but are not limited to:

+ Enhancement
+ Registration
+ Segmentation
+ Feature Extraction
+ Content-Based Retrieval
+ Synthetic Image Generation
+ Classification
+ Visualization

Paper Submission