A generalized contrast enhancement approach for knee MR images

Knee Osteoarthritis (OA) is a most prevalent joint disease that can be diagnosed by measuring physiology and morphology of knee joint organs using Magnetic Resonance Imaging (MRI). Measurement of morphological changes in the knee joint organs is a highly challenging task as it requires interpretatio...

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Main Authors: Gandhamal, A., Talbar, S., Gajre, S., Hani, A.F.M., Kumar, D.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.20134 /
Published: Institute of Electrical and Electronics Engineers Inc. 2017
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016100434&doi=10.1109%2fICONSIP.2016.7857499&partnerID=40&md5=151ab29294c23e2c47437024f99ac9a7
http://eprints.utp.edu.my/20134/
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spelling utp-eprints.201342018-04-22T14:42:17Z A generalized contrast enhancement approach for knee MR images Gandhamal, A. Talbar, S. Gajre, S. Hani, A.F.M. Kumar, D. Knee Osteoarthritis (OA) is a most prevalent joint disease that can be diagnosed by measuring physiology and morphology of knee joint organs using Magnetic Resonance Imaging (MRI). Measurement of morphological changes in the knee joint organs is a highly challenging task as it requires interpretation and analysis from MR images acquired using different MR pulse sequences. In general, most knee MR images acquired in clinical routines exhibit insignificant tissue contrast and low background luminance in the regions presenting different tissues. This results in the difficulties for further processing and quantitative measurement. In this paper, a method for contrast enhancement in knee MR images acquired using different MR pulse sequences is presented. Local Gray Level Transformation using S-curve technique that has originated from original Gray Level Transform is developed and tested on 6 different knee MR image sequences. The performance of the developed technique is measured by calculating Enhancement Measure (EME), Feature Similarity Index Measure (FSIM) and Absolute Mean Brightness Error (AMBE) and comparing results with existing methods such as Histogram Equalization (THE) and Bi-histogram Based Histogram Equalization (BBHE). Results show significant improvements over existing methods in resolving improper brightness and contrast distribution issues that will contribute to the development of quantitative methods for morphological assessment of knee joint osteoarthritis. © 2016 IEEE. Institute of Electrical and Electronics Engineers Inc. 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016100434&doi=10.1109%2fICONSIP.2016.7857499&partnerID=40&md5=151ab29294c23e2c47437024f99ac9a7 Gandhamal, A. and Talbar, S. and Gajre, S. and Hani, A.F.M. and Kumar, D. (2017) A generalized contrast enhancement approach for knee MR images. 2016 International Conference on Signal and Information Processing, IConSIP 2016 . http://eprints.utp.edu.my/20134/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Knee Osteoarthritis (OA) is a most prevalent joint disease that can be diagnosed by measuring physiology and morphology of knee joint organs using Magnetic Resonance Imaging (MRI). Measurement of morphological changes in the knee joint organs is a highly challenging task as it requires interpretation and analysis from MR images acquired using different MR pulse sequences. In general, most knee MR images acquired in clinical routines exhibit insignificant tissue contrast and low background luminance in the regions presenting different tissues. This results in the difficulties for further processing and quantitative measurement. In this paper, a method for contrast enhancement in knee MR images acquired using different MR pulse sequences is presented. Local Gray Level Transformation using S-curve technique that has originated from original Gray Level Transform is developed and tested on 6 different knee MR image sequences. The performance of the developed technique is measured by calculating Enhancement Measure (EME), Feature Similarity Index Measure (FSIM) and Absolute Mean Brightness Error (AMBE) and comparing results with existing methods such as Histogram Equalization (THE) and Bi-histogram Based Histogram Equalization (BBHE). Results show significant improvements over existing methods in resolving improper brightness and contrast distribution issues that will contribute to the development of quantitative methods for morphological assessment of knee joint osteoarthritis. © 2016 IEEE.
format Article
author Gandhamal, A.
Talbar, S.
Gajre, S.
Hani, A.F.M.
Kumar, D.
spellingShingle Gandhamal, A.
Talbar, S.
Gajre, S.
Hani, A.F.M.
Kumar, D.
A generalized contrast enhancement approach for knee MR images
author_sort Gandhamal, A.
title A generalized contrast enhancement approach for knee MR images
title_short A generalized contrast enhancement approach for knee MR images
title_full A generalized contrast enhancement approach for knee MR images
title_fullStr A generalized contrast enhancement approach for knee MR images
title_full_unstemmed A generalized contrast enhancement approach for knee MR images
title_sort generalized contrast enhancement approach for knee mr images
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016100434&doi=10.1109%2fICONSIP.2016.7857499&partnerID=40&md5=151ab29294c23e2c47437024f99ac9a7
http://eprints.utp.edu.my/20134/
_version_ 1741196323486433280
score 11.62408

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