Aplikasi Deteksi Tumor Otak Citra MRI Menggunakan Model VGG16
DOI:
https://doi.org/10.29407/gxn7p082Abstract
Tumor otak adalah salah satu penyakit yang sangat serius dan membutuhkan diagnosis serta penanganan yang cepat dan akurat. Citra Magnetic Resonance (MRI) sering digunakan sebagai alat utama untuk mendeteksi tumor otak karena kemampuannya dalam memvisualisasikan jaringan lunak dengan baik. Dalam penelitian ini, penulis menerapkan teknik thresholding dan deteksi tepi sebagai tahap pre-processing citra MRI untuk meningkatkan akurasi model VGG16 dalam mengidentifikasi empat jenis tumor otak yaitu, glioma, meningioma, pituitary, dan normal.
Proses pre-processing citra MRI meliputi resizing dan normalisasi serta penerapan thresholding dan deteksi tepi. Hasil pre-processing kemudian digunakan sebagai input untuk model VGG16 yang sebelumnya telah dilatih. Evaluasi model dilakukan dengan menggunakan metrik klasifikasi akurasi, presisi, recall, dan f1-score. Hasil penelitian menunjukkan bahwa penerapan thresholding dan deteksi tepi dalam pre-processing citra MRI dapat meningkatkan akurasi model VGG16 dalam mengidentifikasi tumor otak dari 87% menjadi 90% ke atas. Peningkatan akurasi ini disebabkan oleh kemampuan teknik pre-processing dalam memperjelas batas-batas struktur anatomi pada citra MRI, sehingga fitur yang relevan dapat lebih efektif diidentifikasi oleh model deep learning.
Keywords:
deteksi tumor otak, edge detection, meningkatkan akurasi##plugins.themes.default.displayStats.downloads##
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