Calcaneofibular ligament ultrasound image segmentation based on advanced image processing techniques

Vedpal Singh; Ajay Jangra; S. Parasuraman; John George; I. Elamvazuthi; M. K.A.Ahamed Khan

doi:10.1109/ICCIC.2017.8524428

Calcaneofibular ligament ultrasound image segmentation based on advanced image processing techniques

Vedpal Singh, Ajay Jangra, S. Parasuraman, John George, I. Elamvazuthi, M. K.A.Ahamed Khan

Malaysia Sch of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

2 Citations (Scopus)

Abstract

Calcaneofibular ligament is a fibrous tissue that connects calcaneus bone to fibula bone and it can be visualized using ultrasound imaging. However, due to contrast variation and inhomogeneous textured nature of calcaneofibular ligament tissues in ultrasound images, segmentation of calcaneofibular ligament is a challenging issue. A framework has been proposed for the accurate segmentation of calcaneofibular ligament form ultrasound images to address the issue. The proposed framework comprises of the following: (1) contrast enhancement using adaptive histogram equalization, (2) energy minimization using Fractional Order - Darwinian Particle Swarm Optimization, and (3) calcaneofibular ligament region extraction using Chan-Vese method. The proposed framework is not only helped in accurate segmentation of ultrasound images, it also helpful in efficient computation with lowest time.

Original language	English
Title of host publication	2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017
Editors	N. Krishnan, M. Karthikeyan
Publisher	IEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781509066209
DOIs	https://doi.org/10.1109/ICCIC.2017.8524428
Publication status	Published - 2017
Event	IEEE International Conference on Computational Intelligence and Computing Research 2017 - Tamilnadu, India Duration: 14 Dec 2017 → 16 Dec 2017 Conference number: 8th https://ieeexplore.ieee.org/xpl/conhome/8501353/proceeding (Proceedings)

Conference

Conference	IEEE International Conference on Computational Intelligence and Computing Research 2017
Abbreviated title	ICCIC 2017
Country/Territory	India
City	Tamilnadu
Period	14/12/17 → 16/12/17
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8501353/proceeding (Proceedings)

Keywords

Calcaneofibular ligament
Chan-Vese method
Particle Swarm Optimization
segmentation

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10.1109/ICCIC.2017.8524428

Cite this

Singh, V., Jangra, A., Parasuraman, S., George, J., Elamvazuthi, I., & Khan, M. K. A. A. (2017). Calcaneofibular ligament ultrasound image segmentation based on advanced image processing techniques. In N. Krishnan, & M. Karthikeyan (Eds.), 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICCIC.2017.8524428

@inproceedings{1328944ef01d48f69372cdf72a590884,

title = "Calcaneofibular ligament ultrasound image segmentation based on advanced image processing techniques",

abstract = "Calcaneofibular ligament is a fibrous tissue that connects calcaneus bone to fibula bone and it can be visualized using ultrasound imaging. However, due to contrast variation and inhomogeneous textured nature of calcaneofibular ligament tissues in ultrasound images, segmentation of calcaneofibular ligament is a challenging issue. A framework has been proposed for the accurate segmentation of calcaneofibular ligament form ultrasound images to address the issue. The proposed framework comprises of the following: (1) contrast enhancement using adaptive histogram equalization, (2) energy minimization using Fractional Order - Darwinian Particle Swarm Optimization, and (3) calcaneofibular ligament region extraction using Chan-Vese method. The proposed framework is not only helped in accurate segmentation of ultrasound images, it also helpful in efficient computation with lowest time.",

keywords = "Calcaneofibular ligament, Chan-Vese method, Particle Swarm Optimization, segmentation",

author = "Vedpal Singh and Ajay Jangra and S. Parasuraman and John George and I. Elamvazuthi and Khan, {M. K.A.Ahamed}",

note = "Funding Information: Ministry of Education (MOE), Malaysia for sponsoring the project under FRGS grant entitled {\textquoteleft}Formulation of Mathematical Model for 3-D Reconstruction of Ultrasound Images of MSK Disorders{\textquoteright}. Publisher Copyright: {\textcopyright} 2017 IEEE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; IEEE International Conference on Computational Intelligence and Computing Research 2017, ICCIC 2017 ; Conference date: 14-12-2017 Through 16-12-2017",

year = "2017",

doi = "10.1109/ICCIC.2017.8524428",

language = "English",

editor = "N. Krishnan and M. Karthikeyan",

booktitle = "2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

url = "https://ieeexplore.ieee.org/xpl/conhome/8501353/proceeding",

}

Singh, V, Jangra, A, Parasuraman, S, George, J, Elamvazuthi, I & Khan, MKAA 2017, Calcaneofibular ligament ultrasound image segmentation based on advanced image processing techniques. in N Krishnan & M Karthikeyan (eds), 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017. IEEE, Institute of Electrical and Electronics Engineers, IEEE International Conference on Computational Intelligence and Computing Research 2017, Tamilnadu, India, 14/12/17. https://doi.org/10.1109/ICCIC.2017.8524428

Calcaneofibular ligament ultrasound image segmentation based on advanced image processing techniques. / Singh, Vedpal; Jangra, Ajay; Parasuraman, S. et al.
2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017. ed. / N. Krishnan; M. Karthikeyan. IEEE, Institute of Electrical and Electronics Engineers, 2017.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

TY - GEN

T1 - Calcaneofibular ligament ultrasound image segmentation based on advanced image processing techniques

AU - Singh, Vedpal

AU - Jangra, Ajay

AU - Parasuraman, S.

AU - George, John

AU - Elamvazuthi, I.

AU - Khan, M. K.A.Ahamed

N1 - Conference code: 8th

PY - 2017

Y1 - 2017

N2 - Calcaneofibular ligament is a fibrous tissue that connects calcaneus bone to fibula bone and it can be visualized using ultrasound imaging. However, due to contrast variation and inhomogeneous textured nature of calcaneofibular ligament tissues in ultrasound images, segmentation of calcaneofibular ligament is a challenging issue. A framework has been proposed for the accurate segmentation of calcaneofibular ligament form ultrasound images to address the issue. The proposed framework comprises of the following: (1) contrast enhancement using adaptive histogram equalization, (2) energy minimization using Fractional Order - Darwinian Particle Swarm Optimization, and (3) calcaneofibular ligament region extraction using Chan-Vese method. The proposed framework is not only helped in accurate segmentation of ultrasound images, it also helpful in efficient computation with lowest time.

AB - Calcaneofibular ligament is a fibrous tissue that connects calcaneus bone to fibula bone and it can be visualized using ultrasound imaging. However, due to contrast variation and inhomogeneous textured nature of calcaneofibular ligament tissues in ultrasound images, segmentation of calcaneofibular ligament is a challenging issue. A framework has been proposed for the accurate segmentation of calcaneofibular ligament form ultrasound images to address the issue. The proposed framework comprises of the following: (1) contrast enhancement using adaptive histogram equalization, (2) energy minimization using Fractional Order - Darwinian Particle Swarm Optimization, and (3) calcaneofibular ligament region extraction using Chan-Vese method. The proposed framework is not only helped in accurate segmentation of ultrasound images, it also helpful in efficient computation with lowest time.

KW - Calcaneofibular ligament

KW - Chan-Vese method

KW - Particle Swarm Optimization

KW - segmentation

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DO - 10.1109/ICCIC.2017.8524428

M3 - Conference Paper

AN - SCOPUS:85057949565

BT - 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017

A2 - Krishnan, N.

A2 - Karthikeyan, M.

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE International Conference on Computational Intelligence and Computing Research 2017

Y2 - 14 December 2017 through 16 December 2017

ER -

Singh V, Jangra A, Parasuraman S, George J, Elamvazuthi I, Khan MKAA. Calcaneofibular ligament ultrasound image segmentation based on advanced image processing techniques. In Krishnan N, Karthikeyan M, editors, 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017. IEEE, Institute of Electrical and Electronics Engineers. 2017 doi: 10.1109/ICCIC.2017.8524428

Calcaneofibular ligament ultrasound image segmentation based on advanced image processing techniques

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