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Standardized medical image registration for radiological identification of decedents based on paranasal sinuses
Image registration software is frequently used in clinical radiology, e.g., for follow-up diagnosis. To a certain extent, the radiological identification of decedents (RadID) is comparable to a clinical follow-up diagnosis, in that two datasets from different dates are compared in terms of their ana...
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Published in: | Journal of forensic and legal medicine 2018-02, Vol.54, p.96-101 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Image registration software is frequently used in clinical radiology, e.g., for follow-up diagnosis. To a certain extent, the radiological identification of decedents (RadID) is comparable to a clinical follow-up diagnosis, in that two datasets from different dates are compared in terms of their anatomical characteristics (e.g., paranasal sinuses) or surgical implants. Due to the increasing use of computed tomography (CT) for head examinations in clinical radiology and the increased use of postmortem CT (PMCT) in forensic imaging, the comparison of three-dimensional (3D) clinical CT (termed as antemortem CT (AMCT) in this article) and PMCT datasets for RadID is becoming increasingly practical. In particular, the comparison of paranasal sinuses in AMCT and PMCT imaging is considered a suitable and reliable modality for RadID. However, previous publications regarding RadID based on comparisons of 3D datasets have not considered the implementation of image registration to provide software-side support for RadID. This article demonstrates and evaluates the use of a standard medical image registration procedure for RadID by comparing paranasal sinuses.
•Standardized medical image registration looks suitable for radiological identification based on paranasal sinuses.•The presented approach is easy-to-use, time-efficient and reliable.•The presented approach provides a quick and easy method for human identification. |
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ISSN: | 1752-928X 1878-7487 |
DOI: | 10.1016/j.jflm.2017.12.003 |