{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,15]],"date-time":"2025-06-15T04:05:03Z","timestamp":1749960303697,"version":"3.41.0"},"reference-count":38,"publisher":"IOP Publishing","issue":"3","license":[{"start":{"date-parts":[[2024,4,26]],"date-time":"2024-04-26T00:00:00Z","timestamp":1714089600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/page\/copyright"},{"start":{"date-parts":[[2024,4,26]],"date-time":"2024-04-26T00:00:00Z","timestamp":1714089600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Biomed. Phys. Eng. Express"],"published-print":{"date-parts":[[2024,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>\n                  <jats:italic>Introduction<\/jats:italic>. The currently available dosimetry techniques in computed tomography can be inaccurate which overestimate the absorbed dose. Therefore, we aimed to provide an automated and fast methodology to more accurately calculate the SSDE using <jats:inline-formula>\n                     <jats:tex-math>\n\n<\/jats:tex-math>\n                     <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:msub>\n                           <mml:mrow>\n                              <mml:mi>D<\/mml:mi>\n                           <\/mml:mrow>\n                           <mml:mrow>\n                              <mml:mi>w<\/mml:mi>\n                           <\/mml:mrow>\n                        <\/mml:msub>\n                     <\/mml:math>\n                  \n                  <\/jats:inline-formula> obtained by using CNN from thorax and abdominal CT study images. <jats:italic>Methods<\/jats:italic>. The SSDE was determined from the 200 records files. For that purpose, patients\u2019 size was measured in two ways: (a) by developing an algorithm following the AAPM Report No. 204 methodology; and (b) using a CNN according to AAPM Report No. 220. <jats:italic>Results<\/jats:italic>. The patient\u2019s size measured by the in-house software in the region of thorax and abdomen was 27.63 \u00b1 3.23 cm and 28.66 \u00b1 3.37 cm, while CNN was 18.90 \u00b1 2.6 cm and 21.77 \u00b1 2.45 cm. The SSDE in thorax according to 204 and 220 reports were 17.26 \u00b1 2.81 mGy and 23.70 \u00b1 2.96 mGy for women and 17.08 \u00b1 2.09 mGy and 23.47 \u00b1 2.34 mGy for men. In abdomen was 18.54 \u00b1 2.25 mGy and 23.40 \u00b1 1.88 mGy in women and 18.37 \u00b1 2.31 mGy and 23.84 \u00b1 2.36 mGy in men. <jats:italic>Conclusions<\/jats:italic>. Implementing CNN-based automated methodologies can contribute to fast and accurate dose calculations, thereby improving patient-specific radiation safety in clinical practice.<\/jats:p>","DOI":"10.1088\/2057-1976\/ad3fbe","type":"journal-article","created":{"date-parts":[[2024,4,17]],"date-time":"2024-04-17T22:21:07Z","timestamp":1713392467000},"page":"035035","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["CNN application for automated determination of the patient\u2019s size to obtain the size-specific dose estimated in CT"],"prefix":"10.1088","volume":"10","author":[{"given":"Erik R","family":"Hern\u00e1ndez-D\u00e1vila","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8355-3927","authenticated-orcid":true,"given":"Eugenio","family":"Torres-Garc\u00eda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liliana","family":"Aranda-Lara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ernesto","family":"Roldan-Valadez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4388-3811","authenticated-orcid":true,"given":"Keila","family":"Isaac-Oliv\u00e9","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mario","family":"Flores-Reyes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2024,4,26]]},"reference":[{"key":"bpexad3fbebib1","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.cgh.2011.09.005","article-title":"Use of abdominopelvic computed tomography in emergency departments and rates of urgent diagnoses in crohn\u2019s disease","volume":"10","author":"Kerner","year":"2012","journal-title":"Clin. 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