Title :
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
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;
Conference_Titel :
Image and Vision Computing New Zealand, 2009. IVCNZ '09. 24th International Conference
Conference_Location :
Wellington
Print_ISBN :
978-1-4244-4697-1
Electronic_ISBN :
2151-2205
DOI :
10.1109/IVCNZ.2009.5378420
