Title :
Automatic brain tumor extraction from T1-weighted coronal MRI using fast bounding box and dynamic snake
Author :
Tao Xu ; Mandal, Mrinal
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
Brain tumor segmentation from MRI data is an important but challenging task. This paper presents an efficient and fully automatic brain tumor segmentation technique. The proposed technique includes a fuzzy C-means (FCM) based preprocessing to enhance the quality of T1-weighted coronal MR images, a fast bounding box (FBB) detection algorithm to locate a rectangle around tumor, and a new dynamic snake using modified Hausdorff distance (MHD) for the final tumor extraction.
Keywords :
biomedical MRI; brain; fuzzy systems; image segmentation; medical image processing; neurophysiology; tumours; MRI data; T1-weighted coronal MR imaging; automatic brain tumor extraction; brain tumor segmentation; dynamic snake; fast bounding box detection algorithm; fully automatic brain tumor segmentation technique; fuzzy C-means based preprocessing; modified Hausdorff distance; Computers; Hemorrhaging; Humans; Image segmentation; Magnetic resonance imaging; Random access memory; Tumors; Algorithms; Biostatistics; Brain Neoplasms; Databases, Factual; Diagnosis, Computer-Assisted; Humans; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6345963
