Detection and classification of granulation tissue in chronic ulcers

Ahmad Fadzil M Hani, Leena Arshad, Aamir Saeed Malik, Adawiyah Jamil, Felix Yap Boon Bin

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

2 Citations (Scopus)

Abstract

The ability to measure objectively wound healing is important for an effective wound management. Describing wound tissues in terms of percentages of each tissue colour is an approved clinical method of wound assessment. Wound healing is indicated by the growth of the red granulation tissue, which is rich in small blood capillaries that contain haemoglobin pigment reflecting the red colour of the tissue. A novel approach based on utilizing haemoglobin pigment content in chronic ulcers as an image marker to detect the growth of granulation tissue is investigated in this study. Independent Component Analysis is employed to convert colour images of chronic ulcers into images due to haemoglobin pigment only. K-means clustering is implemented to classify and segment regions of granulation tissue from the extracted haemoglobin images. Results obtained indicate an overall accuracy of 96.88% of the algorithm performance when compared to the manual segmentation.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages139-150
Number of pages12
Volume7066 LNCS
EditionPART 1
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2nd International Visual Informatics Conference, IVIC 2011 - Selangor
Duration: 9 Nov 201111 Nov 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7066 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd International Visual Informatics Conference, IVIC 2011
CitySelangor
Period9/11/1111/11/11

Fingerprint

Granulation
Hemoglobin
Tissue
Wound Healing
Pigments
Color
K-means Clustering
Independent Component Analysis
Color Image
Convert
Blood
Percentage
Segmentation
Classify
Independent component analysis

Keywords

  • Chronic Wounds
  • Granulation Tissue
  • Haemoglobin
  • Independent Component Analysis
  • Ulcers
  • Visual Informatics

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Hani, A. F. M., Arshad, L., Malik, A. S., Jamil, A., & Bin, F. Y. B. (2011). Detection and classification of granulation tissue in chronic ulcers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 7066 LNCS, pp. 139-150). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7066 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-25191-7_14

Detection and classification of granulation tissue in chronic ulcers. / Hani, Ahmad Fadzil M; Arshad, Leena; Malik, Aamir Saeed; Jamil, Adawiyah; Bin, Felix Yap Boon.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7066 LNCS PART 1. ed. 2011. p. 139-150 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7066 LNCS, No. PART 1).

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

Hani, AFM, Arshad, L, Malik, AS, Jamil, A & Bin, FYB 2011, Detection and classification of granulation tissue in chronic ulcers. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 7066 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7066 LNCS, pp. 139-150, 2nd International Visual Informatics Conference, IVIC 2011, Selangor, 9/11/11. https://doi.org/10.1007/978-3-642-25191-7_14
Hani AFM, Arshad L, Malik AS, Jamil A, Bin FYB. Detection and classification of granulation tissue in chronic ulcers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 7066 LNCS. 2011. p. 139-150. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-25191-7_14
Hani, Ahmad Fadzil M ; Arshad, Leena ; Malik, Aamir Saeed ; Jamil, Adawiyah ; Bin, Felix Yap Boon. / Detection and classification of granulation tissue in chronic ulcers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7066 LNCS PART 1. ed. 2011. pp. 139-150 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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