Renal Segmentation from 3D Ultrasound via Fuzzy Appearance Models and Patient-Specific Alpha Shapes

Juan J. Cerrolaza, Nabile Safdar, Elijah Biggs, James Jago, Craig A Peters, Marius George Linguraru

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Ultrasound (US) imaging is the primary imaging modality for pediatric hydronephrosis, which manifests as the dilation of the renal collecting system (CS). In this paper, we present a new framework for the segmentation of renal structures, kidney and CS, from 3DUS scans. First, the kidney is segmented using an active shape model-based approach, tailored to deal with the challenges raised by US images. A weighted statistical shape model allows to compensate the image variation with the propagation direction of the US wavefront. The model is completed with a new fuzzy appearance model and a multi-scale omnidirectional Gabor-based appearance descriptor. Next, the CS is segmented using an active contour formulation, which combines contour-and intensity-based terms. The new positive alpha detector presented here allows to control the propagation process by means of a patient-specific stopping function created from the bands of adipose tissue within the kidney. The performance of the new segmentation approach was evaluated on a dataset of 39 cases, showing an average Dice's coefficient of 0.86±0.05 for the kidney, and 0.74 ± 0.10 for the CS segmentation, respectively. These promising results demonstrate the potential utility of this framework for the US-based assessment of the severity of pediatric hydronephrosis.

Original languageEnglish (US)
Article number7478056
Pages (from-to)2393-2402
Number of pages10
JournalIEEE Transactions on Medical Imaging
Volume35
Issue number11
DOIs
StatePublished - Nov 1 2016

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Keywords

  • Active shape model
  • alpha shape
  • collecting system
  • Gabor filters
  • hydronephrosis
  • image segmentation
  • kidney
  • Ultrasonography

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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