Klasifikasi Kanker Payudara Menggunakan Residual Neural Network

Reynold Erwandi, Suyanto Suyanto

Abstract


Kanker Payudara menjadi salah satu penyebab kematian yang umum terutama pada kaum wanita. Di Amerika Serikat pada tahun 2015, kanker payudara menjadi jenis kanker yang paling banyak diderita dan menjadi kanker paling mematikan setelah kanker paru-paru. Studi terkait menyatakan bahwa pendeteksi dan penanggulangan secara diri menjadi faktor penting dalam menghadapi kanker payudara. Proses diagnosa kanker payudara secara tradisional memakan waktu yang cukup lama, terlebih lagi para ahli patologi belum 100% yakin atas hasil diagnosa mereka. Oleh karena itu dalam
penelitian ini dibuatlah sebuah sistem dengan bantuan komputer yang dapat membantu para dokter untuk mengklasifikasi jenis sel payudara berdasarkan gambar histopatologi. Dalam penelitian ini, diusulkan sebuah metode menggunakan pendekatan deep convolutional neural network menggunakan arsitektur Residual Neural Network (ResNet) untuk pengklasifikasian berdasarkan gambar histopatologi pada dataset BreakHis. Performa terbaik yang dicapai dalam metode ini mencapai tingkat rata-rata akurasi 99,3% pada pengklasifikasian binary, dan tingkat rata-rata akurasi 94,6% pada pengklasifikasian multi-class yang mana hampir setara dengan kondisi state-ofthe-art saat penelitian ini ditulis.

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DOI: http://dx.doi.org/10.21108/INDOJC.2020.5.1.373

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