Kidney segmentation in ultrasound via genetic initialization and Active Shape Models with rotation correction

Carlos S. Mendoza, Xin Kang, Nabile Safdar, Emmarie Myers, Craig A Peters, Marius George Linguraru

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations

Abstract

In this paper we present a segmentation method for 2D ultrasound images of the pediatric kidney. Our method relies on minimal user intervention and produces accurate segmentations thanks to a combination of improvements made to the Active Shape Model (ASM) framework. The initialization of the ASM module is based on a Covariance Matrix Adaptation Evolution Strategy (CMA-ES) genetic algorithm that optimizes the pose and the main shape variation modes of the kidney shape model. In order to account for the image formation process in ultrasound, the appearance model is obtained not according to the anatomically corresponding contour landmarks, but to those that exhibit a similar angle of incidence with respect to the wavefront traveling from the probe. The results indicate a median Dice's coefficient of 90.2% and a relative area difference of 10.8% for segmentation of a set of 80 kidney images.

Original languageEnglish (US)
Title of host publicationISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro
Pages69-72
Number of pages4
DOIs
StatePublished - 2013
Event2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 - San Francisco, CA, United States
Duration: Apr 7 2013Apr 11 2013

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
Country/TerritoryUnited States
CitySan Francisco, CA
Period4/7/134/11/13

Keywords

  • Active Shape Models
  • Hydronephrosis
  • Kidney
  • Segmentation
  • Ultrasound

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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