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Updated: May 14, 2026

Image Rendering Techniques in Postmortem Computed Tomography: Evaluation of Biological Health and Profile in Stranded Cetaceans

Published on: September 27, 2020

Forensic considerations for preprocessing effects on clinical MDCT scans.

Andrew D Wade¹, Gerald J Conlogue

¹Department of Anthropology, University of Western Ontario, London, Ontario, Canada, N6A 5C2. awade4@uwo.ca

Journal of Forensic Sciences

|February 15, 2013

Summary

This summary is machine-generated.

Computed tomography (CT) image preprocessing significantly alters raw data, impacting artifact appearance. Different reconstruction algorithms and scanning parameters can mitigate these effects, crucial for medico-legal image analysis.

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Assessing Cortical Cerebral Microinfarcts on High Resolution MR Images

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Published on: November 20, 2015

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Last Updated: May 14, 2026

Image Rendering Techniques in Postmortem Computed Tomography: Evaluation of Biological Health and Profile in Stranded Cetaceans

Published on: September 27, 2020

Assessing Cortical Cerebral Microinfarcts on High Resolution MR Images

Assessing Cortical Cerebral Microinfarcts on High Resolution MR Images

Published on: November 20, 2015

Area of Science:

Medical Imaging
Forensic Science
Radiology

Background:

Digital image manipulation requires documentation, similar to computed tomography (CT) data.
CT image reconstruction involves preprocessing raw data into viewable images.
This preprocessing step, though occurring at the source, alters image data and requires accounting.

Purpose of the Study:

To assess the impact of different CT preprocessing algorithms on image output.
To evaluate how preprocessing affects the appearance of fragments, artifacts, and soft tissue in CT scans.
To determine if preprocessing algorithms and scanning parameters can overcome image artifacts.

Main Methods:

Repeated CT scans of a gunshot wound phantom were performed.
A Toshiba Aquilion 64-slice multidetector CT scanner was utilized.
Image output was assessed following preprocessing with varying algorithms.

Main Results:

Substantial differences in image output were observed with different preprocessing algorithms.
Preprocessing effects varied in the presence of high-density inclusions.
Specific algorithms and parameters influenced the appearance of fragments and artifacts.

Conclusions:

CT image preprocessing significantly alters image output and must be documented.
Preprocessing affects image quality differently, especially with high-density inclusions.
Optimizing preprocessing algorithms and scanning parameters can help manage and overcome CT image artifacts.