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An Automatic Assessment System of Diabetic Foot Ulcers Based on Wound Area Determination, Color Segmentation, and Healing Score Evaluation.
Wang, Lei; Pedersen, Peder C; Strong, Diane M; Tulu, Bengisu; Agu, Emmanuel; Ignotz, Ron; He, Qian.
Afiliación
  • Wang L; Electrical and Computer Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA lwang1@wpi.edu.
  • Pedersen PC; Electrical and Computer Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA.
  • Strong DM; School of Business, Worcester Polytechnic Institute, Worcester, MA, USA.
  • Tulu B; School of Business, Worcester Polytechnic Institute, Worcester, MA, USA.
  • Agu E; Computer Science Department, Worcester Polytechnic Institute, Worcester, MA, USA.
  • Ignotz R; Plastic Surgery Department, UMASS Medical School, Worcester, MA, USA.
  • He Q; Computer Science Department, Worcester Polytechnic Institute, Worcester, MA, USA.
J Diabetes Sci Technol ; 10(2): 421-8, 2015 Aug 07.
Article en En | MEDLINE | ID: mdl-26253144
BACKGROUND: For individuals with type 2 diabetes, foot ulcers represent a significant health issue. The aim of this study is to design and evaluate a wound assessment system to help wound clinics assess patients with foot ulcers in a way that complements their current visual examination and manual measurements of their foot ulcers. METHODS: The physical components of the system consist of an image capture box, a smartphone for wound image capture and a laptop for analyzing the wound image. The wound image assessment algorithms calculate the overall wound area, color segmented wound areas, and a healing score, to provide a quantitative assessment of the wound healing status both for a single wound image and comparisons of subsequent images to an initial wound image. RESULTS: The system was evaluated by assessing foot ulcers for 12 patients in the Wound Clinic at University of Massachusetts Medical School. As performance measures, the Matthews correlation coefficient (MCC) value for the wound area determination algorithm tested on 32 foot ulcer images was .68. The clinical validity of our healing score algorithm relative to the experienced clinicians was measured by Krippendorff's alpha coefficient (KAC) and ranged from .42 to .81. CONCLUSION: Our system provides a promising real-time method for wound assessment based on image analysis. Clinical comparisons indicate that the optimized mean-shift-based algorithm is well suited for wound area determination. Clinical evaluation of our healing score algorithm shows its potential to provide clinicians with a quantitative method for evaluating wound healing status.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Telemedicina / Pie Diabético / Diabetes Mellitus Tipo 2 Tipo de estudio: Guideline Límite: Adult / Female / Humans / Male Idioma: En Revista: J Diabetes Sci Technol Asunto de la revista: ENDOCRINOLOGIA Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Telemedicina / Pie Diabético / Diabetes Mellitus Tipo 2 Tipo de estudio: Guideline Límite: Adult / Female / Humans / Male Idioma: En Revista: J Diabetes Sci Technol Asunto de la revista: ENDOCRINOLOGIA Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos