Dear Colleagues,

Research on computer analysis of medical images holds great potential for enhancing the health of patients. However, a number of systematic obstacles are impeding the field’s advancement, including data limitations, such as biases, and research incentives, such as optimization for publication. Medical imaging plays a significant role in different clinical applications, such as medical procedures used for early detection, monitoring, diagnosis, and treatment evaluation of various medical conditions. The basics of the principles and implementations of artificial neural networks and deep learning are essential for understanding medical image analysis in computer vision. The deep learning approach (DLA) in medical image analysis has emerged as a fast-growing research field. Deep learning has recently revolutionized medical image computing methods by automating the discovery of features and producing superior results. Recent developments in deep learning have heightened the importance of biomedical signal and image processing research. In order to provide clinicians with useful information, biomedical signal processing requires the analysis of measurements taken at specific points in time and recorded in a patient’s chart. Biomedical image processing is conceptually similar to biomedical signal processing in multiple dimensions. Using X-ray, ultrasound, MRI, nuclear medicine, and visual imaging technologies, it involves image analysis, enhancement, and presentation.

In response, this Special Issue solicits original and novel methodological contributions addressing key challenges in the explainability and generalizability of deep learning for medical imaging. Submissions should emphasize research and advanced development of technical aspects of new image analysis methodologies, and all newly developed methods should be evaluated or validated using real and massive medical imaging data.

Dr. Sathishkumar V E.
Dr. Neelakandan Subramani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• deep learning
• internet of things
• internet of medical things
• biomedical image analysis
• medical image processing
• medical disease analysis
• biomedical data analytics
• multimodal image analysis
• healthcare data analysis