NDLI: Automated wound identification system based on image segmentation and Artificial Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Bo Song Sacan, A.
Copyright Year	2012
Description	Author affiliation: School of Bio medical Engineering, Science and Health Systems, Drexel University, 3120 Market Street, Philadelphia, PA 19104, USA (Bo Song; Sacan, A.)
Abstract	A system that can automatically and accurately identify the region of a chronic wound could largely improve conventional clinical practice for the wound diagnosis and treatment. We designed a system that uses color wound photographs taken from the patients, and is capable of automatic image segmentation and wound region identification. Several commonly used segmentation methods are utilized with their parameters fine-tuned automatically to obtain a collection of candidate wound regions. Two different types of Artificial Neural Networks (ANNs), the Multi-Layer Perceptron (MLP) and the Radial Basis Function (RBF) with parameters determined by a cross-validation approach, are then applied with supervised learning in the prediction procedure for the wound identification, and their results are compared. The satisfactory results obtained by this system make it a promising tool to assist in the field of clinical wound evaluation.
Starting Page	1
Ending Page	4
File Size	2165369
Page Count	4
File Format	PDF
ISBN	9781467325592
e-ISBN	9781467325608
e-ISBN	9781467325585
DOI	10.1109/BIBM.2012.6392633
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Image segmentation Databases Artificial Neural Networks Image Segmentation Wounds Feature extraction Vectors Optimization Wound Identification
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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