Title :
Self-adaptive masking method for automatic shape recognition and motion correction of thallium-201 myocardial perfusion SPECT imaging
Author :
Dong, K. ; Tabrizi, M.H.N. ; Movahed, A.
Author_Institution :
Dept. of Math. & Comput. Sci., East Carolina Univ., Greenville, NC, USA
Abstract :
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
Keywords :
adaptive signal processing; cardiology; fast Fourier transforms; feature extraction; filtering theory; image motion analysis; image recognition; image segmentation; medical image processing; noise; single photon emission computed tomography; thallium; 2D FFT; Tl; automatic shape recognition; feature extraction; frequency domain filtering; image segmentation; low SNR images; motion correction; nuclear cardiac imaging; planar images; recursive thresholding; region recognition; self-adaptive masking method; shape detection; thallium-201 myocardial perfusion SPECT imaging; tracking; two-dimensional fast Fourier transform; Fast Fourier transforms; Filtering; Frequency domain analysis; Heart; Image recognition; Motion detection; Myocardium; Shape; Signal to noise ratio; Tracking;
Conference_Titel :
Information Technology: Coding and Computing, 2000. Proceedings. International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
0-7695-0540-6
DOI :
10.1109/ITCC.2000.844273
