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Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images

机译:使用MRI图像的端到端增量深神经网络全自动脑肿瘤分割

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Background and Objective: Nowadays, getting an efficient Brain Tumor Segmentation in Multi-Sequence MR images as soon as possible, gives an early clinical diagnosis, treatment and follow-up. The aim of this study is to develop a new deep learning model for the segmentation of brain tumors. The proposed models are used to segment the brain tumors of Glioblastomas (with both high and low grade). Glioblastomas have four properties: different sizes, shapes, contrasts, in addition, Glioblastomas appear anywhere in the brain.
机译:背景和目的:如今,尽快在多序列MR图像中获得高效的脑肿瘤分割,给药早期临床诊断,治疗和随访。 本研究的目的是为脑肿瘤分割开发一种新的深度学习模型。 所提出的模型用于分割胶质细胞瘤的脑肿瘤(具有高低等级)。 Glioblastomas有四种性质:不同尺寸,形状,对比,此外,Glioblastomas出现在大脑中的任何地方。

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