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Improving Gross Anatomy : = Enhancing the Information Content of Cadaveric CT Scans and Models.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Improving Gross Anatomy :/
Reminder of title:	Enhancing the Information Content of Cadaveric CT Scans and Models.
Author:	Lewis, Steven A.
Description:	1 online resource (174 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 84-12, Section: B.
Contained By:	Dissertations Abstracts International84-12B.
Subject:	Biomedical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9798379735074

Improving Gross Anatomy : = Enhancing the Information Content of Cadaveric CT Scans and Models.
Lewis, Steven A.

Improving Gross Anatomy :Enhancing the Information Content of Cadaveric CT Scans and Models. - 1 online resource (174 pages)

Source: Dissertations Abstracts International, Volume: 84-12, Section: B.

Thesis (Ph.D.)--State University of New York at Buffalo, 2023.

Includes bibliographical references

Gross anatomy has been primarily taught and researched through the use of cadaveric dis-section for hundreds of years. COVID-19 demonstrated that medical schools cannot sustain gross anatomy education and research through these traditional methods alone. There is a desperate need for the development of new gross anatomy courses that leverage these traditional approaches, but also modern computer vision and biomedical engineering techniques. These techniques are becoming more and more important to the fields of medicine. The purpose of this thesis is to explore the ways in which computer vision, modeling, and analysis can enhance traditional gross anatomy education and research. This is achieved through the analysis of cadaveric, non-contrast enhanced (NCE), whole-body CT imaging, and 3D modelling of anatomical structures.In this work, we hypothesize that state-of-the art computer vision can enhance the information content of these CT images and 3D models for the purpose of gross anatomy education and research. We explore this hypothesis in a variety of ways. We first analyze different physical and computational methods to enhance the image quality of cadaveric, NCE, whole-body CT. Additionally, we demonstrate that cadaveric, NCE whole-body CT can be leveraged for multi-organ segmentation. We also use cadaveric segmentations and 3D models to supplement our understanding of the rare disease Seckel Syndrome, and the variation present in kidney models. Finally, we apply this framework to the teaching of graduate students in gross anatomy. Our results indicate that a pipeline such as this can in fact improve gross anatomy education and research.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798379735074Subjects--Topical Terms:

588770
Biomedical engineering.
Subjects--Index Terms:

Artificial intelligenceIndex Terms--Genre/Form:

554714
Electronic books.

Improving Gross Anatomy : = Enhancing the Information Content of Cadaveric CT Scans and Models.
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