Automatic segmentation of 3D cardiac SPECT imagery

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Abstract
The automatic visualization and quantitative analysis of cardiac SPECT data requires the ability to automat- ically segment and extract voxels representing the heart. The attributes of the 3D data make this task quite challenging. In this paper, we attempt to address these issues and propose an algorithm which successfully detects the voxels belonging to the Left Ventricle (LV) of the heart and filters out the noise and all other interfering organs. The algorithm relies on various image processing and pattern analysis techniques as well as the constraints put forward by the anatomy. The final outcome of this algorithm is a segmented 3D dataset containing voxels pertaining only to the LV. This filtered dataset is then employed for automatic determina- tion of LV orientation. The results show that this methodology is a very promising approach to segmentation of cardiac SPECT imagery.

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