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Computed Tomography

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...

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Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Published on: March 14, 2018

A new high-resolution computed tomography (CT) segmentation method for trabecular bone architectural analysis.

Heike Scherf¹, Rico Tilgner

¹Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany. heike.scherf@eva.mpg.de

American Journal of Physical Anthropology

|March 13, 2009

Summary

A new Ray Casting Algorithm (RCA) offers accurate, automated segmentation for 3D bone structures from high-resolution CT scans. This method surpasses traditional techniques for analyzing fossil and recent cancellous bone with improved reliability.

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Area of Science:

Paleoanthropology
Biomedical Imaging
Bone Histology

Background:

High-resolution computed tomography (CT) and micro-CT are valuable for anthropological studies, offering non-destructive 3D bone structure analysis.
Accurate bone segmentation is critical for precise measurements, particularly for trabecular bone, but no fully reliable method currently exists.
Existing CT techniques face challenges with image quality and artifact reduction, impacting segmentation accuracy.

Purpose of the Study:

To introduce a novel, automated, and accurate computerized segmentation method for high-resolution CT datasets of cancellous bone.
To evaluate the performance of the new Ray Casting Algorithm (RCA) against established image thresholding techniques.
To demonstrate the robustness and superior quality of the RCA method for analyzing both fossil and recent bone samples.

Main Methods:

Development and implementation of the Ray Casting Algorithm (RCA) for automated bone segmentation.
Comparative analysis of RCA against the half-maximum height protocol and adaptive iterative thresholding.
Testing the algorithm on high-resolution CT datasets of extant and fossil cancellous bone.

Main Results:

The Ray Casting Algorithm (RCA) provides a reproducible, accurate, and fully automated solution for bone segmentation.
RCA demonstrates superior performance compared to conventional thresholding methods, even with lower quality input images.
The method is robust against common CT artifacts such as noise, beam hardening, ring artifacts, and blurriness.

Conclusions:

The Ray Casting Algorithm (RCA) represents a significant advancement in the automated segmentation of cancellous bone from CT data.
RCA offers enhanced reliability and accuracy for anthropological and biomedical research involving bone structure analysis.
Optimal CT scanning parameters remain important, but RCA provides greater resilience to image quality variations.