A statistical method for display and segmentation of 3D image data

Author

Vafadar, Bahareh ; Wu, Bing ; Bones, Phil

Author_Institution

Dept. Electr. & Comput. Eng., Univ. of Canterbury, Christchurch, New Zealand

fYear

2009

fDate

23-25 Nov. 2009

Firstpage

148

Lastpage

152

Abstract

A new method for visualisation and segmentation of vessel structures in 3D magnetic resonance angiography (MRA) images is presented. This method uses a simple statistical model of the information stored along parallel rays within the data set to derive a 2D projection image. Although similar to the maximum image projection (MIP) method, the new method uses a single parameter to achieve a higher contrast-to-noise ratio at a modest computational cost. The same idea is employed to provide a means of segmenting a 3D data set in order to derive a region of support for the purpose of reconstructing image sequences with high temporal resolution.

Keywords

biomedical MRI; data visualisation; image segmentation; image sequences; statistical analysis; 2D projection image; 3D image data segmentation; 3D magnetic resonance angiography; contrast-to-noise ratio; image sequence reconstruction; maximum image projection method; statistical method; vessel structures; Angiography; Computational efficiency; Image reconstruction; Image resolution; Image segmentation; Image sequences; Magnetic resonance; Statistical analysis; Three dimensional displays; Visualization; 3D segmentation; MR angiography; Maximum intensity projection;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Vision Computing New Zealand, 2009. IVCNZ '09. 24th International Conference

Conference_Location

Wellington

ISSN

2151-2205

Print_ISBN

978-1-4244-4697-1

Electronic_ISBN

2151-2205

Type

conf

DOI

10.1109/IVCNZ.2009.5378420

Filename

5378420