DocumentCode :
1789486
Title :
A preprocessing method for magnetic resonance images of head to improve the performance of brain extraction tools
Author :
Minli Liao ; Weitun Yang ; Xiaojie Zhang ; Min Lu ; Weibei Dou
Author_Institution :
Honor Sch., Harbin Inst. of Technol., Harbin, China
fYear :
2014
fDate :
14-16 Oct. 2014
Firstpage :
121
Lastpage :
125
Abstract :
An automated preprocessing method to improve the performance of brain segmentation with Brain Extraction Tools (BET) is proposed in this paper. It is an automatic decision method of optimal cutting plane of non-brain tissues. This method can be easily integrated into BET and can significantly improve the brain segmentation result for troublesome images. Some clinical 3D T1-weighted MRI data of glioma patients have been used to evaluate this method. Both BET with and without this preprocessing method are carried out, and the results are compared with the “gold-standard” segmented by experts. Two criteria are used to judge the performance, overlay rate and extra rate, where extra rate indicates the ratio of the amount of residual non-brain tissues after segmentation to total non-brain tissues. In the case where no neck area exists the patient head data, both of the BET with and without this preprocessing give the same result. But in the case where the neck is partly included, this proposed preprocessing achieves an average overlay rate of 97.28%, greater than 97% provided by non-preprocessing; and in term of extra rate, the BET with this preprocessing can reach 5.08% that much lower than 29.3% of that without preprocessing.
Keywords :
biomedical MRI; brain; feature extraction; image segmentation; medical image processing; tumours; BET; automated preprocessing method; automatic decision method; average overlay rate; brain extraction tools; brain segmentation performance; clinical 3D T1-weighted MRI data; extra rate; glioma patients; gold-standard; magnetic resonance images; neck area; optimal cutting plane; patient head data; residual nonbrain tissues; total nonbrain tissues; Brain; Head; Image edge detection; Image segmentation; Magnetic resonance imaging; Neck; Three-dimensional displays; Brain Extraction Tool; MRI; brain segmentation; glioma;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2014 7th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4799-5837-5
Type :
conf
DOI :
10.1109/BMEI.2014.7002755
Filename :
7002755
Link To Document :
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