Title :
Segmentation of kidneys from computed tomography using 3D fast GrowCut algorithm
Author :
Gao-Yuan Dai ; Zhi-Cheng Li ; Jia Gu ; Lei Wang ; Xing-Min Li
Author_Institution :
Shenzhen Key Lab. for Low-cost Healthcare, Shenzhen Inst. of Adv. Technol., Shenzhen, China
Abstract :
This paper proposes a fast GrowCut (FGC) algorithm and applies the new algorithm in three-dimensional (3D) kidney segmentation from computed tomography (CT) volume data. Users could mark the object of interest with different labels in CT slices. FGC propagates the labels using monotonically decreasing function and gray features to derive an optimal cut for a given data in space. The gray features play a great role in comparing with neighborhood cells. The experimental results clearly demonstrate nie superiority of FGC in accuracy and speed.
Keywords :
computerised tomography; image segmentation; kidney; medical image processing; 3D fast GrowCut algorithm; 3D kidney segmentation; CT slice labels; computed tomography volume data; gray features; neighborhood cells; Accuracy; Biomedical imaging; Computed tomography; Image segmentation; Kidney; Level set; Three-dimensional displays; Fast Grow Cut (FGC); kidney segmentation; three dimensional segmentation;
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
DOI :
10.1109/ICIP.2013.6738236