{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T02:03:26Z","timestamp":1768529006242,"version":"3.49.0"},"reference-count":44,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2017,11,6]],"date-time":"2017-11-06T00:00:00Z","timestamp":1509926400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000968","name":"American Heart Association","doi-asserted-by":"publisher","award":["14GRNT19040010"],"award-info":[{"award-number":["14GRNT19040010"]}],"id":[{"id":"10.13039\/100000968","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000968","name":"American Heart Association","doi-asserted-by":"publisher","award":["13GRNT17090037"],"award-info":[{"award-number":["13GRNT17090037"]}],"id":[{"id":"10.13039\/100000968","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2017,12]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>Segmentation of contrast\u2010enhanced CT and measurement of SPECT point spread function (PSF) are usually required for conventional partial volume correction (PVC). This study was to develop a segmentation\u2010free method with blind deconvolution (BD) and anatomical\u2010based filtering for SPECT PVC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The proposed method was implemented using an iterative BD algorithm to estimate the restored image and the PSF simultaneously. An anatomical\u2010based filtering was implemented at each iteration to reduce Gibbs artifact and suppress noise amplification in the deconvolution process. The proposed method was validated with <jats:sup>123<\/jats:sup>I\u2010metaiodobenzylguanidine (<jats:sup>123<\/jats:sup>I\u2010mIBG) SPECT\/CT imaging of NCAT phantoms with and without myocardial perfusion defect and a physical cardiac phantom. Fifteen heart\u2010to\u2010mediastinum ratios (HMRs) were configured in the NCAT and physical phantoms. Correlations between SPECT\u2010quantified and true HMRs were calculated from images without PVC as well as from BD restored images. The proposed method was also performed on a human <jats:sup>123<\/jats:sup>I\u2010mIBG study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Relative bias and standard deviation images of NCAT phantoms showed that the proposed method reduced both bias and noise. Mean relative bias in the simulated normal myocardium was markedly improved (\u221216.8%\u00a0\u00b1\u00a00.4% versus \u22120.8%\u00a0\u00b1\u00a00.6% for low noise level; \u221216.7%\u00a0\u00b1\u00a00.7% versus \u22122.3%\u00a0\u00b1\u00a00.9% for high noise level). Mean relative bias in the simulated myocardial defect was also noticeably improved (\u221212.7%\u00a0\u00b1\u00a01.2% versus 1.2%\u00a0\u00b1\u00a01.6% for low noise level; \u221213.5%\u00a0\u00b1\u00a02.4% versus \u22120.9%\u00a0\u00b1\u00a02.8% for high noise level). The signal to noise ratio (SNR) of the defect was improved from 2.95\u00a0\u00b1\u00a00.09 to 4.07\u00a0\u00b1\u00a00.16 for low noise level (38% increase of mean), and from 2.56\u00a0\u00b1\u00a00.15 to 3.62\u00a0\u00b1\u00a00.22 for high noise level (41% increase of mean). For both NCAT and physical phantoms, HMRs calculated from images without PVC were underestimated (correlations between SPECT\u2010quantified and true HMRs: y\u00a0=\u00a00.81x\u00a0+\u00a00.1 for NCAT phantom; y\u00a0=\u00a00.82x\u00a0+\u00a00.14 for physical phantom). HMRs from BD restored images were markedly improved (correlations between SPECT\u2010quantified and true HMRs: y\u00a0=\u00a0x\u00a0+\u00a00.05 for NCAT phantom; y\u00a0=\u00a00.97x\u00a0\u2212\u00a00.12 for physical phantom). After applying the proposed PVC method, the estimation error between the SPECT\u2010quantified and true HMRs was significantly reduced from \u22120.75\u00a0\u00b1\u00a00.57 to 0.04\u00a0\u00b1\u00a00.17 for NCAT phantom (<jats:italic>P<\/jats:italic>\u00a0=\u00a08e\u201005), and from \u22120.68\u00a0\u00b1\u00a00.67 to \u22120.26\u00a0\u00b1\u00a00.42 for physical phantom (<jats:italic>P<\/jats:italic>\u00a0=\u00a00.005). The human study demonstrated that the HMR increased by 8% with PVC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The proposed segmentation\u2010free PVC method has the potential of improving SPECT quantification accuracy and reducing noise without the need for premeasuring the image PSF.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.12622","type":"journal-article","created":{"date-parts":[[2017,10,10]],"date-time":"2017-10-10T09:12:40Z","timestamp":1507626760000},"page":"6435-6446","source":"Crossref","is-referenced-by-count":8,"title":["A blind deconvolution method incorporated with anatomical\u2010based filtering for partial volume correction: Validations with <sup>123<\/sup>I\u2010mIBG cardiac SPECT\/CT"],"prefix":"10.1002","volume":"44","author":[{"given":"Jing","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Radiology and Biomedical Imaging Yale University New Haven CT 06520 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine (Cardiology) Yale University New Haven CT 06520 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Taraneh","family":"Hashemi Zonouz","sequence":"additional","affiliation":[{"name":"Department of Radiology and Biomedical Imaging Yale University New Haven CT 06520 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Veronica M.","family":"Sandoval","sequence":"additional","affiliation":[{"name":"Nuclear Cardiology Yale\u2010New Haven Hospital New Haven CT 06510 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hassan","family":"Mohy\u2010ud\u2010Din","sequence":"additional","affiliation":[{"name":"Department of Radiology and Biomedical Imaging Yale University New Haven CT 06520 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rachel J.","family":"Lampert","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine (Cardiology) Yale University New Haven CT 06520 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Albert J.","family":"Sinusas","sequence":"additional","affiliation":[{"name":"Department of Radiology and Biomedical Imaging Yale University New Haven CT 06520 USA"},{"name":"Department of Internal Medicine (Cardiology) Yale University New Haven CT 06520 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chi","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Radiology and Biomedical Imaging Yale University New Haven CT 06520 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi\u2010Hwa","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine (Cardiology) Yale University New Haven CT 06520 USA"},{"name":"Department of Biomedical Imaging and Radiological Sciences National Yang\u2010Ming University Taipei 100 Taiwan"},{"name":"Department of Biomedical Engineering Chung Yuan Christian University Taoyuan 330 Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2017,11,6]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehn113"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2010.01.014"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12350-010-9313-4"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12350-012-9539-4"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12350-011-9438-0"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.semnuclmed.2014.04.005"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.115.157503"},{"key":"e_1_2_8_9_1","unstructured":"LiuY\u2010H WuJ LiuC SinusasAJ.Planar versus SPECT quantification of the heart\u2010to\u2010mediastinum ratio from I\u2010123\u2010MIBG sympathetic cardiac SPECT imaging: Accuracy as assessed by computer simulations. 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