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Research Article Open access CC BY 4.0

Classification and Segmentation of Brain Tumor Using EfficientNet-B7 and U-Net

Antonius Fajar Adinegoro, Gusti Ngurah Sutapa, Anak Agung Ngurah Gunawan, Ni Kadek Nova Anggarani, Putu Suardana, I. Gde Antha Kasmawan

Asian Journal of Research in Computer Science · pp. 1–9 · Published 10 Mar 2023

10.9734/ajrcos/2023/v15i3320

Abstract

Tumors are caused by uncontrolled growth of abnormal cells. Magnetic Resonance Imaging (MRI) is modality that is widely used to produce highly detailed brain images. In addition, a surgical biopsy of the suspected tissue (tumor) is required to obtain more information about the type of tumor. Biopsy takes 10 to 15 days for laboratory testing. Based on a study conducted by Brady in 2016, errors in radiology practice are common, with an estimated daily error rate of 3-5%. Therefore, using the application of artificial intelligence, is expected to simplify and improve the accuracy of doctor's diagnose.

Convolutional neural network U-Net EfficientNet-B7 machine learning brain tumor

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