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However, manual methods can be laborious and subject to a high degree of human variability. In this work, we developed various\n            <jats:bold>convolutional neural network<\/jats:bold>\n            (\n            <jats:bold>CNN<\/jats:bold>\n            ) architectures to segment Stanford\n            <jats:bold>type B aortic dissections<\/jats:bold>\n            (\n            <jats:bold>TBADs<\/jats:bold>\n            ), characterized by a tear in the descending aortic wall creating a normal channel of blood flow called a true lumen and a pathologic channel within the wall called a false lumen. We introduced several variations to the\n            <jats:bold>two-dimensional<\/jats:bold>\n            (\n            <jats:bold>2D<\/jats:bold>\n            ) and\n            <jats:bold>three-dimensional<\/jats:bold>\n            (3\n            <jats:bold>D<\/jats:bold>\n            ) U-Net, where small stacks of slices were inputted into the networks instead of individual slices or whole geometries. We compared these variations with a variety of CNN segmentation architectures and found that stacking the input data slices in the upward direction with 2D U-Net improved segmentation accuracy, as measured by the\n            <jats:bold>Dice similarity coefficient<\/jats:bold>\n            (\n            <jats:bold>DC<\/jats:bold>\n            ) and point-by-point\n            <jats:bold>average distance<\/jats:bold>\n            (\n            <jats:bold>AVD<\/jats:bold>\n            ), by more than\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"TeX\" version=\"MathJax\">15\\%<\/jats:tex-math>\n            <\/jats:inline-formula>\n            . Our optimal architecture produced DC scores of 0.94, 0.88, and 0.90 and AVD values of 0.074, 0.22, and 0.11 in the whole aorta, true lumen, and false lumen, respectively. Altogether, the predicted reconstructions closely matched manual reconstructions.\n          <\/jats:p>","DOI":"10.1145\/3472302","type":"journal-article","created":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T01:39:53Z","timestamp":1634434793000},"page":"1-16","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Evaluation of U-Net Based Architectures for Automatic Aortic Dissection Segmentation"],"prefix":"10.1145","volume":"3","author":[{"given":"Bradley","family":"Feiger","sequence":"first","affiliation":[{"name":"Duke University Department of Biomedical Engineering, Durham NC"}]},{"given":"Erick","family":"Lorenzana-Saldivar","sequence":"additional","affiliation":[{"name":"Duke University Department of Biomedical Engineering, Durham NC"}]},{"given":"Colin","family":"Cooke","sequence":"additional","affiliation":[{"name":"Duke University Department of Electrical Engineering, Durham, NC"}]},{"given":"Roarke","family":"Horstmeyer","sequence":"additional","affiliation":[{"name":"Duke University Department of Biomedical Engineering, Durham NC"}]},{"given":"Muath","family":"Bishawi","sequence":"additional","affiliation":[{"name":"Duke University Department of Surgery, Durham, NC"}]},{"given":"Julie","family":"Doberne","sequence":"additional","affiliation":[{"name":"Duke University Department of Surgery, Durham, NC"}]},{"given":"G. Chad","family":"Hughes","sequence":"additional","affiliation":[{"name":"Duke University Department of Surgery, Durham, NC"}]},{"given":"David","family":"Ranney","sequence":"additional","affiliation":[{"name":"Duke University Department of Surgery, Durham, NC"}]},{"given":"Soraya","family":"Voigt","sequence":"additional","affiliation":[{"name":"Duke University Department of Surgery, Durham, NC"}]},{"given":"Amanda","family":"Randles","sequence":"additional","affiliation":[{"name":"Duke University Department of Biomedical Engineering, Durham NC"}]}],"member":"320","published-online":{"date-parts":[[2021,10,15]]},"reference":[{"issue":"9345","key":"e_1_3_2_2_1","doi-asserted-by":"crossref","first-page":"1531","DOI":"10.1016\/S0140-6736(02)11522-4","article-title":"The multicentre aneurysm screening study (MASS) into the effect of abdominal aortic aneurysm screening on mortality in men: A randomised controlled trial","volume":"360","author":"Ashton H. A.","year":"2002","unstructured":"H. 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