title: Renal cortex segmentation using optimal surface search with novel graph construction.
abstract: In this paper, we propose a novel approach to solve the renal cortex segmentation problem, which has rarely been studied. In this study, the renal cortex segmentation problem is handled as a multiple-surfaces extraction problem, which is solved using the optimal surface search method. We propose a novel graph construction scheme in the optimal surface search to better accommodate multiple surfaces. Different surface sub-graphs are constructed according to their properties, and inter-surface relationships are also modeled in the graph. The proposed method was tested on 17 clinical CT datasets. The true positive volume fraction (TPVF) and false positive volume fraction (FPVF) are 74.10% and 0.08%, respectively. The experimental results demonstrate the effectiveness of the proposed method.
authors: Institute of Automation, Chinese Academy of Sciences, China.
authors: Xiuli
authors: X
authors: Li
authors: Xinjian
authors: X
authors: Chen
authors: Jianhua
authors: J
authors: Yao
authors: Xing
authors: X
authors: Zhang
authors: Jie
authors: J
authors: Tian
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003952:Diagnostic Imaging / Q000379:methods*; D004058:Diffusion; D006801:Humans; D007672:Kidney Cortex / Q000473:pathology*; D008953:Models, Anatomic; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods*