Abstract:
BACKGROUND:Computer-aided segmentation and border detection in dermoscopic images is one of the core components of diagnostic procedures and therapeutic interventions for skin cancer. Automated assessment tools for dermoscopy images have become an important research field mainly because of inter- and intra-observer variations in human interpretation. In this study, we compare two approaches for automatic border detection in dermoscopy images: density based clustering (DBSCAN) and Fuzzy C-Means (FCM) clustering algorithms. In the first approach, if there exists enough density--greater than certain number of points--around a point, then either a new cluster is formed around the point or an existing cluster grows by including the point and its neighbors. In the second approach FCM clustering is used. This approach has the ability to assign one data point into more than one cluster. RESULTS:Each approach is examined on a set of 100 dermoscopy images whose manually drawn borders by a dermatologist are used as the ground truth. Error rates; false positives and false negatives along with true positives and true negatives are quantified by comparing results with manually determined borders from a dermatologist. The assessments obtained from both methods are quantitatively analyzed over three accuracy measures: border error, precision, and recall. CONCLUSION:As well as low border error, high precision and recall, visual outcome showed that the DBSCAN effectively delineated targeted lesion, and has bright future; however, the FCM had poor performance especially in border error metric.
journal_name
BMC Bioinformaticsjournal_title
BMC bioinformaticsauthors
Kockara S,Mete M,Chen B,Aydin Kdoi
10.1186/1471-2105-11-S6-S26subject
Has Abstractpub_date
2010-10-07 00:00:00pages
S26issn
1471-2105pii
1471-2105-11-S6-S26journal_volume
11 Suppl 6pub_type
杂志文章abstract:BACKGROUND:While researchers have utilized versions of the Affymetrix human GeneChip for the assessment of expression patterns in non human primate (NHP) samples, there has been no comprehensive sequence analysis study undertaken to demonstrate that the probe sequences designed to detect human transcripts are reliably ...
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更新日期:2010-09-27 00:00:00
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journal_title:BMC bioinformatics
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更新日期:2006-01-26 00:00:00
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更新日期:2009-11-18 00:00:00
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journal_title:BMC bioinformatics
pub_type: 杂志文章
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更新日期:2008-12-12 00:00:00
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