Adaptive segmentation based on multi-classification model for dermoscopy images

doi:10.1007/s11704-015-4391-8

Front. Comput. Sci.

2015, Vol. 9

Issue (5) : 720-728 https://doi.org/10.1007/s11704-015-4391-8

RESEARCH ARTICLE

Adaptive segmentation based on multi-classification model for dermoscopy images

Fengying XIE^1,^*(

),Yefen WU¹,Yang LI¹,Zhiguo JIANG¹,Rusong MENG²

1. Image Processing Center, School of Astronautics, Beihang University, Beijing 100191, China
2. General Hospital of the Air Force, People’s Liberation Army, Beijing 100036, China

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Abstract

Segmentation accuracy of dermoscopy images is important in the computer-aided diagnosis of skin cancer and a wide variety of segmentation methods for dermoscopy images have been developed. Considering that each method has its strengths and weaknesses, a novel adaptive segmentation framework based on multi-classification model is proposed for dermoscopy images. Firstly, five patterns of images are summarized according to the factors influencing segmentation. Then the matching relation is established between each image pattern and its optimal segmentationmethod. Next, the given image is classified into one of the five patterns by the multi-classification model based on BP neural network. Finally, the optimal segmentation method for this image is selected according to the matching relation, and then the image is effectively segmented. Experiments show that the proposed method delivers better accuracy and more robust segmentation results compared with the other seven state-of-the-art methods.

Keywords adaptive segmentation feature extraction pattern classification dermoscopy image

Corresponding Author(s): Fengying XIE

Just Accepted Date: 04 February 2015 Issue Date: 24 September 2015

Cite this article:

Fengying XIE,Yefen WU,Yang LI, et al. Adaptive segmentation based on multi-classification model for dermoscopy images[J]. Front. Comput. Sci., 2015, 9(5): 720-728.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-015-4391-8
https://academic.hep.com.cn/fcs/EN/Y2015/V9/I5/720

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