Paper
14 February 2012 Shape-constrained multi-atlas based segmentation with multichannel registration
Author Affiliations +
Abstract
Multi-atlas based segmentation methods have recently attracted much attention in medical image segmentation. The multi-atlas based segmentation methods typically consist of three steps, including image registration, label propagation, and label fusion. Most of the recent studies devote to improving the label fusion step and adopt a typical image registration method for registering atlases to the target image. However, the existing registration methods may become unstable when poor image quality or high anatomical variance between registered image pairs involved. In this paper, we propose an iterative image segmentation and registration procedure to simultaneously improve the registration and segmentation performance in the multi-atlas based segmentation framework. Particularly, a two-channel registration method is adopted with one channel driven by appearance similarity between the atlas image and the target image and the other channel optimized by similarity between atlas label and the segmentation of the target image. The image segmentation is performed by fusing labels of multiple atlases. The validation of our method on hippocampus segmentation of 30 subjects containing MR images with both 1.5T and 3.0T field strength has demonstrated that our method can significantly improve the segmentation performance with different fusion strategies and obtain segmentation results with Dice overlap of 0.892±0.024 for 1.5T images and 0.902±0.022 for 3.0T images to manual segmentations.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yongfu Hao, Tianzi Jiang, and Yong Fan "Shape-constrained multi-atlas based segmentation with multichannel registration", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83143N (14 February 2012); https://doi.org/10.1117/12.911370
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Cited by 5 scholarly publications.
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KEYWORDS
Image segmentation

Image registration

Image fusion

Image processing algorithms and systems

Detection and tracking algorithms

Magnetic resonance imaging

Control systems

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