Analisis Perbaikan Kualitas Citra Menggunakan CLAHE dan HE Pada Citra X-Ray Covid-19 dan Pneumonia

Kana Saputra S, Insan Taufik, Dinda Farahdilla Dharma, Mhd Hidayat

Sari


Abstrak
Pneumonia banyak terjadi di negara berkembang dengan sistem kesehatan yang rapuh karena kompleksitasnya, termasuk negara Indonesia. Pneumonia biasanya disebabkan oleh virus atau bakteri yang telah terpapar di lingkungan atau diteruskan oleh orang lain yang terinfeksi dengan cara kontak langsung atau menghirup udara dari batuk atau bersin. Salah satu virus yang saat ini menjadi perhatian dunia adalah Virus Corona atau dapat dikatakan sebagai Covid-19 yang juga menyerang paru-paru manusia. X-ray merupakan teknik yang paling umum digunakan oleh seluruh rumah sakit untuk melihat kasus Covid-19 dikarenakan biaya yang lebih murah dibandingkan dengn CT. Namun, citra X-ray tidak dapat dengan mudah membedakan jaringan lunak dengan kontras yang buruk untuk membatasi dosis paparan pada pasien. Oleh karena itu, penelitian ini bertujuan untuk melakukan perbaikan kualitas citra dari hasil citra X-ray pasien menggunakan metode Contrast Limited Adaptive Histogram Equalization (CLAHE) dan Histogram Equalization (HE). Hasil analisis menunjukkan bahwa metode CLAHE mampu memberikan citra yang lebih jelas pada citra citra X-Ray Covid-19, X-Ray Pneumonia, dan X-Ray Normal dibandingkan dengan HE.
Kata kunci: covid-19, contrast limited adaptive histogram equalization, histogram equalization, pneumonia

Abstract
Pneumonia is common in developing countries with fragile health systems due to their complexity, including Indonesia. Pneumonia is usually caused by viruses or bacteria exposed in the environment or by other people who are infected by direct contact or air from coughing or sneezing. One of the viruses that is currently attracting the world's attention is the Corona Virus or can be said as Covid-19 which also attacks the human lungs. X-ray is the most common technique used by all hospitals to see cases of Covid-19 because it is cheaper than CT. However, X-ray images cannot easily distinguish soft tissue with poor contrast to limit the patient's dose of exposure. Therefore, this study aims to improve the image quality of the patient's X-ray images using the Contrast Limited Adaptive Histogram Equalization (CLAHE) and Histogram Equalization (HE) methods. The results of the analysis show that the CLAHE method is able to provide clearer images on Covid-19 X-Ray, Pneumonia X-Ray, and Normal X-Ray images compared to HE.
Keywords: covid-19, contrast limited adaptive histogram equalization, histogram equalization, pneumonia


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Referensi


Chen, Z. M., Fu, J. F., Shu, Q., Chen, Y. H., Hua, C. Z., Li, F. B., … Zhang, Y. Y. (2020). Diagnosis and treatment recommendations for pediatric respiratory infection caused by the 2019 novel coronavirus. World Journal of Pediatrics, 16(3), 240–246. https://doi.org/10.1007/s12519-020-00345-5

Hemdan, E. E.-D., Shouman, M. A., & Karar, M. E. (2020). COVIDX-Net: A Framework of Deep Learning Classifiers to Diagnose COVID-19 in X-Ray Images. Retrieved from http://arxiv.org/abs/2003.11055

Hidayat, J., Usman, Faisal, A., & Syafriwel. (2019). Perbandingan Metode Perbaikan Kualitas Citra Berbasis Histogram Equalization Pada Citra Satelit. Journal of Electrical Technology, 4(3), 111–115.

Maguolo, G., & Nanni, L. (2021). A critic evaluation of methods for COVID-19 automatic detection from X-ray images. Information Fusion, 76(April), 1–7. https://doi.org/10.1016/j.inffus.2021.04.008

Mertiana, W. D., Sardjono, T. A., & Hikmah, N. F. (2020). Peningkatan Kontras Citra Mamografi Digital dengan Menggunakan CLAHE dan Contrast Stretching, 9(2), A222–A227.

Ozturk, T., Talo, M., Yildirim, E. A., Baloglu, U. B., Yildirim, O., & Acharya, U. R. (2020). Automated Detection of COVID-19 Cases using Deep Neural Networks with X-Ray Images. Computers in Biology and Medicine, 121. https://doi.org/10.1016/j.compbiomed.2020.103792

Pranata, A., & Astuti, E. Z. (2017). Pengolahan Citra Berbasis Deteksi Tepi Prewitt Pada Gambar Gigi Manusia. Eksplora Informatika, 6(2), 98–105. Retrieved from https://eksplora.stikom-bali.ac.id/index.php/eksplora/article/view/110/91

Putra, R. E., Tjandrasa, H., & Suciati, N. (2020). Severity classification of non-proliferative diabetic retinopathy using convolutional support vector machine. International Journal of Intelligent Engineering and Systems, 13(4), 156–170. https://doi.org/10.22266/IJIES2020.0831.14

Saifullah, S. (2020). Analisis Perbandingan He Dan Clahe Pada Image Enhancement Dalam Proses Segmenasi Citra Untuk Deteksi Fertilitas Telur. Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI), 9(1), 134. https://doi.org/10.23887/janapati.v9i1.23013

Sazmita, D. T., Efendi, R., & Susilo, B. (2020). Pengolahan Citra Telapak Tangan Manusia Menggunakan Metode Histogram Equalization dan Homomorphic Filtering. Jurnal Rekursif, 8(1), 47–58.

Society, A. T. (2016). What is pneumonia? American Journal of Respiratory and Critical Care Medicine, 193(1), P1–P2. https://doi.org/10.1164/rccm.1931P1

Sulistyawati, Sofiana, L., Amala, S. K., Rokhmayanti, Astuti, F. D., & Nurfita, D. (2020). Pneumonia a neglected disease: A mixed-method study on the case-finding program in Indonesia. AIMS Public Health, 7(1), 81–91. https://doi.org/10.3934/publichealth.2020008

Tinaliah, & Elizabeth, T. (2020). Peningkatan Kualitas Citra X-Ray Paru-Paru Pasien Covid-19 Menggunakan Metode Contrast Limited Adaptive Histogram Equalization. Jurnal Teknologi Informasi, 4(2), 345–349. Retrieved from http://www.jurnal.una.ac.id/index.php/jurti/article/view/1709

Watkins, K., Wright, S., Le Nestour, A., Mathieson, K., Joana, A., Leigh, C., … Ahmar, S. (2017). Fighting for breath: a call to action on childhood pneumonia, (November).

Zhao, D., Yao, F., Wang, L., Zheng, L., Gao, Y., Ye, J., … Gao, R. (2020). A comparative study on the clinical features of coronavirus 2019 (COVID-19) pneumonia with other pneumonias. Clinical Infectious Diseases, 71(15), 756–761. https://doi.org/10.1093/cid/ciaa247

Zu, Z. Y., Jiang, M. Di, Xu, P. P., Chen, W., Ni, Qi. Q., Lu, G. M., & Zhang, L. J. (2020). Coronavirus disease 2019 (Covid-19): A pediatric perspective. Journal of the Nepal Medical Association, 58(227), 525–532. https://doi.org/10.31729/jnma.4977




DOI: https://doi.org/10.31294/ijcit.v6i2.10855

P-ISSN: 2527-449X E-ISSN: 2549-7421
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