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

Medical Physics 2022-03-08 v1 Computer Vision and Pattern Recognition Image and Video Processing

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.

Keywords

Cite

@article{arxiv.2203.03338,
  title  = {Joint brain tumor segmentation from multi MR sequences through a deep convolutional neural network},
  author = {Farzaneh Dehghani and Alireza Karimian and Hossein Arabi},
  journal= {arXiv preprint arXiv:2203.03338},
  year   = {2022}
}
R2 v1 2026-06-24T10:04:27.105Z