Premium
Modifying constrained least‐squares restoration for application to single photon emission computed tomography projection images
Author(s) -
Penney Bill C.,
King Michael A.,
Schwinger Ronald B.,
Baker Stephen P.,
Doherty Paul W.
Publication year - 1988
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.596227
Subject(s) - image restoration , projection (relational algebra) , artificial intelligence , single photon emission computed tomography , iterative reconstruction , computer vision , emission computed tomography , imaging phantom , computer science , noise (video) , shot noise , positron emission tomography , mathematics , nuclear medicine , optics , physics , image (mathematics) , image processing , algorithm , medicine , detector
Image restoration methods have been shown to increase the contrast of nuclear medicine images by decreasing the effects of scatter and septal penetration. Image restoration can also reduce the high‐frequency noise in the image. This study applies constrained least‐squares (CLS) restoration to the projection images of single photon emission computed tomography (SPECT). In a previous study, it was noted that CLS restoration has the potential advantage of automatically adapting to the blurred object. This potential is confirmed using planar images. CLS restoration is then modified to improve its performance when applied to SPECT projection image sets. The modification was necessary because the Poisson noise in low count SPECT images causes considerable variation in the CLS filter. On phantom studies, count‐dependent Metz restoration was slightly better than the modified CLS restoration method, according to measures of contrast and noise. However, CLS restoration was generally judged as yielding the best results when applied to clinical studies, apparently because of its ability to adapt to the image being restored.