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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computers in biology and medicine Jg. 85; S. 75 - 85
Hauptverfasser: Fan, Haidi, Xie, Fengying, Li, Yang, Jiang, Zhiguo, Liu, Jie
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Elsevier Ltd 01.06.2017
Elsevier Limited
Schlagworte:
Accuracy
Algorithms
Automatic segmentation
Automation
Borders
Brightness
CAD
Cancer
Cluster Analysis
Color
Computer aided design
Computer-aided diagnosis
Databases, Factual
Dermatology
Dermoscopy - methods
Dermoscopy images
Diagnosis
Genetic algorithms
Humans
Image Interpretation, Computer-Assisted - methods
Image processing
Image segmentation
Internal Medicine
International conferences
Medical diagnosis
Melanoma
Methods
Microscopy
Neurosciences
Optimization
Other
Pattern recognition
Researchers
Robustness
Saliency
Skin cancer
Skin Neoplasms - diagnostic imaging
State of the art
Threshold
Saliency
Automatic segmentation
Dermoscopy images
Computer-aided diagnosis
Threshold
ISSN:0010-4825, 1879-0534, 1879-0534
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
Bibliographie: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