A novel breast ultrasound image segmentation algorithm based on neutrosophic similarity score and level set
Computer Methods and Programs in BiomedicinePublished 14 September 2015
Yanhui Guo, Abdulkadir Şengür, Jiawei Tian
Citations84
SJR quartileQ1
SJR score1.13
SNIP1.63
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TL;DR
A new BUS image segmentation algorithm based on neutrosophic similarity score (NSS) and level set algorithm is proposed that is able to segment the BUS images effectively and accurately.
Abstract
Breast ultrasound (BUS) image segmentation is a challenging task due to the speckle noise, poor quality of the ultrasound images and size and location of the breast lesions. In this paper, we propose a new BUS image segmentation algorithm based on neutrosophic similarity score (NSS) and level set algorithm. At first, the input BUS image is transferred to the NS domain via three membership subsets T, I and F, and then, a similarity score NSS is defined and employed to measure the belonging degree to the true tumor region. Finally, the level set method is used to segment the tumor from the background tissue region in the NSS image. Experiments have been conducted on a variety of clinical BUS images. Several measurements are used to evaluate and compare the proposed method's performance. The experimental results demonstrate that the proposed method is able to segment the BUS images effectively and accurately.
Keywords
Computer ScienceMedicineEngineering
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