Applications of Computational Modeling in Biomedical Image and Signal Processing—2nd Edition

Dear Colleagues,

With significant efforts in research and development in recent years, many advanced medical imaging modalities and biosignal 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, further 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 “Applications of Computational Modeling in Biomedical Image and Signal Processing—2nd Edition”, 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 reductions in 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;
8. The experience of applying computational model generated quantitative markers in clinical practice of disease diagnosis and treatment planning;
9. Development and application of multimodal foundation models for biomedical applications to integrate diverse data modalities such as medical images, biosignals, and clinical text, improving accuracy, robustness, and interpretability in disease diagnosis and treatment planning.

Dr. Xuxin Chen
Prof. Dr. Bin Zheng
Guest Editors

Manuscript Submission Information

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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. 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.

• computational modeling
• quantitative disease markers
• medical image processing
• image segmentation
• biosignal testing
• biosignal processes
• feature selection
• deep learning
• computer-aided diagnosis
• data standardization
• synthetic data generation

• Machine Learning and Artificial Intelligence for Biomedical Applications in Bioengineering (19 articles)