{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T08:10:09Z","timestamp":1762935009108,"version":"3.45.0"},"reference-count":39,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,3,18]],"date-time":"2025-03-18T00:00:00Z","timestamp":1742256000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01\u2010HL142258","R01\u2010HL139066"],"award-info":[{"award-number":["R01\u2010HL142258","R01\u2010HL139066"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2025,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Dynamic imaging holds great potential in the diagnosis and comprehensive evaluation of different diseases by capturing mechanical and dynamic characteristics of moving organs. Nonetheless, motion artifacts notably impair image quality, hindering accurate and localized analysis\u2014particularly in free\u2010breathing scenarios. In preclinical studies, traditional methods often necessitate artificial breathing control or use invasive techniques that do not permit functional lung assessment under normal physiological conditions, potentially biasing results and restricting longitudinal studies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aimed to mitigate motion artifacts and preserve temporal information, thus enhancing the spatiotemporal resolution of dynamic micro\u2010CT images in free\u2010breathing animals. We sought to combine the benefits of standard amplitude and phase binning within an unsupervised learning approach, without the need for iterative methods, prior knowledge, or alteration of the reconstruction process. Our approach facilitates accurate imaging of free\u2010breathing animals under various protocols, without requiring artificial breathing control or invasive interventions, through a straightforward, immediately applicable retrospective analysis method.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A novel periodic line\u2010constrained K\u2010means clustering technique was developed as an unsupervised method for projection\/interleave binning. To validate this technique on preclinical micro\u2010CT images, a syringe\u2010spring system was engineered to simulate respiratory motion. Imaging was performed on this moving phantom with various breathing rates and inhale\u2010to\u2010exhale (I\/E) ratios, as well as in free\u2010breathing rats and rabbits. Additionally, we detail a method for extracting the breathing signal directly from the x\u2010ray projection images and introduce a systematic approach for data imputation in limited\u2010angle scenarios. We also established a metric for quantifying motion artifacts in our 4DCT images.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The clustering method effectively integrated the benefits of both amplitude and phase binning, leading to a marked reduction in motion artifacts across all tests. Notably, our method yielded enhanced image clarity and improved accuracy in capturing dynamic lung volumes, evidenced by sharper diaphragm edges, better visibility of blood vessels, and diminished blurring and motion artifacts. Quantitative analysis using linear regression of diaphragm speed versus blur measure showed a near\u2010zero slope for both rats and rabbits, indicating a substantial decrease in motion artifact presence compared to traditional binning methods.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The periodic line\u2010constrained K\u2010means clustering method provides a robust solution for enhancing the quality of dynamic micro\u2010CT imaging in preclinical studies. By reducing motion artifacts and improving image resolution, this approach enables more precise evaluations of lung function under physiologically relevant conditions. Future work will explore the application of this method to various respiratory disease models and assess its potential for broader clinical use in dynamic imaging of other organs.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.17762","type":"journal-article","created":{"date-parts":[[2025,3,18]],"date-time":"2025-03-18T23:43:41Z","timestamp":1742341421000},"page":"4318-4329","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An unsupervised approach for projection binning to reduce motion artifacts in free\u2010breathing animal models"],"prefix":"10.1002","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5483-8613","authenticated-orcid":false,"given":"Mostafa K.","family":"Ismail","sequence":"first","affiliation":[{"name":"Department of Bioengineering School of Engineering and Applied Sciences University of Pennsylvania Philadelphia Pennsylvania USA"},{"name":"Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Ruppert","sequence":"additional","affiliation":[{"name":"Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Caballo","sequence":"additional","affiliation":[{"name":"Application Science MILabs B.V. Houten 3991 CD the Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hooman","family":"Hamedani","sequence":"additional","affiliation":[{"name":"Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ian","family":"Duncan","sequence":"additional","affiliation":[{"name":"Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephen","family":"Kadlecek","sequence":"additional","affiliation":[{"name":"Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rahim","family":"Rizi","sequence":"additional","affiliation":[{"name":"Department of Bioengineering School of Engineering and Applied Sciences University of 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