Segmentation of ultrasound breast images based on a neutrosophic method

Ming Zhang; Ling Zhang; Heng-Da Cheng

doi:10.1117/1.3505854

1 November 2010 Segmentation of ultrasound breast images based on a neutrosophic method

Ming Zhang, Ling Zhang, Heng-Da Cheng

Author Affiliations +

Optical Engineering, Vol. 49, Issue 11, 117001 (November 2010). https://doi.org/10.1117/1.3505854

Abstract

Breast cancer is one of the leading cancers of women. Ultrasound is often used for breast cancer diagnosis because it is harmless, portable, and low-cost. However, the segmentation of breast ultrasound (BUS) images is a difficult task due to their low contrast and speckle noise. Neutrosophy studies the origin, nature, and scope of neutralities and their interactions with different ideational spectra. It is a new philosophy to extend fuzzy logic and is the basis of neutrosophic logic, neutrosophic probability theory, neutrosophic set theory, and neutrosophic statistics. In this paper, we employ neutrosophy and develop a fully automatic algorithm for BUS image segmentation. By using neutrosophy, we integrate two conflicting opinions about speckle in ultrasound image: speckle is noise and speckle includes pattern information. The experiments demonstrate that the proposed approach is accurate, effective, and robust.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Ming Zhang, Ling Zhang, and Heng-Da Cheng "Segmentation of ultrasound breast images based on a neutrosophic method," Optical Engineering 49(11), 117001 (1 November 2010). https://doi.org/10.1117/1.3505854

Published: 1 November 2010

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available