Applications of Computational Modeling in Biomedical Image and Signal Processing

Dear Colleagues,

With significant efforts in research and development in recent years, many advanced medical imaging modalities and bio-signal testing methods have emerged and been used in translational medical research projects and/or clinical practice. However, due to the heterogeneity and/or random noise of the acquired images and detected biosignals, methods of identifying and extracting quantitative, robust, and clinically relevant image or biosignal markers remain a major challenge. Thus, more research efforts are needed to develop and test new computational models that can more effectively process biomedical images and/or biosignals, aiming to compute robust and non-redundant features, and then to develop new novel image or biosignal markers or predictive models that can assist clinicians in diagnosing diseases and/or predicting disease prognosis more accurately.          

For this purpose, this Special Issue, entitled “Application of Computational Modeling in Biomedical Image and Signal Processing”, will focus on publishing original research papers and comprehensive review papers related to the development and application of novel computational models that can help facilitate the discovery of new quantitative, robust, and clinically relevant image or biosignal markers for disease detection, diagnosis, and prognosis. The topics of interest for this Special Issue include, but are not limited to, the following:

1. Image or biosignal data standardization or normalization to improve robustness of deep learning models;
2. Novel computational models for medical image filtering, segmentation, and feature selection;
3. Novel computational models for biosignal filtering, normalization, and reduction of feature dimensionality;
4. New methods to train and test deep learning models using relatively small numbers of medical data/samples;
5. New methods or models to generate and apply synthetic data to improve accuracy and robustness of deep learning models in biomedical applications;
6. Novel fusion methods or models to combine both medical image features and biosignal markers to improve accuracy of disease detection and diagnosis;
7. Observer preference or performance studies to test or validate the potential clinical value or utility of computational models or quantitative image or biosignal markers;

Experience of applying computational model generated quantitative markers in clinical practice of disease diagnosis and treatment planning

Prof. Dr. Bin Zheng
Dr. Xuxin Chen
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering 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 2700 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.