A fuzzy C-means quantization based automatic extraction of rotator cuff tendon tears from ultrasound images-Reference-Cited by-同舟云学术

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A fuzzy C-means quantization based automatic extraction of rotator cuff tendon tears from ultrasound images

Published:2018-07-27 Issue:1 Volume:35 Page:149-158
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Kim Kwang Baek¹,Song Yu-Seon²,Park Hyun Jun³,Song Doo Heon⁴,Choi Byung Kwan⁵

Affiliation:

1. Department of Computer Engineering, Silla University, Busan, Korea

2. Department of Radiology, School of Medicine, Pusan National University, Busan, Korea

3. Division of Software Convergence, Cheongju University, Cheongju, Korea

4. Department of Computer Games, Yong-In SongDam College, Yongin, Korea

5. Department of Neurosurgery, School of Medicine, Pusan National University, Busan, Korea

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference18 articles.

1. Prevalence and riskfactors of a rotator cuff tear in the general population;Yamamoto;J Shoulder Elbow Surg,2010

2. Surgical repair of chronicrotator cuff tears: A prospective long-term study;Cofield;J Bone Joint Surg Am,2001

3. Curvelet based automaticsegmentation of supraspinatus tendon from ultrasound image: A focused assistive diagnostic method;Gupta;Biomedical Engineering Online,2014

4. Shoulder ultrasound: What you need to know;Singh;Indian J Radiol Imag,2012

5. Detection of rotator cuff tears: The value of MRI following ultrasound;Rutten;Eur Radiol,2010

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