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

fYear

2012

fDate

Aug. 28 2012-Sept. 1 2012

Firstpage

444

Lastpage

447

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE

Conference_Location

San Diego, CA

ISSN

1557-170X

Print_ISBN

978-1-4244-4119-8

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/EMBC.2012.6345963

Filename

6345963