Dominic Gascho, Patricia M. Flach, Sarah Schaerli, Michael J. Thali, Sören Kottner
{"title":"Application of 3D image fusion for radiological identification of decedents","authors":"Dominic Gascho, Patricia M. Flach, Sarah Schaerli, Michael J. Thali, Sören Kottner","doi":"10.1016/j.jofri.2018.04.002","DOIUrl":null,"url":null,"abstract":"<div><p>The fusion of antemortem and postmortem datasets may facilitate the radiological identification of decedents (RadID). Software for the image fusion is readily available from clinical radiology. This article demonstrates image fusions of three-dimensional datasets using medical image fusion software and describes RadID based on paranasal sinus, orthopedic implant, degenerative changes, healed fracture and dental positions by means of superimposed datasets (from computed tomography and magnetic resonance imaging).</p></div>","PeriodicalId":45371,"journal":{"name":"Journal of Forensic Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jofri.2018.04.002","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forensic Radiology and Imaging","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212478017300655","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The fusion of antemortem and postmortem datasets may facilitate the radiological identification of decedents (RadID). Software for the image fusion is readily available from clinical radiology. This article demonstrates image fusions of three-dimensional datasets using medical image fusion software and describes RadID based on paranasal sinus, orthopedic implant, degenerative changes, healed fracture and dental positions by means of superimposed datasets (from computed tomography and magnetic resonance imaging).