Utilizing Image Processing Techniques for Wound Management and Evaluation in Clinical Practice: Establishing the Feasibility of Implementing Artificial Intelligence in Routine Wound Care.
OBJECTIVE: To develop a generalizable and accurate method for automatically analyzing wound images captured in clinical practice and extracting key wound characteristics such as surface area measurement. METHODS: The authors used image processing techniques to create a robust algorithm for segmentin...
| Publicado en: | Advances in Skin & Wound Care Vol. 38; no. 1; pp. 31 - 40 |
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| Autores principales: | , , |
| Formato: | algorithm equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Lippincott Williams & Wilkins
Jan/Feb2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=182341633&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 182341633 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15277941 38T jtl: Advances in Skin & Wound Care issn: 15277941 maglogo: N pubinfo: dt: Jan/Feb2025 vid: 38 iid: 1 pid: 5086 pub: Lippincott Williams & Wilkins place: Baltimore, Maryland artinfo: ui: 182341633 182341633 182341633 10.1097/ASW.0000000000000246 182341633 ppf: 31 ppct: 9 formats: tig: atl: Utilizing Image Processing Techniques for Wound Management and Evaluation in Clinical Practice: Establishing the Feasibility of Implementing Artificial Intelligence in Routine Wound Care. aug: au: Dabas, Mai Kapp, Suzanne Gefen, Amit sug: subj: Wounds, Chronic Nursing Wound Care Wound Assessment Artificial Intelligence Image Processing, Computer Assisted Utilization Human Female Male Aged Aged, 80 and Over Sociodemographic Factors Photography Scales Algorithms Validity Pressure Ulcer Prevention and Control Decision Making, Clinical Descriptive Statistics Aged: 65+ years Aged, 80 & over Female Male ab: OBJECTIVE: To develop a generalizable and accurate method for automatically analyzing wound images captured in clinical practice and extracting key wound characteristics such as surface area measurement. METHODS: The authors used image processing techniques to create a robust algorithm for segmenting pressure injuries from digital images captured by nurses during clinical practice. The algorithm also measured the real-world wound surface area. They used the hue-saturation-value color space to analyze red color values and to detect and segment the wound region within the entire image. To assess the accuracy of the algorithm's wound segmentation, the authors compared the results against wound image annotations. RESULTS: The algorithm performed impressively, achieving an intersection-over-union score of up to 0.85 and 100% intersection with the annotations. The algorithm effectively analyzed wound images obtained during clinical practice and accurately extracted the surface area of the documented pressure injuries. These results support the feasibility and applicability of this methodology. CONCLUSIONS: Accurate determination of wound size and healing supports decision-making regarding treatment and is essential to successful outcomes. This innovative approach for visual assessment of chronic wounds highlights the potential of computerized wound analysis in clinical practice. By leveraging advanced computational techniques, healthcare providers can gain valuable insights into wound progression, enabling more accurate assessments to support their decision-making. pubtype: Academic Journal doctype: algorithm equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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