SPECT reconstruction

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Filtered back-projection • very fast • direct inversion of the projection formula • corrections for scatter, non-uniform attenuation and other physical factors are difficult • it needs a lot of filtering - trade-off between blurring and noise • quantitative imaging difficult
Iterative <strong>reconstruction</strong> • discreteness of data included in the model • it is easy to model and handle projection noise, especially when the counts are low • it is easy to model the imaging physics such as geometry, non-uniform attenuation, scatter, etc. • quantitative imaging possible • amplification of noise • long calculation time
Page 1 and 2: Regional Training Workshop Advanced
Page 3 and 4: anterior view lateral view courtesy
Page 5 and 6: Groch MW, Erwin WD. J Nucl Med Tech
Page 7 and 8: 2nd step in tomography = reconstruc
Page 9 and 10: Recording projections of a slice
Page 11 and 12: Filtered back-projection (FBP)
Page 14 and 15: 1 2 3 4
Page 16 and 17: 1 2 3 3 4 7 1 5 4 2 5 4 6 3
Page 18 and 19: 3 3 3 7 7 7 1 5 4 2 5 4 6 3
Page 20 and 21: 12 11 3 14 18 7 1 5 4 2 5 4 6 3
Page 22 and 23: 3 (divide each entry by 3) 3 6 4 9
Page 26 and 27: ack projection (BP) = summation of
Page 28 and 29: Sequence of summing original and fi
Page 30 and 31: Reconstruction of a slice from proj
Page 32 and 33: The principle of the iterative algo
Page 34 and 35: measured projections first estimate
Page 36 and 37: 1 2 3 2.5 2.5 5 3 4 7 2.5 2.5 5 4 6
Page 38 and 39: 1 2 3 1 2.5 5 3 4 7 2.5 2.5 5 4 6 5
Page 40 and 41: 1 2 3 1 2 5 3 4 7 3 2.5 5 4 6 5 5 c
Page 42 and 43: Iterative reconstruction - multipli
Page 44 and 45: Iterative reconstruction - multipli
Page 48 and 49: References: Groch MW, Erwin WD. SPE

SPECT reconstruction

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