Automatic Segmentation of Dermoscopic Images by Iterative Classification
Accurate detection of the borders of skin lesions is a vital first step for computer aided diagnostic systems. This paper presents a novel automatic approach to segmentation of skin lesions that is particularly suitable for analysis of dermoscopic images. Assumptions about the image acquisition, in...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2011-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2011/972648 |
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| _version_ | 1850233420781715456 |
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| author | Maciel Zortea Stein Olav Skrøvseth Thomas R. Schopf Herbert M. Kirchesch Fred Godtliebsen |
| author_facet | Maciel Zortea Stein Olav Skrøvseth Thomas R. Schopf Herbert M. Kirchesch Fred Godtliebsen |
| author_sort | Maciel Zortea |
| collection | DOAJ |
| description | Accurate detection of the borders of skin lesions is a vital first step for computer aided diagnostic systems. This paper presents a novel automatic approach to segmentation of skin lesions that is particularly suitable for analysis of dermoscopic images. Assumptions about the image acquisition, in particular, the approximate location and color, are used to derive an automatic rule to select small seed regions, likely to correspond to samples of skin and the lesion of interest. The seed regions are used as initial training samples, and the lesion segmentation problem is treated as binary classification problem. An iterative hybrid classification strategy, based on a weighted combination of estimated posteriors of a linear and quadratic classifier, is used to update both the automatically selected training samples and the segmentation, increasing reliability and final accuracy, especially for those challenging images, where the contrast between the background skin and lesion is low. |
| format | Article |
| id | doaj-art-0c18f660997b44ae9b74705e522097fc |
| institution | OA Journals |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-0c18f660997b44ae9b74705e522097fc2025-08-20T02:02:55ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962011-01-01201110.1155/2011/972648972648Automatic Segmentation of Dermoscopic Images by Iterative ClassificationMaciel Zortea0Stein Olav Skrøvseth1Thomas R. Schopf2Herbert M. Kirchesch3Fred Godtliebsen4Department of Mathematics and Statistics, University of Tromsø, 9037 Tromsø, NorwayNorwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, 9038 Tromsø, NorwayNorwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, 9038 Tromsø, NorwayVenloer Straße 107, 50259 Pulheim, GermanyDepartment of Mathematics and Statistics, University of Tromsø, 9037 Tromsø, NorwayAccurate detection of the borders of skin lesions is a vital first step for computer aided diagnostic systems. This paper presents a novel automatic approach to segmentation of skin lesions that is particularly suitable for analysis of dermoscopic images. Assumptions about the image acquisition, in particular, the approximate location and color, are used to derive an automatic rule to select small seed regions, likely to correspond to samples of skin and the lesion of interest. The seed regions are used as initial training samples, and the lesion segmentation problem is treated as binary classification problem. An iterative hybrid classification strategy, based on a weighted combination of estimated posteriors of a linear and quadratic classifier, is used to update both the automatically selected training samples and the segmentation, increasing reliability and final accuracy, especially for those challenging images, where the contrast between the background skin and lesion is low.http://dx.doi.org/10.1155/2011/972648 |
| spellingShingle | Maciel Zortea Stein Olav Skrøvseth Thomas R. Schopf Herbert M. Kirchesch Fred Godtliebsen Automatic Segmentation of Dermoscopic Images by Iterative Classification International Journal of Biomedical Imaging |
| title | Automatic Segmentation of Dermoscopic Images by Iterative Classification |
| title_full | Automatic Segmentation of Dermoscopic Images by Iterative Classification |
| title_fullStr | Automatic Segmentation of Dermoscopic Images by Iterative Classification |
| title_full_unstemmed | Automatic Segmentation of Dermoscopic Images by Iterative Classification |
| title_short | Automatic Segmentation of Dermoscopic Images by Iterative Classification |
| title_sort | automatic segmentation of dermoscopic images by iterative classification |
| url | http://dx.doi.org/10.1155/2011/972648 |
| work_keys_str_mv | AT macielzortea automaticsegmentationofdermoscopicimagesbyiterativeclassification AT steinolavskrøvseth automaticsegmentationofdermoscopicimagesbyiterativeclassification AT thomasrschopf automaticsegmentationofdermoscopicimagesbyiterativeclassification AT herbertmkirchesch automaticsegmentationofdermoscopicimagesbyiterativeclassification AT fredgodtliebsen automaticsegmentationofdermoscopicimagesbyiterativeclassification |