Computer Vision for Medical Informatics and Biometrics Applications
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 July 2025 | Viewed by 1162
Special Issue Editor
Interests: image processing; computer vision; machine learning; pattern recognition; feature extraction; image segmentation
Special Issue Information
Dear Colleagues,
Computer vision (CV) integration into medical informatics and biometric applications is essential for advancing medical research and improving healthcare delivery. The rapid development of artificial intelligence (AI) and CV has significantly improved diagnostic performance by enabling the early detection of diseases with high precision, thus identifying signs which are often too subtle for human perception.
AI-powered CV systems have revolutionized the analysis of medical imaging, allowing for the early and accurate detection of conditions such as cancer, cardiovascular diseases, and neurological disorders. These systems can process and interpret large volumes of medical images swiftly and accurately, reducing the workload on radiologists. Additionally, they are less prone to human error, subjective assessment, and user variability, leading to more consistent and reliable diagnostic outcomes.
The automation capabilities of CV and AI in medical informatics are profound. By automating routine and repetitive tasks, these technologies allow medical professionals to focus on the more complex and critical aspects of patient care. This not only improves the efficiency within healthcare systems, but also enhances the quality of care provided to patients.
Similarly, biometric applications have greatly benefited from advancements in CV and AI research. The improvements in the accuracy, security, and reliability of biometric systems have wide-ranging implications across various sectors, including healthcare, finance, and law enforcement. In healthcare, for example, biometric systems enhance patient identification processes, ensuring the right care is provided to the right patient. In finance, they improve security measures for transactions, while, in law enforcement, they aid in accurate identification and tracking.
As CV and AI technologies continue to evolve, their importance in medical research and practice will only increase. This ongoing development promises to lead to better patient care and more innovative healthcare solutions. Furthermore, their integration into biometric applications is expected to result in more robust and reliable systems, enhancing security and efficiency across multiple sectors.
In conclusion, the integration of CV and AI into medical informatics and biometrics applications represents a significant advancement in both fields. These technologies are not only transforming current practices, but are also paving the way for future innovations that will further enhance the quality and reliability of healthcare and security systems.
Prof. Dr. Boris Escalante-Ramírez
Guest Editor
Manuscript Submission Information
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Keywords
- computer vision (CV)
- artificial intelligence (AI)
- medical informatics
- computed-aided diagnosis
- computed assisted intervention
- medical imaging computing
- translational medicine
- PACS
- innovative healthcare solutions
- biometrics applications
- biometric systems
- patient identification
- identification and tracking
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