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

Adinegoro, Antonius Fajar and Sutapa, Gusti Ngurah and Gunawan, Anak Agung Ngurah and Anggarani, Ni Kadek Nova and Suardana, Putu and Kasmawan, I. Gde Antha (2023) Classification and Segmentation of Brain Tumor Using EfficientNet-B7 and U-Net. Asian Journal of Research in Computer Science, 15 (3). pp. 1-9. ISSN 2581-8260

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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.

Item Type: Article
Subjects: East India Archive > Computer Science
Depositing User: Unnamed user with email support@eastindiaarchive.com
Date Deposited: 14 Mar 2023 06:09
Last Modified: 05 Sep 2024 11:39
URI: http://ebooks.keeplibrary.com/id/eprint/543

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