Border detection in dermoscopy images using hybrid thresholding on optimized color channels
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| Title: | Border detection in dermoscopy images using hybrid thresholding on optimized color channels |
|---|---|
| Authors: | Garnavi, Rahil1 r.garnavi@ee.unimelb.edu.au, Aldeen, Mohammad1 aldeen@unimelb.edu.au, Celebi, M. Emre2 ecelebi@lsus.edu, Varigos, George3 George.varigos@mh.org.au, Finch, Sue4 sfinch@unimelb.edu.au |
| Source: | Computerized Medical Imaging & Graphics. Mar2011, Vol. 35 Issue 2, p105-115. 11p. |
| Subjects: | Biosensors, Microscopy, Image analysis, Colorimetry, Dermatologists, Sensitivity analysis, Vector processing (Computer science) |
| Abstract: | Abstract: Automated border detection is one of the most important steps in dermoscopy image analysis. Although numerous border detection methods have been developed, few studies have focused on determining the optimal color channels for border detection in dermoscopy images. This paper proposes an automatic border detection method which determines the optimal color channels and performs hybrid thresholding to detect the lesion borders. The color optimization process is tested on a set of 30 dermoscopy images with four sets of dermatologist-drawn borders used as the ground truth. The hybrid border detection method is tested on a set of 85 dermoscopy images with two sets of ground truth using various metrics including accuracy, precision, sensitivity, specificity, and border error. The proposed method, which is comprised of two stages, is designed to increase specificity in the first stage and sensitivity in the second stage. It is shown to be highly competitive with three state-of-the-art border detection methods and potentially faster, since it mainly involves scalar processing as opposed to vector processing performed in the other methods. Furthermore, it is shown that our method is as good as, and in some cases more effective than a dermatology registrar. [Copyright &y& Elsevier] |
| Copyright of Computerized Medical Imaging & Graphics is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 58096443 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Border detection in dermoscopy images using hybrid thresholding on optimized color channels – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Garnavi%2C+Rahil%22">Garnavi, Rahil</searchLink><relatesTo>1</relatesTo><i> r.garnavi@ee.unimelb.edu.au</i><br /><searchLink fieldCode="AR" term="%22Aldeen%2C+Mohammad%22">Aldeen, Mohammad</searchLink><relatesTo>1</relatesTo><i> aldeen@unimelb.edu.au</i><br /><searchLink fieldCode="AR" term="%22Celebi%2C+M%2E+Emre%22">Celebi, M. Emre</searchLink><relatesTo>2</relatesTo><i> ecelebi@lsus.edu</i><br /><searchLink fieldCode="AR" term="%22Varigos%2C+George%22">Varigos, George</searchLink><relatesTo>3</relatesTo><i> George.varigos@mh.org.au</i><br /><searchLink fieldCode="AR" term="%22Finch%2C+Sue%22">Finch, Sue</searchLink><relatesTo>4</relatesTo><i> sfinch@unimelb.edu.au</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computerized+Medical+Imaging+%26+Graphics%22">Computerized Medical Imaging & Graphics</searchLink>. Mar2011, Vol. 35 Issue 2, p105-115. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Biosensors%22">Biosensors</searchLink><br /><searchLink fieldCode="DE" term="%22Microscopy%22">Microscopy</searchLink><br /><searchLink fieldCode="DE" term="%22Image+analysis%22">Image analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Colorimetry%22">Colorimetry</searchLink><br /><searchLink fieldCode="DE" term="%22Dermatologists%22">Dermatologists</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Vector+processing+%28Computer+science%29%22">Vector processing (Computer science)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract: Automated border detection is one of the most important steps in dermoscopy image analysis. Although numerous border detection methods have been developed, few studies have focused on determining the optimal color channels for border detection in dermoscopy images. This paper proposes an automatic border detection method which determines the optimal color channels and performs hybrid thresholding to detect the lesion borders. The color optimization process is tested on a set of 30 dermoscopy images with four sets of dermatologist-drawn borders used as the ground truth. The hybrid border detection method is tested on a set of 85 dermoscopy images with two sets of ground truth using various metrics including accuracy, precision, sensitivity, specificity, and border error. The proposed method, which is comprised of two stages, is designed to increase specificity in the first stage and sensitivity in the second stage. It is shown to be highly competitive with three state-of-the-art border detection methods and potentially faster, since it mainly involves scalar processing as opposed to vector processing performed in the other methods. Furthermore, it is shown that our method is as good as, and in some cases more effective than a dermatology registrar. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computerized Medical Imaging & Graphics is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.compmedimag.2010.08.001 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 105 Subjects: – SubjectFull: Biosensors Type: general – SubjectFull: Microscopy Type: general – SubjectFull: Image analysis Type: general – SubjectFull: Colorimetry Type: general – SubjectFull: Dermatologists Type: general – SubjectFull: Sensitivity analysis Type: general – SubjectFull: Vector processing (Computer science) Type: general Titles: – TitleFull: Border detection in dermoscopy images using hybrid thresholding on optimized color channels Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Garnavi, Rahil – PersonEntity: Name: NameFull: Aldeen, Mohammad – PersonEntity: Name: NameFull: Celebi, M. Emre – PersonEntity: Name: NameFull: Varigos, George – PersonEntity: Name: NameFull: Finch, Sue IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2011 Type: published Y: 2011 Identifiers: – Type: issn-print Value: 08956111 Numbering: – Type: volume Value: 35 – Type: issue Value: 2 Titles: – TitleFull: Computerized Medical Imaging & Graphics Type: main |
| ResultId | 1 |
