Iterative Quadtree Decomposition Segmentation of Liver MR Image

Author

Dongxiang, Chi ; Tiankun, Lu

Author_Institution

Sch. of Electron. & Inf., Shanghai Dianji Univ., Shanghai, China

Volume

3

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

527

Lastpage

529

Abstract

An improved iterative quadtree decomposition (IQD) algorithm is proposed: starting from a seed point or a ranking order of liver area, a segmentation result of liver in MR image is obtained by a quadtree decomposition, regional morphology operation and ordering of ROI. The IQD algorithm overcomes unfavorable condition of small proportion of liver area in the MR image which makes the segmentation difficult. The segmentation result demonstrates the advantage of the approach and lays foundation for future extraction of tumor.

Keywords

biomedical MRI; feature extraction; image segmentation; iterative methods; liver; medical image processing; quadtrees; tumours; feature extraction; image segmentation; iterative quadtree decomposition; liver MR image; ranking order; regional morphology operation; seed point; tumor; Artificial intelligence; Computational intelligence; Data structures; Image segmentation; Iterative algorithms; Liver neoplasms; Magnetic resonance; Magnetic resonance imaging; Morphology; Pixel; MRI; iterative quadtree decomposition; liver;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-3835-8

Electronic_ISBN

978-0-7695-3816-7

Type

conf

DOI

10.1109/AICI.2009.152

Filename

5376796