{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T22:49:13Z","timestamp":1790635753893,"version":"4.1.0"},"reference-count":24,"publisher":"IOP Publishing","issue":"8","license":[{"start":{"date-parts":[[2017,3,17]],"date-time":"2017-03-17T00:00:00Z","timestamp":1489708800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2017,3,17]],"date-time":"2017-03-17T00:00:00Z","timestamp":1489708800000},"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":["Phys. Med. Biol."],"published-print":{"date-parts":[[2017,4,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>In MR guided radiation therapy planning both MR and CT images for a patient are acquired and co-registered to obtain a tissue specific HU map. Generation of the HU map directly from the MRI would eliminate the CT acquisition and may improve radiation therapy planning. In this preliminary study of substitute CT (sCT) generation, two porcine leg phantoms were scanned using a 3D ultrashort echo time (PETRA) sequence and co-registered to corresponding CT images to build tissue specific regression models. The model was created from one co-registered CT-PETRA pair to generate the sCT for the other PETRA image. An expectation maximization based clustering was performed on the co-registered PETRA image to identify the soft tissues, dense bone and air class membership probabilities. A tissue specific non linear regression model was built from one registered CT-PETRA pair dataset to predict the sCT of the second PETRA image in a two-fold cross validation schema. A complete substitute CT is generated in 3\u2009min. The mean absolute HU error for air was 0.3 HU, bone was 95 HU, fat was 30 HU and for muscle it was 10 HU. The mean surface reconstruction error for the bone was 1.3\u2009mm. The PETRA sequence enabled a low mean absolute surface distance for the bone and a low HU error for other classes. The sCT generated from a single PETRA sequence shows promise for the generation of fast sCT for MRI based radiation therapy planning.<\/jats:p>","DOI":"10.1088\/1361-6560\/aa508a","type":"journal-article","created":{"date-parts":[[2017,3,17]],"date-time":"2017-03-17T12:18:39Z","timestamp":1489753119000},"page":"2950-2960","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Substitute CT generation from a single ultra short time echo MRI sequence: preliminary study"],"prefix":"10.1088","volume":"62","author":[{"given":"Soumya","family":"Ghose","sequence":"first","affiliation":[{"name":"Case Western Reserve University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason A","family":"Dowling","sequence":"additional","affiliation":[{"name":"The Australian e-Health & Research Centre"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robba","family":"Rai","sequence":"additional","affiliation":[{"name":"Liverpool Cancer Therapy Centre, Liverpool Hospital"},{"name":"Ingham Institute for Applied Medical Research and Liverpool Cancer Therapy Centre"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gary P","family":"Liney","sequence":"additional","affiliation":[{"name":"Liverpool Cancer Therapy Centre, Liverpool Hospital"},{"name":"Ingham Institute for Applied Medical Research and Liverpool Cancer Therapy Centre"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2017,3,17]]},"reference":[{"key":"pmbaa508abib001","doi-asserted-by":"publisher","first-page":"1596","DOI":"10.1118\/1.4914158","type":"journal-article","article-title":"Patch-based generation of a pseudo CT from conventional MRI sequences for MRI-only radiotherapy of the brain","volume":"42","author":"Andreasen","year":"2015","journal-title":"Med. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2016-08-10","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2016-11-29","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2017-03-17","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}