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

Farzaneh Dehghani; Alireza Karimian; Hossein Arabi

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arXiv · 2203.03338

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

Farzaneh Dehghani·Alireza Karimian·Hossein Arabi

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Abstract

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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Farzaneh Dehghani, Alireza Karimian, Hossein Arabi. 2022-03-07. Joint brain tumor segmentation from multi MR sequences through a deep convolutional neural network. https://arxiv.org/abs/2203.03338

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