Computer-Vision-Based Biomedical Image Processing
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 January 2025 | Viewed by 879
Special Issue Editors
Interests: computer vision; deep learning; medical computer vision
Special Issues, Collections and Topics in MDPI journals
Interests: big data analytics; machine learning; computer vision; IoT; smart grids; distributed system; software engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Computer vision has a rich history spanning decades of efforts towards enabling computers to perceive visual stimuli meaningfully. Machine perception covers a range of levels, from low-level tasks such as identifying edges to high-level tasks such as understanding complete scenes. The growth of modern computer vision has overlapped with the generation of large amounts of digital data in several scientific fields. Large datasets allow computer vision models to acquire varied pattern recognition abilities, ranging from physician-level diagnostics to medical scene perception.
This Special Issue aims to bring together researchers and practitioners from the fields of computer vision and biomedical imaging to showcase cutting-edge developments in computer vision algorithms and their applications in biomedical image processing and digital healthcare. This Special Issue invites original research articles, comprehensive reviews, and insightful case studies that focus on, but are not limited to, the following topics:
- Deep-Learning-Enabled Medical Computer Vision
- Computer-Aided Diagnosis (CAD)
- Imaging Biomarkers
- Biomedical Informatics
- Multi-level Biomedical Data Integration
- Explainable and Trustworthy Computer Vision
- Screening, Early Detection, and Prediction of Future Outcomes
Dr. Grigorios E. Kalliatakis
Dr. Christos Chrysoulas
Guest Editors
Manuscript Submission Information
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Keywords
- computer vision
- artificial intelligence
- biomedical image processing
- medical image analysis
- deep learning
- representation learning
- computer-aided detection
- anomaly detection
- biomarkers
- digital healthcare
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Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Moving Healthcare AI-Support Systems for Visually Detectable Diseases onto Constrained Devices
Author: Watt
Highlights: -The model produced a test accuracy of 78% and a test loss of 1.08. The test data consisted of 1000 images.
-Our model produced a higher accuracy than a similar model developed by Ramlakhan & Shang, who used a smaller dataset.
-However, our model produced a lower accuracy than two similar models using higher spec hardware.
