Computer Vision in Biomedical Engineering

Dear Colleagues,

Biomedical imaging plays a crucial role in healthcare, improving the diagnosis, treatment planning, and monitoring of diseases. The integration of computer vision and deep learning techniques has revolutionized this field by enabling more accurate, automated, and efficient analysis of complex data. From biomedical imaging, computer vision is driving advances that improve both patient care and precision medicine. However, many challenges remain, such as handling big data collections, ensuring robust and interpretable models, and integrating these systems into society.

The main objective of this Special Issue is to attract high-quality papers detailing recent research, as well as review articles that contribute to this interdisciplinary domain. Relevant topics for this Special Issue may include (but are not limited to) the following:

• Medical image processing: innovative techniques for diagnosis, enhancement, segmentation, and feature extraction in biomedical images.
• Deep learning in biomedical imaging: novel architectures, transfer learning, and AI approaches applied to biomedical imaging.
• 3D medical image reconstruction: advances in 3D volumetric analysis and reconstruction methods based on CT, MRI, and ultrasound imaging.
• Computer-aided diagnosis: development of decision-support systems leveraging AI for disease detection, classification, and diagnosis.
• Pattern recognition: detection and analysis of pathological patterns in various types of images.
• Computer vision: vision techniques applied to biomedical imaging, surgical guidance, and patient monitoring systems.
• X-ray and CT image analysis: automated techniques for analyzing biological images and detecting anomalies and features.
• Optical imaging in biomedicine: advancements in microscopy, endoscopy, and other optical imaging methods.
• Augmented and virtual reality: AR/VR technologies for surgical planning, medical training, and enhanced visualization of biomedical data.
• Multimodal imaging and fusion: techniques for integrating data from multiple imaging modalities.

Dr. Francisco Daniel Pérez-Cano
Dr. Juan Jiménez-Delgado
Dr. Gema Parra-Cabrera
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 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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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.

• medical image processing
• deep learning in biomedical imaging
• 3D medical image reconstruction
• computer-aided diagnosis
• pattern recognition
• computer vision
• X-ray and CT image analysis
• pptical imaging in biomedicine
• augmented and virtual reality
• multimodal imaging and fusion