Self-adaptive masking method for automatic shape recognition and motion correction of thallium-201 myocardial perfusion SPECT imaging

We introduce a new self-adaptive masking method for shape detection of low signal to noise ratio (SNR) images to improve the tracking capabilities of the motion correction in nuclear cardiac imaging. The method is developed using two-dimensional fast Fourier transform, ideal filtering in the frequency domain, recursive thresholding, and region recognition. This method is independent of the correlation between the context of the planar images and has a good tolerance for low SNR images. Also it is robust under the circumstances of significant abrupt motion of the object.