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Related Experiment Video

Updated: Dec 6, 2025

Digital Planimetry for Assessing Wound Closure Kinetics in a Mouse Model
07:56

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Published on: January 10, 2025

997

Computer Vision Challenges for Chronic Wounds Assessment.

Paula A Teixeira, Paulino A Sousa, M Coimbra

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 6, 2020
    PubMed
    Summary
    This summary is machine-generated.

    Computer vision shows promise for chronic wound assessment, improving upon subjective human evaluation. Further research and larger datasets are needed for widespread clinical adoption in wound healing.

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    Area of Science:

    • Medical Imaging
    • Computer Vision
    • Wound Care Technology

    Background:

    • Chronic wounds affect millions globally, incurring significant healthcare costs.
    • Current wound assessment relies on subjective human evaluation, leading to inconsistencies.
    • There is a need for objective, automated methods in chronic wound diagnosis and treatment monitoring.

    Purpose of the Study:

    • To review and map the existing literature on computer vision applications for chronic wound assessment and healing.
    • To identify the maturity of various computer vision techniques in addressing clinical challenges in wound care.
    • To highlight areas requiring further research and development for clinical implementation.

    Main Methods:

    • A comprehensive scoping review of 109 articles was conducted.
    • Literature was analyzed to map computer vision techniques to clinical challenges in wound assessment.
    • The maturity of different computer vision approaches was evaluated based on existing research.

    Main Results:

    • Computer vision shows potential for objective wound assessment and healing monitoring.
    • Significant progress has been made in wound size measurement and tissue type classification.
    • Several clinical areas require larger datasets and more extensive computer vision research.

    Conclusions:

    • Computer vision offers a path towards more objective and accurate chronic wound assessment.
    • While promising, further research is essential to translate computer vision advancements into routine clinical practice.
    • Addressing data limitations and expanding research efforts are crucial for realizing the full potential of computer vision in wound healing.