A multiscale approach to contour fitting for MR images

Daniel Rueckert, Peter Burger

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations

Abstract

We present a new multiscale contour fitting process which combines information about the image and the contour of the object at different levels of scale. The algorithm is based on energy minimizing deformable models but avoids some of the problems associated with these models. The segmentation algorithm starts by constructing a linear scale-space of an image through convolution of the original image with a Gaussian kernel at different levels of scale, where the scale corresponds to the standard deviation of the Gaussian kernel. At high levels of scale large scale features of the objects are preserved while small scale features, like object details as well as noise, are suppressed. In order to maximize the accuracy of the segmentation, the contour of the object of interest is then tracked in scale-space from coarse to fine scales. We propose a hybrid Multi-Temperature Simulated Annealing optimization to minimize the energy of the deformable model. At high levels of scale the SA optimization is started at high temperatures, enabling the SA optimization to find a global optimal solution. At lower levels of scale the SA optimization is started at lower temperatures (at the lowest level the temperature is close to 0). This enforces a more deterministic behaviour of the SA optimization at lower scales and leads to an increasingly local optimization as high energy barriers can not be crossed. The performance and robustness of the algorithm have been tested on spin-echo MR images of the cardiovascular system. The task was to segment the ascending and descending aorta in 15 datasets of different individuals in order to measure regional aortic compliance. The results show that the algorithm is able to provide more accurate segmentation results than the classic contour fitting process and is at the same time very robust to noise and initialization.

Original languageEnglish
Pages (from-to)289-300
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume2710
DOIs
StatePublished - 1996
Externally publishedYes
EventMedical Imaging 1996 Image Processing - Newport Beach, CA, United States
Duration: 12 Feb 199615 Feb 1996

Keywords

  • Contour Fitting
  • Deformable Models
  • Image Segmentation
  • Iterated Conditional Modes (ICM)
  • Multiresolution Deformable Models
  • Multiscale Image Analysis
  • Simulated Annealing (SA)

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