Brain Tumor Segmentation on MR and CT Images Using Fuzzy C-Means and Active Contour Methods

Hamid, M.; Mu'ti, A.; Intifadhah, S. H.; Putri, E. R.

doi:10.55981/aij.2025.1466

Akses terbuka Jurnal SINTA 1

Brain Tumor Segmentation on MR and CT Images Using Fuzzy C-Means and Active Contour Methods

Atom Indonesia · Vol. 51 No. 1 (2025) · hlm. 43–49

DOI: 10.55981/aij.2025.1466
ISSN: 2356-5322, 0126-1568
Terbit: 2025-03-05
Penerbit: National Research and Innovation Agency
Bahasa: eng
Lisensi: creativecommons.org/licenses/by-nc-sa/4.0

Abstrak

A brain tumor is a dangerous brain disease that can attack anyone. It can be described as the abnormal growth of cells in or around the brain, leading to impaired brain function. The first step in diagnosing a brain tumor is to perform an MRI (Magnetic Resonance Imaging) scan. The research aims to analyze the segmentation results of brain tumor MRI and CT (Computed Tomography) images using the Fuzzy C-Means and Active Contour methods. The evaluation is based on ROC parameters, including accuracy, dice score, precision, and sensitivity. The methodology involves analyzing data from secondary image sources, using MATLAB for the segmentation process, and evaluating the results of image segmentation by radiologists. Four ROC measurements were used for each method. The segmentation evaluation results for MRI images show that the Fuzzy C-Means method achieved a precision of 0.92; sensitivity of 0.64; dice score of 0.76; and accuracy of 0.61. The Active Contour method, on the other hand, obtained a precision of 0.97; a sensitivity of 0.99; a dice score of 0.98; and an accuracy of 0.96. For CT images, the Fuzzy C-Means method yielded a precision of 0.72; sensitivity of 0.98; dice score of 0.83; and accuracy of 0.71. The Active Contour method obtained a precision of 0.96; a sensitivity of 0.95; a dice score of 0.96; and an accuracy of 0.92. These results indicate that the Active Contour method, especially with MRI images, provides better segmentation performance. In conclusion, the segmentation results from the Active Contour method can be used as additional information for doctors in diagnosing the presence of tumors.

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23 penulis · 46 tautan kepenulisan bersama · 6 lintas organisasi

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Mulawarman University
Lambung Mangkurat University
University of Indonesia
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Tampilkan sebagai tabel

Rekan penulis	Organisasi	Artikel bersama
Rahmawati Munir	Mulawarman University	3
Sherly Putri	Mulawarman University	2
R. Anthon	Mulawarman University	2
Amar Vijai Nasrulloh	Lambung Mangkurat University	1
Arfan Eko Fahrudin	Lambung Mangkurat University	1
R. Jannah	Mulawarman University	1
A. Putri	Afiliasi tidak diketahui	1
Retno Zurma	Afiliasi tidak diketahui	1
A. Nur	Mulawarman University	1
Kholis Nurhanafi	Mulawarman University	1
Fatimah Kunti Hentihu	Afiliasi tidak diketahui	1
D. R. (Dian) Putri	Mulawarman University	1
Robert Janssen Stevenly	Afiliasi tidak diketahui	1
Prawito Prajitno	University of Indonesia	1
Djarwani Soeharso Soejoko	University of Indonesia	1
Ahmad Zarkasi	Mulawarman University	1
Dadan Hamdani	Mulawarman University	1
Adrianus Inu Natalisanto	Mulawarman University	1
Suhadi Muliyono	Mulawarman University	1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://atomindonesia.brin.go.id/index.php/aij/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.

Metadata asli (oai_dc)

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	<dc:title xml:lang="en-US">Brain Tumor Segmentation on MR and CT Images Using Fuzzy C-Means and Active Contour Methods</dc:title>
	<dc:creator>Hamid, M.</dc:creator>
	<dc:creator>Mu'ti, A.</dc:creator>
	<dc:creator>Intifadhah, S. H.</dc:creator>
	<dc:creator>Putri, E. R.</dc:creator>
	<dc:subject xml:lang="en-US">Active contour; Brain tumor; Fuzzy C-Means; Segmentation</dc:subject>
	<dc:description xml:lang="en-US">A brain tumor is a dangerous brain disease that can attack anyone. It can be described as the abnormal growth of cells in or around the brain, leading to impaired brain function. The first step in diagnosing a brain tumor is to perform an MRI (Magnetic Resonance Imaging) scan. The research aims to analyze the segmentation results of brain tumor MRI and CT (Computed Tomography) images using the Fuzzy C-Means and Active Contour methods. The evaluation is based on ROC parameters, including accuracy, dice score, precision, and sensitivity. The methodology involves analyzing data from secondary image sources, using MATLAB for the segmentation process, and evaluating the results of image segmentation by radiologists. Four ROC measurements were used for each method. The segmentation evaluation results for MRI images show that the Fuzzy C-Means method achieved a precision of 0.92; sensitivity of 0.64; dice score of 0.76; and accuracy of 0.61. The Active Contour method, on the other hand, obtained a precision of 0.97; a sensitivity of 0.99; a dice score of 0.98; and an accuracy of 0.96. For CT images, the Fuzzy C-Means method yielded a precision of 0.72; sensitivity of 0.98; dice score of 0.83; and accuracy of 0.71. The Active Contour method obtained a precision of 0.96; a sensitivity of 0.95; a dice score of 0.96; and an accuracy of 0.92. These results indicate that the Active Contour method, especially with MRI images, provides better segmentation performance. In conclusion, the segmentation results from the Active Contour method can be used as additional information for doctors in diagnosing the presence of tumors.</dc:description>
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	<dc:date>2025-03-05</dc:date>
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	<dc:source xml:lang="en-US">Atom Indonesia; Vol 51, No 1 (2025): APRIL 2025; 43-49</dc:source>
	<dc:source>2356-5322</dc:source>
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	<dc:rights xml:lang="en-US">Copyright (c) 2025 Atom Indonesia</dc:rights>
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