Fast and Robust Segmentation of Head in T1-weighted Magnetic Resonance Volumes

Author

Hu, Qingmao ; Qian, Guoyu ; Nowinski, Wieslaw L.

Author_Institution

Biomed. Imaging Lab, Agency for Sci., Technol. & Res., Singapore

fYear

2006

fDate

5-8 Dec. 2006

Firstpage

1

Lastpage

4

Abstract

A fast and robust algorithm to segment the head from T1-weighted magnetic resonance (MR) volumes is presented based on robust determination of threshold from combination of the original volume (through employing the fuzzy c-means clustering which is insensitive to intensity inhomogeneity) and the average axial image (which suppresses the intensity noise), efficient connected component analysis through iterative recursion and fast implementation of morphological operations via decomposition of structuring elements. The algorithm has been validated against 101 data sets with various artifacts

Keywords

biomedical MRI; fuzzy set theory; image segmentation; iterative methods; mathematical morphology; medical image processing; pattern clustering; principal component analysis; T1-weighted magnetic resonance volumes; axial image; component analysis; fuzzy c-means clustering; head; image segmentation; intensity inhomogeneity; intensity noise; iterative recursion; magnetic resonance imaging; morphological operation; structuring element decomposition; Algorithm design and analysis; Clustering algorithms; Image analysis; Image segmentation; Magnetic analysis; Magnetic heads; Magnetic noise; Magnetic resonance; Morphological operations; Noise robustness; Head; Magnetic Resonance Imaging; Robust Segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on

Conference_Location

Singapore

Print_ISBN

1-4244-0341-3

Electronic_ISBN

1-4214-042-1

Type

conf

DOI

10.1109/ICARCV.2006.345356

Filename

4150340