Universiti Teknologi Malaysia Institutional Repository

Medical image visual appearance improvement using bihistogram bezier curve contrast enhancement: data from the osteoarthritis initiative

Gan, Hong Seng and Tan, Tian Swee and Abdul Karim, Ahmad Helmy and Sayuti, Khairil Amir and Abdul Kadir, Mohammed Rafiq and Tham, Weng Kit and Wong, Liang Xuan and Chaudhary, Kashif Tufail and Ali, Jalil and Yupapin, Preecha P.P. (2014) Medical image visual appearance improvement using bihistogram bezier curve contrast enhancement: data from the osteoarthritis initiative. Scientific World Journal . ISSN 1537-744X

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Official URL: http://dx.doi.org/10.1155/2014/294104

Abstract

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

Item Type:Article
Uncontrolled Keywords:contrast enhancement, histogram, image enhancement, image processing
Subjects:Q Science > QH Natural history
Divisions:Biosciences and Medical Engineering
ID Code:53419
Deposited By: Siti Nor Hashidah Zakaria
Deposited On:01 Feb 2016 11:54
Last Modified:28 Jul 2018 14:26

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