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  • Peneliti DIKE UGM Kembangkan Algoritma Cerdas untuk Tingkatkan Kualitas Citra Medis MRI

Peneliti DIKE UGM Kembangkan Algoritma Cerdas untuk Tingkatkan Kualitas Citra Medis MRI

  • Kegiatan
  • 22 Mei 2025, 06.34
  • Oleh: wimbono
  • 0

Yogyakarta, 21 Mei 2025 – Tim peneliti dari Departemen Ilmu Komputer dan Elektronika Universitas Gadjah Mada (UGM) berhasil mengembangkan algoritma baru untuk meningkatkan kualitas pencitraan medis, khususnya Magnetic Resonance Imaging (MRI). Penelitian ini telah dipublikasikan dalam jurnal Engineering, Technology & Applied Science Research Vol. 15, No. 4, 2025 – jurnal internasional bereputasi yang terindeks Scopus Q2.

Penelitian berjudul “An Improved Cuckoo Search Algorithm with Dynamic Parameters and Hybrid Distribution for Enhanced CLAHE” ini dilakukan oleh Sri Huning Anwariningsih yang merupakan mahasiswa Program Doktor Ilmu Komputer DIKE UGM dengan Tim Promotor Wahyono, S.Kom., Ph.D., dan Dr. Raden Sumiharto, S.Si., M.Kom. Mereka merancang algoritma Dynamic-Hybrid Cuckoo Search Algorithm (DH-CSA) untuk mengoptimalkan metode Contrast Limited Adaptive Histogram Equalization (CLAHE) dalam meningkatkan kontras citra MRI.

“CLAHE merupakan teknik penting dalam pencitraan medis, namun kualitas hasilnya sangat bergantung pada parameter yang digunakan. Di sinilah peran algoritma optimasi menjadi krusial,” jelas Huning.

DH-CSA memperkenalkan dua inovasi utama: penyesuaian dinamis pada parameter step size dan discovery rate, serta penerapan distribusi hibrida (gabungan distribusi normal dan uniform) untuk meningkatkan proses pencarian solusi. Kombinasi ini terbukti menghasilkan gambar dengan kontras lebih tinggi dan detail struktur yang lebih terjaga.

Metode ini diuji menggunakan 290 citra MRI otak dari dataset ABIDE (Autism Brain Imaging Data Exchange) dan menunjukkan performa yang unggul dibandingkan metode optimasi lainnya seperti PSO-CLAHE dan FA-CLAHE. Nilai Peak Signal-to-Noise Ratio (PSNR) mencapai 45,54 dB, Structural Similarity Index (SSIM) sebesar 0,97, serta nilai Feature Similarity Index (FSIM) mendekati sempurna, yaitu 0,9995. Semua ini menunjukkan bahwa gambar hasil pemrosesan memiliki kualitas sangat tinggi dan struktur asli yang tetap terjaga. Meski memiliki waktu komputasi lebih tinggi, metode ini sangat ideal untuk aplikasi offline yang membutuhkan akurasi tinggi dalam proses peningkatan kualitas citra, terutama dalam bidang medis.

Penelitian ini memperkuat kontribusi Indonesia dalam pengembangan teknologi medical image processing, dan membuka peluang lebih luas untuk penerapannya dalam sistem diagnosis berbasis citra digital. Penelitian ini sejalan dengan Tujuan Pembangunan Berkelanjutan (SDGs) nomor 3: Good Health and Well-being, khususnya dalam mendukung layanan kesehatan yang lebih presisi dan berkualitas melalui teknologi diagnostik yang lebih canggih.

 

Author :  Wahyono

Editor : Marina

#SDGs3

Tags: SDGs SDGs 3: Kehidupan Sehat dan Sejahtera

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Universitas Gadjah Mada

Departemen Ilmu Komputer dan Elektronika

Fakultas Matematika dan Ilmu Pengetahuan Alam

Universitas Gadjah Mada

Gedung C, Lantai 4

Sekip Utara Bulaksumur Yogyakarta 55281

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