Clustering of Tuberculosis and Normal Lungs Based on Image Segmentation Results of Chan-Vese and Canny with K-Means

Fayza Nayla Riyana Putri, Nur Cahyo Hendro Wibowo, Hery Mustofa


The lungs are a vital organ in the human body. If there is interference with lung function, the health of the human body as a whole can be affected. Examination by medical workers needs to be done when there is interference with lung function. This examination can usually be done in various ways, one of which is through a chest X-ray radiographic examination procedure. The application of Artificial Intelligence is growing rapidly in the medical field, especially in diagnostics and treatment management. Artificial intelligence in the medical world can also be applied in processing image data in radiology to analyze X-ray results as supporting diagnostic information. Operators Chan-Vese and Canny are two edge detection operators in digital image processing in an effort to obtain the necessary information based on the shape and size of the object. This study was conducted for clustering of normal and tuberculosis lung conditions based on the results of chest X-ray image segmentation from Chan-Vese and Canny using K-Means Clustering. The results of clustering using K-Means obtained an accuracy value of 77.1%, a precision value of 88%, and a specificity value of 97.2%


Canny; Chan-Vese; Tuberculosis; K-Means; Lungs

Full Text:



T. D. Wulan, E. Purwanti, and M. Yasin, “Deteksi Kanker Paru-Paru Dari Citra Foto Rontgen Menggunakan Jaringan Saraf Tiruan Backpropagation,” UNAIR REPOSITORY, Feb. 11, 2023. (accessed Feb. 11, 2023).

Karimah, Z. I. Nikmah, S. K. Aditya, and E. G. Wahyuni, “Aplikasi Web Untuk Pendeteksi Penyakit Paru – Paru Menggunakan Metode Certainty Factor,” 2019. (accessed Sep. 28, 2022).

P. Andhi et al., “Deteksi COVID-19 Berdasarkan Hasil Rontgen Dada (Chest Xray) Menggunakan Python,” Journal of Information Technology and Computer Science, vol. 1, no. 1, pp. 58–67, Jun. 2021, doi: 10.47111/JOINTECOMS.V1I1.2956.

Y. Kumar, A. Koul, R. Singla, and M. F. Ijaz, “Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda,” J Ambient Intell Humaniz Comput, 2022, doi: 10.1007/S12652-021-03612-Z.

D. Prasetyo, “Klasifikasi Citra X-Ray Paru-Paru Anak Pneumonia dan Non-Pneumonia Menggunakan Metode Segmentasi dan Deteksi Tepi,” 2020, Accessed: Sep. 22, 2022. [Online]. Available:;jsessionid=A40324F8FED71BB89D98E5C98FE00327

P. Getreuer, “Chan-Vese Segmentation,” Image Processing On Line, vol. 2, pp. 214–224, Aug. 2012, doi: 10.5201/IPOL.2012.G-CV.

R. J. Hemalatha et al., “Active Contour Based Segmentation Techniques for Medical Image Analysis,” Medical and Biological Image Analysis, Jul. 2018, doi: 10.5772/INTECHOPEN.74576.

E. S. Nur Aisyah, P. Widanti, A. Hayat, S. Yulinda Prasetya, and Helmi Iskandar, “Analisis Kemiripan Pola Citra Digital Menggunakan Metode Euclidean,” SEMNASTEKNOMEDIA, 2015. (accessed Feb. 11, 2023).

P. Amoako-Yirenkyi, J. K. Appati, I. K. Dontwi, P. Amoako-Yirenkyi, J. K. Appati, and I. K. Dontwi, “Performance Analysis of Image Smoothing Techniques on a New Fractional Convolution Mask for Image Edge Detection,” Open Journal of Applied Sciences, vol. 6, no. 7, pp. 478–488, Jul. 2016, doi: 10.4236/OJAPPS.2016.67048.

A. N. Hermana and S. Juerman, “Implementasi Algoritma Canny dan Backpropagation dalam Pengenalan Pola Rumah Adat”.

M. Darwis, L. H. Hasibuan, M. Firmansyah, N. Ahady, and R. Tiaharyadini, “Implementation of K-Means clustering algorithm in mapping the groups of graduated or dropped-out students in the Management Department of the National University,” JISA(Jurnal Informatika dan Sains), vol. 4, no. 1, pp. 1–9, Jun. 2021, doi: 10.31326/JISA.V4I1.848.

J. Riyono, S. D. Puspa, and C. E. Pujiastuti, “Simulasi Clustering Provinsi di Indonesia dalam Penyebaran Covid-19 Berdasarkan Indikator Kesehatan Masyarakat Menggunakan Algoritma Gaussian Mixture Model,” Majamath: Jurnal Matematika dan Pendidikan Matematika, 2022. (accessed Feb. 11, 2023).

W. D. Yuniarti, “Dasar-dasar pemrograman dengan Python,” Deepublish, Nov. 2019. (accessed Nov. 23, 2022).



  • There are currently no refbacks.

Office and Secretariat:

Big Data Research Centre
Puzzle Research Data Technology (Predatech)
Laboratory Building 1st Floor of Faculty of Science and Technology
UIN Sultan Syarif Kasim Riau

Jl. HR. Soebrantas KM. 18.5 No. 155 Pekanbaru Riau – 28293
Phone: 085275359942

Click Here for Information

Journal Indexing:

Google Scholar | ROAD | PKP Index | BASE | ESJI | General Impact Factor | Garuda | Moraref | One Search | Cite Factor | Crossref | WorldCat | Neliti  | SINTA | Dimensions | ICI Index Copernicus