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Artificial Intelligence Algorithm to Classify Patient Specific Bone Density from DICOM Images and the Development of an Osteoporosis Screening Tool

Yeager, Monica M.
http://orcid.org/0000-0001-6596-3877
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1575913132552859

Abstract Details

2019, Master of Science (M.S.), University of Dayton, Electrical Engineering.
The purpose of this thesis was to develop an artificial intelligence algorithm to classify patient specific bone density from DICOM images acquired from orthodontic radiographic scans and to develop an osteoporosis screening tool. Osteoporosis is a degenerative disease that results in weakened, brittle bones; unfortunately, this disease presents no outward symptoms until a bone is fractured. The goal of this research was to develop a method to assist in the early diagnosis of this disease using routine dental and orthodontic scans. Bone density in this thesis was approximated by pixel intensities from patient DICOM images. Individual cephalometric patient scans from an orthodontist were read into a custom MATLAB algorithm, which extracted points from the patient’s alveolar bone and determined the pixel intensity as an indicator for bone density. The alveolar (anterior mandible) bone was analyzed due to a correlation between tooth loss and osteoporosis documented in the literature. The intensity values of these pixels were averaged together as one global value for each patient. By comparing these global values versus age for 32 patients, a correlation between patient age and bone density was evident: as patients increase in age past 35 years, their bone density decreases, with different trend characteristics for men versus women. The results of this thesis provide a basis for the creation of a commercialized graphical user interface to aid medical professionals in the early detection of decreasing bone density in their patients.
Amy Neidhard-Doll, Ph.D. (Committee Chair)
Guru Subramanyam, Ph.D. (Committee Member)
Bradley Ratliff, Ph.D. (Committee Member)
Raj Kulkarni, D.M.D. (Committee Member)
88 p.
Biomedical Engineering; Electrical Engineering; Engineering
bone density from DICOM; osteoporosis screening tool; patient specific; artificial intelligence; medical image processing; MATLAB

Recommended Citations

Citations

  • Yeager, M. M. (2019). Artificial Intelligence Algorithm to Classify Patient Specific Bone Density from DICOM Images and the Development of an Osteoporosis Screening Tool [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1575913132552859

    APA Style (7th edition)

  • Yeager, Monica. Artificial Intelligence Algorithm to Classify Patient Specific Bone Density from DICOM Images and the Development of an Osteoporosis Screening Tool. 2019. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1575913132552859.

    MLA Style (8th edition)

  • Yeager, Monica. "Artificial Intelligence Algorithm to Classify Patient Specific Bone Density from DICOM Images and the Development of an Osteoporosis Screening Tool." Master's thesis, University of Dayton, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1575913132552859

    Chicago Manual of Style (17th edition)

dayton1575913132552859
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© 2019, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.