Identifikasi Tumor Otak Menggunakan Convolutional Neural Network Arsitektur NasNetMobile Dengan Optimasi Wiener Filter
DOI:
https://doi.org/10.26418/pf.v13i3.77722Abstract
Telah dilakukan identifikasi keberadaan tumor otak pada citra Magnetic resonance imaging (MRI) menggunakan metode convolutional neural network (CNN). Proses identifikasi dimulai dari preprocessing citra, yang dilanjutkan dengan CNN arsitektur NasNetMobile. Pada tahap preprocessing, citra dipotong dan disesuaikan ukurannya agar seragam. Proses grayscaling citra kemudian dilakukan sebagai masukan bagi proses ekualisasi histogram. Noise pada citra hasil ekualisasi direduksi menggunakan metode wiener filter dengan nilai K 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, dan 1. Deteksi tepi menggunakan operator sobel dilakukan pada citra biner yang telah difilter tersebut. Citra hasil pengolahan kemudian digunakan pada proses Identifikasi tumor otak menggunakan CNN arsitektur NasNetMobile. Hasil penelitian menunjukan bahwa akurasi tertinggi (95,6%) diperoleh pada model dengan nilai K = 0.4. Tahap preprocessing citra sangat menentukan keakuratan proses identifikasi.
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Date: 24-05-2023
Prisma Fisika
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