Automatic segmentation of dermoscopy images using saliency combined with Otsu threshold
Segmentation is one of the crucial steps for the computer-aided diagnosis (CAD) of skin cancer with dermoscopy images. To accurately extract lesion borders from dermoscopy images, a novel automatic segmentation algorithm using saliency combined with Otsu threshold is proposed in this paper, which in...
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| Vydané v: | Computers in biology and medicine Ročník 85; s. 75 - 85 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
United States
Elsevier Ltd
01.06.2017
Elsevier Limited |
| Predmet: | |
| ISSN: | 0010-4825, 1879-0534, 1879-0534 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | Segmentation is one of the crucial steps for the computer-aided diagnosis (CAD) of skin cancer with dermoscopy images. To accurately extract lesion borders from dermoscopy images, a novel automatic segmentation algorithm using saliency combined with Otsu threshold is proposed in this paper, which includes enhancement and segmentation stages. In the enhancement stage, prior information on healthy skin is extracted, and the color saliency map and brightness saliency map are constructed respectively. By fusing the two saliency maps, the final enhanced image is obtained. In the segmentation stage, according to the histogram distribution of the enhanced image, an optimization function is designed to adjust the traditional Otsu threshold method to obtain more accurate lesion borders. The proposed model is validated from enhancement effectiveness and segmentation accuracy. Experimental results demonstrate that our method is robust and performs better than other state-of-the-art methods.
•A novel segmentation method based on saliency combined with Otsu threshold is proposed for dermoscopy images.•The saliency map based on healthy skin priors is presented to enhance lesion object.•The traditional Otsu threshold method is improved through an optimization function.•Dermoscopy images are accurately segmented through the proposed segmentation method. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 0010-4825 1879-0534 1879-0534 |
| DOI: | 10.1016/j.compbiomed.2017.03.025 |