arXiv 2203.033382022-03-07physics.med-phcs.CVeess.IV

Joint brain tumor segmentation from multi MR sequences through a deep convolutional neural network

University of Isfahan（伊斯法罕大学）；Geneva University Hospital（日内瓦大学医院）

Farzaneh Dehghani, Alireza Karimian, Hossein Arabi

英文摘要：

Brain tumor segmentation is highly contributive in diagnosing and treatment planning. The manual brain tumor delineation is a time-consuming and tedious task and varies depending on the radiologists skill. Automated brain tumor segmentation is of high importance, and does not depend on either inter or intra-observation. The objective of this study is to automate the delineation of brain tumors from the FLAIR, T1 weighted, T2 weighted, and T1 weighted contrast-enhanced MR sequences through a deep learning approach, with a focus on determining which MR sequence alone or which combination thereof would lead to the highest accuracy therein.

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