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

Bibliographic Data

ID8317489
AuthorsHeike Scherf (Max Planck Society, corresponding author), Rico Tilgner (Leipzig University of Applied Sciences)
Year2009
Volume140
Issue1
Pages39-51
Publication date2009-09-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAmerican Journal of Physical Anthropology (JOURNAL)
Journal identifiersISSN: 0002-9483 • E-ISSN: 1096-8644
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ajpa.21033
PMID19280676
OpenAlexW2085568596
LanguageEN
Citations received22
References cited30

In the last decade, high‐resolution computed tomography (CT) and microcomputed tomography (micro‐CT) have been increasingly used in anthropological studies and as a complement to traditional histological techniques. This is due in large part to the ability of CT techniques to nondestructively extract three‐dimensional representations of bone structures. Despite prior studies employing CT techniques, no completely reliable method of bone segmentation has been established. Accurate preprocessing of digital data is crucial for measurement accuracy, especially when subtle structures such as trabecular bone are investigated. The research presented here is a new, reproducible, accurate, and fully automated computerized segmentation method for high‐resolution CT datasets of fossil and recent cancellous bone: the Ray Casting Algorithm (RCA). We compare this technique with commonly used methods of image thresholding (i.e., the half‐maximum height protocol and the automatic, adaptive iterative thresholding procedure). While the quality of the input images is crucial for conventional image segmentation, the RCA method is robust regarding the signal to noise ratio, beam hardening, ring artifacts, and blurriness. Tests with data of extant and fossil material demonstrate the superior quality of RCA compared with conventional thresholding procedures, and emphasize the need for careful consideration of optimal CT scanning parameters. Am J Phys Anthropol 2009. © 2009 Wiley‐Liss, Inc

Cancellous bone · Computer vision · Image (mathematics) · Pattern recognition (psychology) · Preprocessor · Radiology · Segmentation · Thresholding · Tomography · AI in cancer detection · Anatomy · Artificial Intelligence · Computer Science · Medical Image Segmentation Techniques · Medical Imaging and Analysis · Medicine

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