A new 3D model-based minimal path segmentation method for kidney MR images

Ke Li, Baowei Fei

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

7 Scopus citations

Abstract

We present a robust, automated, model-based segmentation method for kidney MR Images. We used dynamic programming and a minimal path approach to detect the optimal path within a weighted graph between two end points. We used an energy function to combine distance and gradient information to guide the marching curve and thus evaluate the best path and span a broken edge. We developed an algorithm to automate the placement of initial end points. Dynamic programming was used to automatically optimize and update end points in the procedure for searching curves. A deformable 3D model was generated using principle component analysis (PCA) and it was used as the prior knowledge for the selection of initial end points and for the evaluation of the best path. We used our minimal path method with surface models to segment mouse kidneys slice-by-slice. The method has been tested for kidney MR images of 44 mice. To quantitatively assess the automatic segmentation method, we compared the automatic segmentation results with manual segmentation. The average and standard deviation of the overlap ratios is 0.93 ± 0.05. The distance error between the automatic and manual segmentation is 0.85 ± 0.41 pixel. The 3D automatic minimal path segmentation method is fast, accurate, and robust. It provides a useful tool for quantification and characterization of kidney MR images.

Original languageEnglish (US)
Title of host publication2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008
PublisherIEEE Computer Society
Pages2342-2344
Number of pages3
ISBN (Print)9781424417483
DOIs
Publication statusPublished - Jan 1 2008
Externally publishedYes
Event2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008 - Shanghai, China
Duration: May 16 2008May 18 2008

Publication series

Name2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008

Conference

Conference2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008
CountryChina
CityShanghai
Period5/16/085/18/08

    Fingerprint

Keywords

  • 3D
  • Deformable model
  • Dynamic Programming
  • Minimal path
  • MRI
  • Polycystic kidney disease
  • Segmentation

ASJC Scopus subject areas

  • Biotechnology
  • Biomedical Engineering

Cite this

Li, K., & Fei, B. (2008). A new 3D model-based minimal path segmentation method for kidney MR images. In 2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008 (pp. 2342-2344). [4535798] (2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008). IEEE Computer Society. https://doi.org/10.1109/ICBBE.2008.918