Clustering and classification of local image of wound blotting for assessment of pressure ulcer

Hiroshi Noguchi, Aya Kitamura, Mikako Yoshida, Takeo Minematsu, Taketoshi Mori, Hiromi Sanada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper describes applying image recognition techniques to the stained image captured by wound blotting. The wound blotting adsorbs the proteins on the wound surface and visualizes protein distribution as a stained image. The local patterns of the stained image may indicate wound healing. For investigation of relationship between pressure ulcer healing process and protein distribution, the categorization and classification by image recognition technique are required because manual classification and annotation are time-consuming and troublesome. In order to apply clustering and classification to the stained image, three features (GLCM, wavelet, and LBP) were compared. As for the clustering, three features achieved the similar performance, however, the clustering results were slightly different from human labeling. As for the classification, wavelet and LBP features achieved good performance. However, particular texture pattern, which is defined as texture whose intensity was stable or changed on direction, was difficult to classify. These results demonstrated the feasibility of applying image recognition technique to the stained images for wound assessment.

Original languageEnglish
Title of host publicationWorld Automation Congress Proceedings
PublisherIEEE Computer Society
Pages427-432
Number of pages6
ISBN (Electronic)9781889335490
DOIs
Publication statusPublished - 2014 Oct 24
Externally publishedYes
Event2014 World Automation Congress, WAC 2014 - Waikoloa, United States
Duration: 2014 Aug 32014 Aug 7

Publication series

NameWorld Automation Congress Proceedings
ISSN (Print)2154-4824
ISSN (Electronic)2154-4832

Other

Other2014 World Automation Congress, WAC 2014
CountryUnited States
CityWaikoloa
Period14/8/314/8/7

ASJC Scopus subject areas

  • Control and Systems Engineering

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