Segmentasi Citra X-ray Paru dengan Deep Learning
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Abstract
Segmentasi gambar merupakan salah satu hal utama dalam kajian computer vision dan image processing. Salah satu contohnya adalah pemrosesan gambar x-ray paru untuk mengetahui penyakit-penyakit yang ada di dalam paru. U-Net merupakan salah satu model segmentasi yang telah dibuat untuk mempermudah seseorang membangun model untuk segmentasi gambar. U-net bisa digunakan pada gambar apapun. Dari keunggulannya itu peneliti mencoba menggunakan U-Net dikombinasikan dengan Inception, MobileNet dan EfficientNet untuk melakukan segmentasi pada gambar medis x-ray paru. Gambar di resize menjadi 512 x 512 pixel. Augmentasi yang dilakukan adalah zoom range, height shift, width shift dan horizontal flip. Epoch sebanyak 200 dan batch size sebesar 4. Skenario terbaik pada penelitian ini adalah dengan menggunakan U-net Efficientnetb0 dengan nilai dice 0.967 dan Jaccard 0.937.
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