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Despite the relevance, the actual practice relies upon visual inspection of the 2DCA image frames by clinicians. This procedure is prone to inaccuracies due to the poor contrast and small size of the CAC; moreover, it is dependent on the physician\u2019s experience. To address this issue, we developed a workflow to assist clinicians in identifying CAC within 2DCA using data from 44 image acquisitions across 14 patients.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods<\/jats:title>\n            <jats:p>Our workflow consists of three stages. In the first stage, a classification backbone based on ResNet-18 is applied to guide the CAC identification by extracting relevant features from 2DCA frames. In the second stage, a U-Net decoder architecture, mirroring the encoding structure of the ResNet-18, is employed to identify the regions of interest (ROI) of the CAC. Eventually, a post-processing step refines the results to obtain the final ROI. The workflow was evaluated using a leave-out cross-validation.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>The proposed method outperformed the comparative methods by achieving an F1-score for the classification step of 0.87 (0.77<jats:inline-formula>\n                <jats:alternatives>\n                  <jats:tex-math>$$-$$<\/jats:tex-math>\n                  <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                    <mml:mo>-<\/mml:mo>\n                  <\/mml:math>\n                <\/jats:alternatives>\n              <\/jats:inline-formula>0.94) (median \u00b1 quartiles), while for the CAC identification step the intersection over minimum (IoM) was 0.64 (0.46<jats:inline-formula>\n                <jats:alternatives>\n                  <jats:tex-math>$$-$$<\/jats:tex-math>\n                  <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                    <mml:mo>-<\/mml:mo>\n                  <\/mml:math>\n                <\/jats:alternatives>\n              <\/jats:inline-formula>0.86) (median \u00b1 quartiles).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>This is the first attempt to propose a clinical decision support system to assist the identification of CAC within 2DCA. The proposed workflow holds the potential to improve both the accuracy and efficiency of CAC quantification, with promising clinical applications. As future work, the concurrent use of multiple auxiliary tasks could be explored to further improve the segmentation performance.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s11548-025-03382-5","type":"journal-article","created":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T19:55:00Z","timestamp":1746734100000},"page":"1273-1281","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A multi-model deep learning approach for the identification of coronary artery calcifications within 2D coronary angiography images"],"prefix":"10.1007","volume":"20","author":[{"given":"Edoardo","family":"De Rose","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ciro Benito","family":"Raggio","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmad Riccardo","family":"Rasheed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierangela","family":"Bruno","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paolo","family":"Zaffino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Salvatore","family":"De Rosa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Calimeri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria Francesca","family":"Spadea","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,8]]},"reference":[{"issue":"1","key":"3382_CR1","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1186\/s12872-024-04157-7","volume":"24","author":"B Elnagar","year":"2024","unstructured":"Elnagar B, Habib M, Elnagar R, Khalfallah M (2024) The value of coronary calcium score in predicting clinical outcomes in patients with chronic coronary syndrome. 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The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}