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An innovative 3D-3D superimposition for assessing anatomical uniqueness of frontal sinuses through segmentation on CT scans
- Source :
- International Journal of Legal Medicine. 133:1159-1165
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
Abstract
- Anatomical uniqueness plays a significant role in the personal identification process of unknown deceased. Frontal sinuses have been widely used in the past decades for this purpose, mostly using 2D X-ray techniques. However, the modern 3D CT-based segmentation methods may help in developing novel and more reliable methods of identification. This study aims at assessing the anatomical uniqueness of frontal sinuses through the 3D model registration. Thirty subjects who underwent two maxillofacial CT scans (interval: 1 month to 5 years) were selected from a hospital database. Frontal sinuses were automatically segmented through ITK-SNAP open source software and the 3D models belonging to the same patient were automatically superimposed according to the least point-to-point difference between the two surfaces. Two hundred patients were randomly selected from the same database and undergo the same procedure to perform 200 superimpositions of frontal sinuses belonging to different individuals, equally divided between males and females (mismatches). Statistically significant differences of average root mean square (RMS) point-to-point distance between the group of matches and mismatches, as well as possible differences according to sex, were assessed through Mann-Whitney U test (p
- Subjects :
- Adult
Male
3d model
030218 nuclear medicine & medical imaging
Pathology and Forensic Medicine
03 medical and health sciences
Imaging, Three-Dimensional
0302 clinical medicine
3d segmentation
Image Processing, Computer-Assisted
Humans
Medicine
Superimposition
Segmentation
030216 legal & forensic medicine
Uniqueness
Orthodontics
business.industry
Significant difference
Open source software
Mann–Whitney U test
Forensic Anthropology
Frontal Sinus
Radiographic Image Interpretation, Computer-Assisted
Female
Tomography, X-Ray Computed
business
Subjects
Details
- ISSN :
- 14371596 and 09379827
- Volume :
- 133
- Database :
- OpenAIRE
- Journal :
- International Journal of Legal Medicine
- Accession number :
- edsair.doi.dedup.....88085cca77e70fa4e909479b4bbeeca1