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Ultrasound imaging is the primary modality for cardiac imaging, however acquisition requires high operator skill, and its interpretation and analysis is difficult due to artifacts. Reconstructing cardiac anatomy in 3D can enable discovery of new biomarkers and make imaging less dependent on operator expertise, however most ultrasound systems only have 2D imaging capabilities. We propose both a simple alteration to the Pix2Vox++ networks for a sizeable reduction in memory usage and computational complexity, and a pipeline to perform reconstruction of 3D anatomy from 2D standard cardiac views, effectively enabling 3D anatomical reconstruction from limited 2D data. We evaluate our pipeline using synthetically generated data achieving accurate 3D whole-heart reconstructions (peak intersection over union score <jats:inline-formula><jats:alternatives><jats:tex-math>$$&gt; 0.88$$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:mrow>\n                    <mml:mo>&gt;<\/mml:mo>\n                    <mml:mn>0.88<\/mml:mn>\n                  <\/mml:mrow>\n                <\/mml:math><\/jats:alternatives><\/jats:inline-formula>) from just two standard anatomical 2D views of the heart. We also show preliminary results using real echo images.<\/jats:p>","DOI":"10.1007\/978-3-031-16902-1_9","type":"book-chapter","created":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T18:06:10Z","timestamp":1663351570000},"page":"86-95","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Efficient Pix2Vox++ for\u00a03D Cardiac Reconstruction from\u00a02D Echo Views"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7912-5249","authenticated-orcid":false,"given":"David","family":"Stojanovski","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1671-3489","authenticated-orcid":false,"given":"Uxio","family":"Hermida","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0756-0054","authenticated-orcid":false,"given":"Marica","family":"Muffoletto","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3097-4928","authenticated-orcid":false,"given":"Pablo","family":"Lamata","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9169-1788","authenticated-orcid":false,"given":"Arian","family":"Beqiri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7897-7589","authenticated-orcid":false,"given":"Alberto","family":"Gomez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,15]]},"reference":[{"key":"9_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1007\/978-3-030-00928-1_44","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2018","author":"JJ Cerrolaza","year":"2018","unstructured":"Cerrolaza, J.J., et al.: 3D fetal skull reconstruction from 2DUS via deep conditional generative networks. 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