Fuzzy spectral clustering for automated delineation of chronic wound region using digital images. (1st October 2017)

• Record Type: Journal Article
• Authors: Manohar Dhane, Dhiraj; Maity, Maitreya; Mungle, Tushar; Bar, Chittaranjan; Achar, Arun; Kolekar, Maheshkumar; Chakraborty, Chandan
• Is Part Of: Computers in biology and medicine. Volume 89(2017)
• Page Start: 551
• Page End: 560
• Publication Date: 2017-10-01
• Subjects: Chronic wound -- Color constancy -- Digital image processing -- Fuzzy similarity measure -- Spectral clustering -- Segmentation; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2017.04.004
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Chronic wound is an abnormal disease condition of localized injury to the skin and its underlying tissues having physiological impaired healing response. Assessment and management of such wound is a significant burden on the healthcare system. Currently, precise wound bed estimation depends on the clinical judgment and remains a difficult task. The paper introduces a novel method for ulcer boundary demarcation and estimation, using optical images captured by a hand-held digital camera. The proposed approach involves gray based fuzzy similarity measure using spatial knowledge of an image. The fuzzy measure is used to construct similarity matrix. The best color channel was chosen by calculating the mean contrast for 26 different color channels of 14 color spaces. It was found that Db color channel has highest mean contrast which provide best segmentation result in comparison with other color channels. The fuzzy spectral clustering (FSC) method was applied on Db color channel for effective delineation of wound region. The segmented wound regions were effectively post-processed using various morphological operations. The performance of proposed segmentation technique was validated by ground-truth images labeled by two experienced dermatologists and a surgeon. The FSC approach was tested on 70 images. FSC effectively segmented targeted ulcer boundary yielding 91.5% segmentation accuracy, 86.7%, Dice index and 79.0%. Jaccard score. The sensitivity and specificity was found to be 87.3% and 95.7% respectively. The performance evaluation shows the robustness of the proposed method of wound area segmentation and its potential to be used for designing patient comfort centric wound care system.