Medical image contrast enhancement using spline concept: Data from the osteoarthritis initiative

Journal of Medical Imaging and Health Informatics

Volumn 4, Issue 4, 2014, Pages 511-520

  Gan, Hong Seng ^a   Tan, Tian Swee ^a   Kadir, Mohammed Rafiq Bin Abdul ^a   Karim, Ahmad Helmy Abdul ^b   Sayuti, Khairil Amir ^b   Wong, Liang Xuan ^a   Tham, Weng Kit ^a  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

^b SCHOOL OF MEDICAL SCIENCES   (Malaysia)

Author keywords

Brightness Preservation; Contrast Enhancement; Cubic Spline; Histogram Equalization; Visual Quality

Indexed keywords

ARTICLE; BRIGHTNESS; CONTRAST ENHANCEMENT; CONTROLLED STUDY; HISTOGRAM; HUMAN; IMAGE ENHANCEMENT; KNEE OSTEOARTHRITIS; LUMINANCE; NUCLEAR MAGNETIC RESONANCE; NUCLEAR MAGNETIC RESONANCE SCANNER; ORGAN PRESERVATION; VISUAL SYSTEM;

EID: 84907275536     PISSN: 21567018     EISSN: 21567026     Source Type: Journal    
DOI: 10.1166/jmihi.2014.1294     Document Type: Article

References (21)

1. R. Gonzalez and R. Woods, Digital Image Processing 2nd edn., Prentice Hall (2002).
2. K. Yeong-Taeg, Contrast enhancement using brightness preserving bihistogram equalization. Consumer Electronics, IEEE Transactions on 43, 1 (1997).
3. J. B. Zimmerman, S. M. Pizer, E. V. Staab, J. R. Perry, W. McCartney, and B. C. Brenton, An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement. Medical Imaging, IEEE Transactions on 7, 304 (1988).
4. L. Fass, Imaging and cancer: A review. Molecular Oncology 2, 115 (2008).
5. H. Chai, T. Swee, G. Seng, and L. Wee, Multipurpose contrast enhancement on epiphyseal plates and ossification centers for bone age assessment. BioMedical Engineering OnLine 12, 1 (2013).
6. W. Z. W. Ismail and K. S. Sim, Contrast enhancement dynamic histogram equalization for medical image processing application. Int. J. Imaging Syst. Technol. 21, 280 (2011).
7. H. Shim, S. Chang, C. Tao, J.-H. Wang, C. K. Kwoh, and K. T. Bae, Knee cartilage: Efficient and reproducible segmentation on high-spatial-resolution MR images with the semiautomated graph-cut algorithm method1. Radiology 251, 548 (2009).
8. A. Lilik, I. K. E. Purnama, H. Mochamad, and P. M. Hery, Osteoarthritis classification using self organizing map based on gabor kernel and contrast-limited adaptive histogram equalization. The Open Biomedical Engineering Journal 7, 18 (2013).
9. W. Qian, C. Liya, and S. Dinggang, Fast histogram equalization for medical image enhancement, Engineering in Medicine and Biology Society, 2008, EMBS 2008, 30th Annual International Conference of the IEEE (2008), pp. 2217-2220.
10. W. Yu, C. Qian, and Z. Baomin, Image enhancement based on equal area dualistic sub-image histogram equalization method. Consumer Electronics, IEEE Transactions on 45, 68 (1999).
11. C. Soong-Der and A. R. Ramli, Minimum mean brightness error bi-histogram equalization in contrast enhancement. Consumer Electronics, IEEE Transactions on 49, 1310 (2003).
12. M. Abdullah-Al-Wadud, M. H. Kabir, M. A. A. Dewan, and C. Oksam, A dynamic histogram equalization for image contrast enhancement. Consumer Electronics, IEEE Transactions on 53, 593 (2007).
13. K. Wongsritong, K. Kittayaruasiriwat, F. Cheevasuvit, K. Dejhan, and A. Somboonkaew, Contrast enhancement using multipeak histogram equalization with brightness preserving, Circuits and Systems, 1998, IEEE APCCAS 1998, The 1998 IEEE Asia-Pacific Conference on, Bangkok, Thailand (1998), pp. 455-458.
14. S.-D. Chen and A. R. Ramli, Contrast enhancement using recursive meanseparate histogram equalization for scalable brightness preservation. IEEE Trans. on Consum. Electron. 49, 1301 (2003).
15. K. S. Sim, C. P. Tso, and Y. Y. Tan, Recursive sub-image histogram equalization applied to gray scale images. Pattern Recognition Letters 28, 1209 (2007).
16. M. Kim and C. Min, Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement. Consumer Electronics, IEEE Transactions on 54, 1389 (2008).
17. F. Eckstein, M. Hudelmaier, W. Wirth, B. Kiefer, R. Jackson, J. Yu, C. B. Eaton, and E. Schneider, Double echo steady state magnetic resonance imaging of knee articular cartilage at 3 Tesla: A pilot study for the osteoarthritis initiative. Annals of the Rheumatic Diseases 65, 433 (2006).
18. H. Gudbjartsson and S. Patz, The rician distribution of noisy mri data. Magnetic Resonance in Medicine 34, 910 (1995).
19. F. Eckstein, G. Ateshian, R. Burgkart, D. Burstein, F. Cicuttini, B. Dardzinski, M. Gray, T. M. Link, S. Majumdar, T. Mosher, C. Peterfy, S. Totterman, J. Waterton, C. S. Winalski, and D. Felson, Proposal for a nomenclature for magnetic resonance imaging based measures of articular cartilage in osteoarthritis. Osteoarthritis and Cartilage 14, 974 (2006).
20. A. Ziaei, H. Yeganeh, K. Faez, and S. Sargolzaei, A novel approach for contrast enhancement in biomedical images based on histogram equalization, BioMedical Engineering and Informatics, 2008, BMEI 2008, International Conference on, Sanya, Hainan, China (2008), pp. 855-858.
21. H. Gan, T. T. Swee, A. H. A. Karim, K. A. Sayuti, M. R. A. Kadir, W. Tham, L. Wong, K. T. Chaudhary, J. Ali, and P. P. Yupapin, Medical image visual appearance improvement using bihistogram bezier curve contrast enhancement: Data from the osteoarthritis initiative. The World Scientific Journal 2014, 1 (2014).