Deep Learning in Biomedical Image Segmentation and Classification: Advancements, Challenges and Applications, 2nd Edition

Dear Colleagues,

This Special Issue aims to explore the latest advancements, challenges, and applications associated with deep learning techniques in the field of biomedical image segmentation and classification. Biomedical image analysis plays a crucial role in various medical domains, enabling the accurate identification, segmentation, and classification of structures, organs, and anomalies. Deep learning, with its ability to learn complex features and patterns from large-scale datasets, has revolutionized biomedical image analysis, offering significant improvements in segmentation and classification accuracy and efficiency. This Special Issue welcomes the submission of original research papers, review articles, and case studies that present novel deep learning methodologies, architectures, and algorithms, as well as their practical applications and implications in biomedical image segmentation and classification. This collection of contributions will provide a comprehensive overview of the current state-of-the-art techniques, identify challenges and limitations, and pave the way for future research directions in this rapidly evolving field.

This Special Issue is a follow up to a previous one. We appreciate the authors’ valuable contributions to the 1st edition, which can be accessed via the following link: https://www.mdpi.com/journal/jimaging/special_issues/DZ7T60VI90.

Dr. Ebrahim Karami
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 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-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 1800 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.

• biomedical image segmentation
• biomedical image classification
• lesion detection with deep learning
• cancer detection and classification with deep learning
• computer-aided diagnosis
• deep learning for MRI and FMRI imaging
• deep learning for X-ray imaging
• deep learning for ultrasound imaging
• deep learning for infrared imaging
• deep learning for biomedical object localization
• biomedical image denoising and enhancement using deep learning
• 3D and 4D biomedical image analysis
• multimodal and multiscale biomedical data fusion
• synthetic data generation and data augmentation
• explainability, interpretability, and uncertainty quantification
• ethics, bias, and federated learning in biomedical imaging

• Deep Learning in Biomedical Image Segmentation and Classification: Advancements, Challenges and Applications in Journal of Imaging (13 articles)