Author : HEBA MOHSEN MOHAMED MOSAAD HUSSIEN
CoAuthors : El-Sayed A. El-Dahshan, El-Sayed El-Horbaty, Abdel-Badeeh Salem
Source : ATINER'S Conference Paper Series
Date of Publication : 05/2016
Abstract :
Segmentation is a core process for automatic detection and identification of
brain tumors as it plays a vital role in extracting the information of the
image as measuring and visualizing the brain's anatomical structures and
analyzing the brain changes. From this point the need for accurate and
automatic segmentation techniques has risen as manual segmentation is not
a realistic solution and yet time consuming. This paper examines the various
automated segmentation techniques used by researchers on brain magnetic
resonance images (MRI), giving the most important features for the most
common techniques used in the area of brain tumors. Moreover, a
comparative study to address the differences, limitations, advantages and
challenges of each technique mentioned when being used on brain MRI to
find out their efficiency in this area and to put guidelines that should be
considered when using these techniques.
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