Supervised segmentation of polycystic kidneys: A new application for stereology data

Joshua D. Warner, Maria V. Irazabal, Ganapathy Krishnamurthi, Bernard F. King, Vicente E. Torres, Bradley J. Erickson

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

Stereology is a volume estimation method, typically applied to diagnostic imaging examinations in population studies where planimetry is too time-consuming (Chapman et al. Kidney Int 64:1035-1045, 2003), to obtain quantitative measurements (Nyengaard J Am Soc Nephrol 10:1100-1123, 1999, Michel and Cruz-Orive J Microsc 150:117-136, 1988) of certain structures or organs. However, true segmentation is required in order to perform advanced analysis of the tissues. This paper describes a novel method for segmentation of region(s) of interest using stereology data as prior information. The result is an efficient segmentation method for structures that cannot be easily segmented using other methods.

Original languageEnglish (US)
Pages (from-to)514-519
Number of pages6
JournalJournal of Digital Imaging
Volume27
Issue number4
DOIs
StatePublished - Aug 2014

Keywords

  • 3D imaging (three-dimensional imaging)
  • 3D segmentation
  • Biomedical image analysis
  • Boundary extraction
  • Data extraction
  • Digital image processing
  • Fuzzy logic
  • Image analysis
  • Image segmentation
  • MR imaging
  • Magnetic resonance imaging
  • Planimetry
  • Polycystic kidney disease
  • Python
  • Segmentation

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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