Literature DB >> 17271952

New protocol for leg ulcer tissue classification from colour images.

H Zheng1, L Bradley, D Patterson, M Galushka, J Winder.   

Abstract

Measurement of wound healing status is very important for monitoring progress in individual patients. Tissue classification is a vital step in the development of an automatic measurement system for wound healing assessment. We present a new tissue classification protocol using the RGB (Red, Green and Blue) histogram distributions of pixel values from wound color images. These three histogram distributions (extracted features) were used as three two-dimensional (2D) input signals for classification. This protocol has been carried out using the KNN classifier and results show that the proposed protocol provides an extremely competent practical method for the classification of wound tissues.

Entities:  

Year:  2004        PMID: 17271952     DOI: 10.1109/IEMBS.2004.1403432

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Wound Size Imaging: Ready for Smart Assessment and Monitoring.

Authors:  Yves Lucas; Rania Niri; Sylvie Treuillet; Hassan Douzi; Benjamin Castaneda
Journal:  Adv Wound Care (New Rochelle)       Date:  2020-09-25       Impact factor: 4.730

2.  Chronic wound assessment and infection detection method.

Authors:  Jui-Tse Hsu; Yung-Wei Chen; Te-Wei Ho; Hao-Chih Tai; Jin-Ming Wu; Hsin-Yun Sun; Chi-Sheng Hung; Yi-Chong Zeng; Sy-Yen Kuo; Feipei Lai
Journal:  BMC Med Inform Decis Mak       Date:  2019-05-24       Impact factor: 2.796

  2 in total

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