Granular computing in model based abdominal organs detection

Comput Med Imaging Graph. 2015 Dec:46 Pt 2:121-30. doi: 10.1016/j.compmedimag.2015.03.002. Epub 2015 Mar 10.

Abstract

Detection of region specific voxel is a true challenge in many segmentation procedures. In this study a concept of implementing granular computing in the detection of anatomical structures in abdominal computed tomography (CT) scans is introduced. After proving the usefulness of the information granules to identify voxels that mark certain organs, an automatic model-based approach has been developed. A three-parameter granule that combines the interval and density distribution of voxels has been introduced and employed to identify organ specific voxels of the liver, spleen and kidneys. The specificity of the information granules varies between 90 and 99% for the liver and spleen and over 85% for the kidneys.

Keywords: Abdominal computed tomography (CT); Granular computing; Image processing; Information granules; Model based object extraction.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Anatomic Landmarks / diagnostic imaging
  • Computer Simulation
  • Humans
  • Imaging, Three-Dimensional / methods*
  • Models, Statistical
  • Pattern Recognition, Automated / methods*
  • Radiographic Image Enhancement / methods
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Radiography, Abdominal / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Tomography, X-Ray Computed / methods*
  • Viscera / diagnostic imaging*