Title :
Iterative Quadtree Decomposition Segmentation of Liver MR Image
Author :
Dongxiang, Chi ; Tiankun, Lu
Author_Institution :
Sch. of Electron. & Inf., Shanghai Dianji Univ., Shanghai, China
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;
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
DOI :
10.1109/AICI.2009.152
