Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative

Well-defined image can assist user to identify region of interest during segmentation. However, complex medical image is usually characterized by poor tissue contrast and low background luminance. The contrast improvement can lift image visual quality, but the fundamental contrast enhancement method...

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Main Authors: Hong-Seng Gan, Tan Tian Swee, Ahmad Helmy Abdul Karim, Khairil Amir Sayuti, Mohammed Rafiq Abdul Kadir, Weng-Kit Tham, Liang-Xuan Wong, Kashif T. Chaudhary, Jalil Ali, Preecha P. Yupapin
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/294104
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author Hong-Seng Gan
Tan Tian Swee
Ahmad Helmy Abdul Karim
Khairil Amir Sayuti
Mohammed Rafiq Abdul Kadir
Weng-Kit Tham
Liang-Xuan Wong
Kashif T. Chaudhary
Jalil Ali
Preecha P. Yupapin
author_facet Hong-Seng Gan
Tan Tian Swee
Ahmad Helmy Abdul Karim
Khairil Amir Sayuti
Mohammed Rafiq Abdul Kadir
Weng-Kit Tham
Liang-Xuan Wong
Kashif T. Chaudhary
Jalil Ali
Preecha P. Yupapin
author_sort Hong-Seng Gan
collection DOAJ
description Well-defined image can assist user to identify region of interest during segmentation. However, complex medical image is usually characterized by poor tissue contrast and low background luminance. The contrast improvement can lift image visual quality, but the fundamental contrast enhancement methods often overlook the sudden jump problem. In this work, the proposed bihistogram Bezier curve contrast enhancement introduces the concept of “adequate contrast enhancement” to overcome sudden jump problem in knee magnetic resonance image. Since every image produces its own intensity distribution, the adequate contrast enhancement checks on the image’s maximum intensity distortion and uses intensity discrepancy reduction to generate Bezier transform curve. The proposed method improves tissue contrast and preserves pertinent knee features without compromising natural image appearance. Besides, statistical results from Fisher’s Least Significant Difference test and the Duncan test have consistently indicated that the proposed method outperforms fundamental contrast enhancement methods to exalt image visual quality. As the study is limited to relatively small image database, future works will include a larger dataset with osteoarthritic images to assess the clinical effectiveness of the proposed method to facilitate the image inspection.
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institution OA Journals
issn 2356-6140
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language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-dc0fbc6e788e42238b3586859ef4b7b22025-08-20T02:21:16ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/294104294104Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis InitiativeHong-Seng Gan0Tan Tian Swee1Ahmad Helmy Abdul Karim2Khairil Amir Sayuti3Mohammed Rafiq Abdul Kadir4Weng-Kit Tham5Liang-Xuan Wong6Kashif T. Chaudhary7Jalil Ali8Preecha P. Yupapin9Department of Biotechnology and Medical Engineering, Faculty of Biosciences and Medical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, MalaysiaDepartment of Biotechnology and Medical Engineering, Medical Device and Technology Group, Material and Manufacturing Research Alliance, Faculty of Biosciences and Medical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, MalaysiaDepartment of Radiology, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, MalaysiaDepartment of Radiology, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, MalaysiaMedical Device and Technology Group, Faculty of Biosciences and Medical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, MalaysiaDepartment of Control Engineering and Mechatronic Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, MalaysiaDepartment of Control Engineering and Mechatronic Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, MalaysiaInstitute of Advanced Photonics Science, Nanotechnology Research Alliance, Universiti Teknologi Malaysia, 81310 Johor Bahru, MalaysiaInstitute of Advanced Photonics Science, Nanotechnology Research Alliance, Universiti Teknologi Malaysia, 81310 Skudai, Johor, MalaysiaDepartment of Physics, Advanced Studies Center, Faculty of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, ThailandWell-defined image can assist user to identify region of interest during segmentation. However, complex medical image is usually characterized by poor tissue contrast and low background luminance. The contrast improvement can lift image visual quality, but the fundamental contrast enhancement methods often overlook the sudden jump problem. In this work, the proposed bihistogram Bezier curve contrast enhancement introduces the concept of “adequate contrast enhancement” to overcome sudden jump problem in knee magnetic resonance image. Since every image produces its own intensity distribution, the adequate contrast enhancement checks on the image’s maximum intensity distortion and uses intensity discrepancy reduction to generate Bezier transform curve. The proposed method improves tissue contrast and preserves pertinent knee features without compromising natural image appearance. Besides, statistical results from Fisher’s Least Significant Difference test and the Duncan test have consistently indicated that the proposed method outperforms fundamental contrast enhancement methods to exalt image visual quality. As the study is limited to relatively small image database, future works will include a larger dataset with osteoarthritic images to assess the clinical effectiveness of the proposed method to facilitate the image inspection.http://dx.doi.org/10.1155/2014/294104
spellingShingle Hong-Seng Gan
Tan Tian Swee
Ahmad Helmy Abdul Karim
Khairil Amir Sayuti
Mohammed Rafiq Abdul Kadir
Weng-Kit Tham
Liang-Xuan Wong
Kashif T. Chaudhary
Jalil Ali
Preecha P. Yupapin
Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative
The Scientific World Journal
title Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative
title_full Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative
title_fullStr Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative
title_full_unstemmed Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative
title_short Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative
title_sort medical image visual appearance improvement using bihistogram bezier curve contrast enhancement data from the osteoarthritis initiative
url http://dx.doi.org/10.1155/2014/294104
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