Renal Cortex Segmentation on Computed Tomography

  • Xinjian Chen
  • Dehui Xiang
  • Wei Ju
  • Heming Zhao
  • Jianhua Yao


The current procedure of renal cortex segmentation is subjective and tedious. This chapter introduces an automated framework for renal cortex segmentation on contrast-enhanced abdominal CT images. The framework consists of four parts: first, an active appearance model (AAM) is built using a set of training images; second, the AAM is refined by live wire (LW) method to initialize the shape and location of the kidney; third, an iterative graph cut-oriented active appearance model (IGC-OAAM) method is applied to segment the kidney; Finally, the identified kidney contour is used as shape constraints for renal cortex segmentation which is also based on IGC-OAAM. The chapter also discusses several other state-of-art techniques for segmentation and modeling of the kidneys.


Compute Tomography Image Training Image Renal Cortex Active Appearance Model Active Shape Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Xinjian Chen
    • 1
  • Dehui Xiang
    • 1
  • Wei Ju
    • 1
  • Heming Zhao
    • 1
  • Jianhua Yao
    • 2
  1. 1.School of Electronics and Information EngineeringSoochow UniversitySuzhouChina
  2. 2.Department of Radiology and Imaging SciencesNational Institute of HealthBethesdaUSA

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