These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Automated interstudy image registration technique for SPECT and PET.
    Author: Eberl S, Kanno I, Fulton RR, Ryan A, Hutton BF, Fulham MJ.
    Journal: J Nucl Med; 1996 Jan; 37(1):137-45. PubMed ID: 8543983.
    Abstract:
    UNLABELLED: We report the extended application of an automated computer technique for three-dimensional spatial registration of SPECT and PET studies. METHODS: The technique iteratively reslices a misaligned data set until the sum of the absolute differences (SAD) from a reference data set is minimized. The registration accuracy was assessed in Hoffman brain phantom studies collected with known misalignments and transmission studies of a thorax phantom with fiducial markers. The SAD was compared with three other cost functions: stochastic sign change criterion, sum of products and standard deviation (s.d.) of ratios. In clinical neurological and myocardial perfusion studies, registration accuracy was estimated from the relative locations of landmarks in the reference and registered data sets. RESULTS: Registration accuracy in the Hoffman brain phantom studies was -0.07 +/- 0.46 mm (mean +/- s.d.) for translations and -0.01 +/- 0.20 degrees for rotations, with maximum translation and rotation errors of 1.2 mm and 0.8 degree, respectively. The SAD was the most accurate and reliable cost function. Registration errors in the thorax phantom were 3.1 +/- 1.7 mm. Mean accuracy in the neurological studies, estimated from landmark pairs, was 2.0 +/- 1.1 mm for SPECT to SPECT and 1.8 +/- 1.1 mm for PET to SPECT registrations. Average registration accuracy in 201Tl myocardial perfusion studies was 2.1 +/- 1.2 mm. CONCLUSION: Our registration method (a) provided accurate registrations for phantom and clinical SPECT and PET studies, (b) is fully automated, (c) simplifies comparison of data sets obtained at different times and with different modalities, and (d) can be applied retrospectively.
    [Abstract] [Full Text] [Related] [New Search]