  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.
