文章基本信息

标题：Wound Image Analysis Classifier for Efficient Tracking of Wound Healing Status
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作者：K. Sundeep Kumar ; B. Eswara Reddy
期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2014
卷号：5
期号：2
页码：15
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Wounds are evolved by increase in number of damage tissues. The traditional way of assessing the woundhealing status is to periodic measure of the area covered by the wound. This technique is tedious tomeasure and periodic assessment is cumbersome. Basically healing status of the wound can be classifiedas contact methods and non contact methods. The purpose of this research work is to accurately assess thehealing status of the wound .To accurately assess the wound, capturing of the wound images are the firsttask to be performed. There are various tools like the photographic wound assessment tool (PWAT) toacquire efficient wound images. Since the characteristics of different types of wounds (venous, pressure,diabetic, and arterial ulcers) vary markedly, determining the reliability and validity of using the PWAT toassess wound appearance for both chronic pressure ulcers and leg ulcers due to vascular insufficiency isimportant. Segmenting the area of the wound from the wound image using efficient segmentationtechniques and preprocessing the segmented wound to reduce the noise using efficient filters and efficientdenoising techniques. Efficient classifiers are needed to classify the wound images. One among theclassifiers are the Wound Image Analysis Classifier (WIAC). Experimental evaluation has been made oncomparing various classifiers like SVM, KNN, WIAC.
关键词：Skin; Wound types; Filtering; Segmentation; Classification