METODE PENINGKATAN KUALITAS CITRA MEDIS: LITERATURE REVIEW

Khasnur Hidjah, Agus Harjoko, Anny Kartika Sari

Abstract


Citra medis biasanya memiliki kontras rendah karena diperoleh dari  hasil X-ray. Padahal, penggunaan citra medis semakin banyak dilakukan, terutama dalam hal pengembangan sistem cerdas yang dapat membantu melakukan diagnosis penyakit. Usaha peningkatan kualitas citra medis dilakukan oleh para peneliti antara lain dengan cara pengembangan algoritme yang telah ada.

Artikel ini memberikan ulasan mengenai penelitian-penelitian terkini yang berkaitan dengan peningkatan kualitas citra medis. Ulasan tersebut diharapkan dapat memberikan gambaran kepada para peneliti mengenai metode-metode terkini untuk meningkatkan kualitas citra

Hasil ulasan menunjukkan bahwa metode berbasis region dan metode hybrid memiliki kemampuan yang lebih baik dalam meningkatkan kontras citra dibandingkan dengan metode klasik. Akan tetapi, metode tersebut memiliki kelemahan dalam hal kompleksitas karena memerlukan waktu komputasi yang cukup panjang.


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References


N. Kanwal, A. Girdhar, and S. Gupta, “Region based adaptive contrast enhancement of medical X-ray images,” 5th Int. Conf. Bioinforma. Biomed. Eng. iCBBE 2011, 2011.

T. Kaur and R. K. Sidhu, “Optimized Adaptive Fuzzy based Image Enhancement Techniques,” vol. 9, no. 1, pp. 11–20, 2016.

B. Ganesan, “Hybrid Contrast Enhancement Approach for Medical Image,” no. Ncetict, pp. 9–12, 2013.

R. C. Gonzalez and R. E. Woods, “Digital Image Processing”, Prentice-Hall, 2nd ed. (2002).

S. Deepa, B. Aruna Devi, “A survey on artificial intelligence approaches for medical image classification”, Indian Journal of Science and Technology, 2011

G. Deng, “A generalized unsharp masking algorithm”, IEEE Transactions on Image Processing, 2011

N. Bhalla, N. Kanwal, A. Girdhar and P. K.

Mann, "An Approach for Contras Enhancement of Color Images with the help of Adaptive Region Growing

Approach," Internatioanl Journal of the Computer, vol. 19, no. 3, p. 28033, September-Desember 2011.

A.H. Hustanto, B. Hidayat, Suhardjo, “Peningkatan Kualitas Radiograf Periapikal pada Deteksi Pulpitis Menggunakan Adaptive Region Growing Approach”, Seminar Nasional Universitas PGRI Yogyakarta, 2015

N. Dusturia, B.Hidayat, Suhardjo, “Peningkatan Kualitas Citra Radiograf Periapikal Menggunakan Metode Fast Gray-Level Grouping”, Semnasteknomedia 2016, ISSN : 2302-3805, 6-7 Februari 2016

S. Pizer, E. Amburn, J. Austin, R. Cromartie, A. Geselowitz, T. Greer, B. Romeny, J. Zimmerman, and K.Zuiderveld, “Adaptive histogram equalization and its variations,” Comput. Vis. Graph. Image Process Vol. 39, no. 3, pp. 355– 368, Sep. 1987

J. Stark, “Adaptive image contrast enhancement using generalizations of histogram equalization,” IEEE Trans. Image Process., vol. 9, no. 5, pp. 889–896, May 2000

Hassan, N. Y. and Akamatsu, N., ―Contrast Enhancement technique of dark blurred Image‖, International Journal of Computer Science and Network Security (IJCSNS), Vol. 6, No. 2, 2006.

N. Mesanovic, M. Grgic, M. Males, E. Skejic and M. Smajlovic, "Automatic CT Segmentation of The Lungs with Region

Growing Algorithm," [Online]. Available: http://www.vcl.fer.hr/papers_pdf/Automat ic%20CT%20Image%20Segmentation%2

of%20the%20Lungs%20with%20Regio

n%20Growing%20Algorithm.pdf.

[Accessed 1 November 2016].

R. Pohle and K. D. Toennies, "Segmentation of Medical Image Using Adaptive Region Growing,"

[Online]. Available: http://www.csee.usf.edu/~manohar/Papers /Segmentation/Segmentation%20of%20M edical%20Images%20using%20Adaptive

%20region%20growing.pdf. [Accessed 5 November 2016].

S. Deepa, B. A. Devi, “A survey on artificial intelligence approaches for medical image classification”, Indian Journal of Science and Technology,Volume 4, 2011

R. Lakshmanan, M. S. Nair, M. Wilscy, R Tatavarti, “Automatic contrast enhancement using Selective Grey-Level Grouping”, Int. J. Signal and Imaging Systems Engineering, Vol. 3, No. 2, 2010

Z.Y. Chen, B. R. Abidi, D. L.Page, dan M. A. Abidi. “Gray-Level Grouping (GLG): An Automatic Method For Optimized Image Contrast Enhancement PartI: The Basic Method.” IEEE Transactions on Image Processing, vol. 15, no. 8, August, pp.2290–2302, 2006a.

E. Peli, “Contrast in complex images,” J. Opt. Soc. Amer., vol. 7, no. 10, pp. 2032–2040, 1990

A.B. Kaswar, S. Mamase, S.B. Musa, A.M. Hadi, A. Yuniarty, A.Z. Arifin, “Parameter Sigmoid Transform Contrast Enhancement For Dental Radiograph Classification And Numbering System” Journal of Computer Science and Information, Volume 8, Issue 2, June 2015, 2015

D. Gaertner and K. L. Clark, “On Optimal Parameters for Ant Colony Optimization Algorithms”, “Proceedings of the International Conference on Artificial Intelligence”, vol. 1, (2005), pp. 83-89.

D. Teodorovic, P. Lucic, G. Markovic and M. Dellorco, “Bee colony optimization: principles and applications”, 8th IEEE Seminar on Neural Network Applications in Electrical Engineering, (2006), pp. 151-156.

S. S. Agaian, B. Silver and K. A. Panetta, “Transform coefficient histogram-based image enhancement algorithms using contrast entropy”, IEEE Transactions on Image Processing, vol. 16, no. 3, (2007), pp. 741-758.

ZhiYu Chen, Besma R. Abidi, David L.Page, dan Mongi A. Abidi. “Gray-Level Grouping (GLG): An Automatic Method For Optimized Image Contrast Enhancement—PartI: The Basic Method.” IEEE Transactions on Image Processing, vol. 15, no. 8, August, pp.2290–2302, 2006a

M. F. Khan, E. Khan and Z. A. Abbasi, “Multi segment histogram equalization for brightness preserving contrast enhancement”, Advances in Computer Science, Engineering & Applications, Springer, (2010), pp. 193-202.

G. Raju and M. S. Nair, “A fast and efficient color image enhancement method based on fuzzy-logic and histogram”, International Elsevier Journal of Electronics and Communications, vol. 68, no. 3, (2014), pp. 237–243

Polesel, A. Ramponi, G. Mathews, V.J.Tele Media Int. Ltd., Frankfurt, “Image Enhancement via adaptive unsharp masking”, IEEE Transactions on Image Processing, Vol. 9, Issue. 3, 2002, pp. 505-510

G. Ramponi, “A cubic unsharp masking technique for contrast enhancement,” Signal Process. pp. 211–222, 1998


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