Digital Medicine and Image Processing

Dear Colleagues, 

This Special Issue will present extended versions of selected papers presented at the 4th International Conference on Digital Medicine and Image Processing (DMIP 2021). DMIP 2021 aims to provide a platform for researchers, engineers, and academicians, as well as industrial professionals from all over the world, to present their research results and development activities in Digital Medicine and Image Processing and related fields. It is one of the leading international conferences for presenting novel and fundamental advances in these fields. It started in Okinawa, Japan in 2018, followed by Shanghai, China in 2019 and Kyoto, Japan in 2020. Hit by global COVID-19 pandemic in 2020, we had many presenters and participants by holding the conference online. The conference returns to Kyoto in 2021.

Image processing, one of the topics covered in the conference, is considered to be one of the most rapidly evolving areas of information technology today, and its applications are expanding and deepening not only in medical imaging, but also in various other fields such as industrial imaging, remote sensing, and space imaging, for instance. Furthermore, digital medicine can be described as a technology for measuring and monitoring human beings for the sake of their health. It consists of a wide range of high-quality medical software and hardware to treat and prevent diseases and improve the health of individuals and entire populations.

In addition to applications and implementations of digital medicine and image processing, this Special Issue also welcomes research on understanding humans, which is the basis for technologies for measuring and monitoring humans. Examples include physiology, biological engineering, neuroscience, natural anthropology, zoology, psychology, and cybernetics. Authors of invited papers should be aware that the final submitted manuscript must provide a minimum of 30% new content and not exceed 30% copy/paste from the proceedings paper. 

Prof. Dr. Kiyoshi Hoshino
Guest Editor

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. Information 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.

• digital medicine
• medical image analysis
• MR image reconstruction
• CT image reconstruction, radiomics
• molecular imaging
• medical big data
• segmentation and 3D visualization
• digital pathology
• bioinformatics
• biological engineering
• computational anatomy
• physiology
• neuroscience
• natural anthropology
• zoology
• psychology
• application of machine learning in medicine
• cybernetics
• image processing
• image segmentation
• image registration
• image reconstruction
• image matching
• feature extraction
• image detection and recognition
• shape analysis
• machine learning
• deep learning
• hardware (FPGA, DSP, IC) for image processing and machine learning