Synthesizing Dental Radiographs for Human Identification

The task of identifying human remains based on dental comparisons of post mortem (PM) and ante mortem (AM) radiographs is labor-intensive, subjective, and has several drawbacks, including: inherently poor image quality, difficulty matching the viewing angles in PM radiographs to those taken AM, and the fact that the state of the dental remains may entirely preclude the possibility of obtaining certain types of radiographs PM. The aim of the present study was to investigate the feasibility of using radiograph-like images reconstructed from PM x-ray computed tomography (CT) data to overcome the shortcomings of conventional radiographic comparison. Algorithms for computer synthesis of panoramic, periapical, and bitewing images are presented. The algorithms were evaluated with data from clinical examinations of two persons. The results demonstrate the efficacy of the CT-based approach and that, in comparison with conventional radiographs, the synthesized images exhibit minimal geometric distortion, reduced blurring, and reduced superimposition of oral structures.

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Post-mortem X-ray computed tomography (PMCT) identification using ante-mortem CT-scan of the sphenoid sinus

Journal of Neuroradiology ◽

10.1016/j.neurad.2018.08.003 ◽

2019 ◽

Vol 46 (4) ◽

pp. 248-255 ◽

Cited By ~ 7

Author(s):

Lucile Deloire ◽

Idris Diallo ◽

Romain Cadieu ◽

Mathieu Auffret ◽

Zarrin Alavi ◽

...

Keyword(s):

Computed Tomography ◽

Ct Scan ◽

Sphenoid Sinus ◽

Post Mortem ◽

X Ray ◽

X Ray Computed

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Influence Rotation Speed of X-ray Computed Tomography on Image Quality

Japanese Journal of Radiological Technology ◽

10.6009/jjrt.kj00000922261 ◽

2004 ◽

Vol 60 (1) ◽

pp. 79-86 ◽

Cited By ~ 2

Author(s):

ISAO YAMAGUCHI ◽

AKIRA MORIMOTO

Keyword(s):

Computed Tomography ◽

Image Quality ◽

Rotation Speed ◽

X Ray ◽

X Ray Computed

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Detection and Quantification of Cracking in Concrete Aggregate through Virtual Data Fusion of X-Ray Computed Tomography Images

Materials ◽

10.3390/ma13183921 ◽

2020 ◽

Vol 13 (18) ◽

pp. 3921

Author(s):

Tyler Oesch ◽

Frank Weise ◽

Giovanni Bruno

Keyword(s):

Computed Tomography ◽

Data Fusion ◽

Crack Detection ◽

Concrete Aggregate ◽

X Ray ◽

Computed Tomography Images ◽

Mineralogical Characteristics ◽

X Ray Computed ◽

Ct Data ◽

Virtual Data

In this work, which is part of a larger research program, a framework called “virtual data fusion” was developed to provide an automated and consistent crack detection method that allows for the cross-comparison of results from large quantities of X-ray computed tomography (CT) data. A partial implementation of this method in a custom program was developed for use in research focused on crack quantification in alkali-silica reaction (ASR)-sensitive concrete aggregates. During the CT image processing, a series of image analyses tailored for detecting specific, individual crack-like characteristics were completed. The results of these analyses were then “fused” in order to identify crack-like objects within the images with much higher accuracy than that yielded by any individual image analysis procedure. The results of this strategy demonstrated the success of the program in effectively identifying crack-like structures and quantifying characteristics, such as surface area and volume. The results demonstrated that the source of aggregate has a very significant impact on the amount of internal cracking, even when the mineralogical characteristics remain very similar. River gravels, for instance, were found to contain significantly higher levels of internal cracking than quarried stone aggregates of the same mineralogical type.

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