Quantitative Assessment of Tumour Extraction from Dermoscopy Images and Evaluation of Computer-Based Extraction Methods for an Automatic Melanoma Diagnostic System

Iyatomi, H, Oka, H, Saito, M, Miyake, A, Kimoto, M, Yamagami, J, Kobayashi, S, Tanikawa, A, Hagiwara, M, Ogawa, K, Argenziano, G, Soyer, HP and Tanaka, M (2006) Quantitative Assessment of Tumour Extraction from Dermoscopy Images and Evaluation of Computer-Based Extraction Methods for an Automatic Melanoma Diagnostic System. Melanoma Research, 16 2: 183-190. doi:10.1097/01.cmr.0000215041.76553.58


Author Iyatomi, H
Oka, H
Saito, M
Miyake, A
Kimoto, M
Yamagami, J
Kobayashi, S
Tanikawa, A
Hagiwara, M
Ogawa, K
Argenziano, G
Soyer, HP
Tanaka, M
Title Quantitative Assessment of Tumour Extraction from Dermoscopy Images and Evaluation of Computer-Based Extraction Methods for an Automatic Melanoma Diagnostic System
Journal name Melanoma Research   Check publisher's open access policy
ISSN 0960-8931
1473-5636
Publication date 2006-04-01
Year available 2006
Sub-type Article (original research)
DOI 10.1097/01.cmr.0000215041.76553.58
Open Access Status DOI
Volume 16
Issue 2
Start page 183
End page 190
Total pages 8
Place of publication London
Publisher Lippincott Williams and Wilkins
Language eng
Subject 110304 Dermatology
Abstract The aims of this study were to provide a quantitative assessment of the tumour area extracted by dermatologists and to evaluate computer-based methods from dermoscopy images for refining a computer-based melanoma diagnostic system. Dermoscopic images of 188 Clark naevi, 56 Reed naevi and 75 melanomas were examined. Five dermatologists manually drew the border of each lesion with a tablet computer. The inter-observer variability was evaluated and the standard tumour area (STA) for each dermoscopy image was defined. Manual extractions by 10 non-medical individuals and by two computer-based methods were evaluated with STA-based assessment criteria: precision and recall. Our new computer-based method introduced the region-growing approach in order to yield results close to those obtained by dermatologists. The effectiveness of our extraction method with regard to diagnostic accuracy was evaluated. Two linear classifiers were built using the results of conventional and new computer-based tumour area extraction methods. The final diagnostic accuracy was evaluated by drawing the receiver operating curve (ROC) of each classifier, and the area under each ROC was evaluated. The standard deviations of the tumour area extracted by five dermatologists and 10 non-medical individuals were 8.9% and 10.7%, respectively. After assessment of the extraction results by dermatologists, the STA was defined as the area that was selected by more than two dermatologists. Dermatologists selected the melanoma area with statistically smaller divergence than that of Clark naevus or Reed naevus (P = 0.05). By contrast, non-medical individuals did not show this difference. Our new computer-based extraction algorithm showed superior performance (precision, 94.1%; recall, 95.3%) to the conventional thresholding method (precision, 99.5%; recall, 876%). These results indicate that our new algorithm extracted a tumour area close to that obtained by dermatologists and, in particular, the border part of the tumour was adequately extracted. With this refinement, the area under the ROC increased from 0.795 to 0.875 and the diagnostic accuracy showed an increase of approximately 20% in specificity when the sensitivity was 80%. It can be concluded that our computer-based tumour extraction algorithm extracted almost the same area as that obtained by dermatologists and provided improved computer-based diagnostic accuracy.
Keyword Oncology
Dermatology
Medicine, Research & Experimental
Oncology
Dermatology
Research & Experimental Medicine
DERMATOLOGY
MEDICINE, RESEARCH & EXPERIMENTAL
ONCOLOGY
Q-Index Code C1
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Medicine Publications
 
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Created: Fri, 03 Apr 2009, 23:16:50 EST by Mary-Anne Marrington on behalf of School of Medicine