Generating statistical shape models of osteological structure from cadaveric CT data

Matthew Wysocki; Scott Doyle

doi:10.1117/12.2612674

4 April 2022 Generating statistical shape models of osteological structure from cadaveric CT data

Matthew Wysocki, Scott Doyle

Proceedings Volume 12036, Medical Imaging 2022: Biomedical Applications in Molecular, Structural, and Functional Imaging; 120361F (2022) https://doi.org/10.1117/12.2612674
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

Cadaveric computed tomography (CT) data are incredibly valuable resources that can support a variety of biomedical education and research endeavors.1–6 These tremendous sources of anatomical information can be used to generate cadaver-specific 3D anatomical models to greatly enhance the learning outcomes for gross anatomy students.7 Unfortunately, cadaveric CT data are also inherently challenging to properly utilize. The main obstacles to successfully extracting accurate anatomical structures for this objective include: the presence of encompassing preserved soft tissue, immediately adjacent anatomical structures of the same tissue type as that of the structure of interest, and CT imaging artifacts that arise from metal medical implants (see Fig. 1). Consequently, it is unfeasible for anatomy faculty or gross anatomy students to obtain cadaveric-specific 3D anatomical models. Furthermore, the challenge of extracting accurate 3D anatomical morphology from cadaveric CT data obstructs many biomedical research avenues. The current investigation establishes a protocol for extracting and analyzing the morphology of osteological structures from cadaveric CT data, which can be employed to augment gross anatomy curricula and galvanize biomedical research.

Conference Presentation

Citation Download Citation

Matthew Wysocki and Scott Doyle "Generating statistical shape models of osteological structure from cadaveric CT data", Proc. SPIE 12036, Medical Imaging 2022: Biomedical Applications in Molecular, Structural, and Functional Imaging, 120361F (4 April 2022); https://doi.org/10.1117/12.2612674

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