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<div>Medical Image Analysis (MIA) is seeking original and unpublished manuscripts for a special issue on Image Analysis in Dermatology:</div><div><a href="https://www.journals.elsevier.com/medical-image-analysis/call-for-papers/special-issue-on-image-analysis-in-dermatology">
https://www.journals.elsevier.com/medical-image-analysis/call-for-papers/special-issue-on-image-analysis-in-dermatology</a><br>
</div><br>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.<br><br>This special issue aims to cover all aspects of dermatological image analysis. Topics of interest include, but are not limited to:<br><br>+ Enhancement<br>+ Registration<br>+ Segmentation<br>+ Feature Extraction<br>+ Content-Based Retrieval<br>+ Synthetic Image Generation<br>+ Classification<br>+ Visualization<br><br>Paper Submission<br>------------------------<br>Please ensure that you read the Guide for Authors before writing your manuscript. The Guide for Authors and manuscript submission link are available on MIA’s homepage (<a href="https://www.elsevier.com/journals/medical-image-analysis/1361-8415/guide-for-authors">https://www.elsevier.com/journals/medical-image-analysis/1361-8415/guide-for-authors</a>). <br><br>When submitting your manuscript, please select the article type “VSI: Img Anal Derm”. Please submit your manuscript latest by March 1, 2021.<br><br>Manuscripts submitted to this special issue must be unpublished and may not be under consideration elsewhere. All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online special issue. Articles from this special issue will appear in different regular issues of the journal, though they will be clearly marked and branded as special issue articles.<br><br>Special Issue Organizers <br>---------------------------------<br>M. Emre Celebi, Ph.D. (University of Central Arkansas, Conway, AR, USA)<br>Catarina Barata, Ph.D. (Instituto Superior Tecnico, Lisbon, Portugal)<br>Allan Halpern, M.D. (Memorial Sloan Kettering Cancer Center, New York City, NY, USA)<br>Philipp Tschandl, M.D. Ph.D. (Medical University of Vienna, Vienna, Austria)<br>Marc Combalia, M.Sc. (Hospital Clinic of Barcelona, Barcelona, Spain)<br>Yuan Liu, Ph.D. (Google Health, Palo Alto, CA, USA)<br>Ender Konukoglu, Ph.D. (ETH-Zurich, Zurich, Switzerland)<br><br>Contact Email<br>-------------------<br><a href="mailto:ecelebi@uca.edu">ecelebi@uca.edu</a>
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