FLAIR Brain Tumor Segmentation Using U-Net Convolutional Neural Network
سال انتشار: 1399
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 344
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شناسه ملی سند علمی:
CECCONF11_020
تاریخ نمایه سازی: 6 دی 1399
چکیده مقاله:
A major challenge in brain tumor treatment planning and quantitative evaluation is determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) technique has emerged as a front-line diagnostic tool for brain tumors without ionizing radiation. Manual segmentation of braintumor extent from 3D MRI volumes is a very time-consuming task and the performance is highly relied on operator’s experience. In this context, a reliable fully automatic segmentation method for the brain tumor segmentation is necessary for an efficient measurement of the tumor extent. In this study,we propose a fully automatic method for brain tumor segmentation, which is developed using U-Net based deep convolutional networks.Our method was evaluated on Multimodal Brain Tumor Image Segmentation (BRATS 2015) datasets, which contain 220 high-grade brain tumor and 54 low-gradetumor cases. Crossvalidation has shown that our method can obtain promising segmentation efficiently
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نویسندگان
Shiva sanati
PhD Student, Computer Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
Neda Nosrati
MSC, Computer Engineering Department, Faculty of Engineering, Islamic Azad university of mashhad, Mashhad, Iran