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Computer Science > Computers and Society

arXiv:2009.07141 (cs)
[Submitted on 15 Sep 2020]

Title:Image Based Artificial Intelligence in Wound Assessment: A Systematic Review

Authors:D. M. Anisuzzaman (1), Chuanbo Wang (1), Behrouz Rostami (2), Sandeep Gopalakrishnan (3), Jeffrey Niezgoda (4), Zeyun Yu (1) ((1) Department of Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI, USA, (2) Department of Electrical Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, USA, (3) College of Nursing, University of Wisconsin-Milwaukee, Milwaukee, WI, USA, (4) Jeffrey Niezgoda is with the AZH Wound Center, Milwaukee, WI, USA.)
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Abstract:Efficient and effective assessment of acute and chronic wounds can help wound care teams in clinical practice to greatly improve wound diagnosis, optimize treatment plans, ease the workload and achieve health related quality of life to the patient population. While artificial intelligence (AI) has found wide applications in health-related sciences and technology, AI-based systems remain to be developed clinically and computationally for high-quality wound care. To this end, we have carried out a systematic review of intelligent image-based data analysis and system developments for wound assessment. Specifically, we provide an extensive review of research methods on wound measurement (segmentation) and wound diagnosis (classification). We also reviewed recent work on wound assessment systems (including hardware, software, and mobile apps). More than 250 articles were retrieved from various publication databases and online resources, and 115 of them were carefully selected to cover the breadth and depth of most recent and relevant work to convey the current review to its fulfillment.
Comments: 18 pages, 9 tables, 1 figure
Subjects: Computers and Society (cs.CY); Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2009.07141 [cs.CY]
  (or arXiv:2009.07141v1 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.2009.07141
Journal reference: Adv Wound Care (New Rochelle). 2021 Sep 21. PMID: 34544270
Related DOI: https://doi.org/10.1089/wound.2021.0091

Submission history

From: D. M. Anisuzzaman [view email]
[v1] Tue, 15 Sep 2020 14:52:14 UTC (414 KB)
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