<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Song Y</submitter><funding>NIBIB NIH HHS</funding><funding>NHLBI NIH HHS</funding><pagination>014002</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9836910</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>10(1)</volume><pubmed_abstract>&lt;h4>Purpose&lt;/h4>Our long-range goal is to improve whole-heart CT calcium scores by extracting quantitative features from individual calcifications. Here, we perform deconvolution to improve bias/reproducibility of small calcification assessments, which can be degraded at the normal CT calcium score image resolution.&lt;h4>Approach&lt;/h4>We analyzed features of individual calcifications on repeated standard (2.5 mm) and thin (1.25 mm) slice scans from QRM-Cardio phantom, cadaver hearts, and CARDIA study participants. Preprocessing to improve the resolution involved of Lucy-Richardson deconvolution with a measured point spread function (PSF) or three-dimensional blind deconvolution in which the PSF was iteratively optimized on high detail structures such as calcifications in images.&lt;h4>Results&lt;/h</pubmed_abstract><journal>Journal of medical imaging (Bellingham, Wash.)</journal><pubmed_title>Improved bias and reproducibility of coronary artery calcification features using deconvolution.</pubmed_title><pmcid>PMC9836910</pmcid><funding_grant_id>HHSN268201800005I</funding_grant_id><funding_grant_id>HHSN268201800004I</funding_grant_id><funding_grant_id>T32 EB007509</funding_grant_id><funding_grant_id>HHSN268201800007I</funding_grant_id><funding_grant_id>HHSN268201800006I</funding_grant_id><funding_grant_id>R01 HL143484</funding_grant_id><funding_grant_id>HHSN268201800003I</funding_grant_id><funding_grant_id>R41 HL144271</funding_grant_id><funding_grant_id>R01 HL165218</funding_grant_id><funding_grant_id>R44 HL156811</funding_grant_id><funding_grant_id>R01 HL098445</funding_grant_id><pubmed_authors>Al-Kindi S</pubmed_authors><pubmed_authors>Carr JJ</pubmed_authors><pubmed_authors>Wilson DL</pubmed_authors><pubmed_authors>Terry JG</pubmed_authors><pubmed_authors>Hoori A</pubmed_authors><pubmed_authors>Jacobs DR</pubmed_authors><pubmed_authors>Song Y</pubmed_authors><pubmed_authors>Wu H</pubmed_authors><pubmed_authors>Vembar M</pubmed_authors><pubmed_authors>Ciancibello L</pubmed_authors></additional><is_claimable>false</is_claimable><name>Improved bias and reproducibility of coronary artery calcification features using deconvolution.</name><description>&lt;h4>Purpose&lt;/h4>Our long-range goal is to improve whole-heart CT calcium scores by extracting quantitative features from individual calcifications. Here, we perform deconvolution to improve bias/reproducibility of small calcification assessments, which can be degraded at the normal CT calcium score image resolution.&lt;h4>Approach&lt;/h4>We analyzed features of individual calcifications on repeated standard (2.5 mm) and thin (1.25 mm) slice scans from QRM-Cardio phantom, cadaver hearts, and CARDIA study participants. Preprocessing to improve the resolution involved of Lucy-Richardson deconvolution with a measured point spread function (PSF) or three-dimensional blind deconvolution in which the PSF was iteratively optimized on high detail structures such as calcifications in images.&lt;h4>Results&lt;/h</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Jan</publication><modification>2025-04-05T12:43:25.956Z</modification><creation>2025-04-05T12:43:25.956Z</creation></dates><accession>S-EPMC9836910</accession><cross_references><pubmed>36647366</pubmed><doi>10.1117/1.jmi.10.1.014002</doi><doi>10.1117/1.JMI.10.1.014002</doi></cross_references></HashMap>