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

Date of Award

2019

Degree Name

M.S. in Electrical Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Advisor: Amy Neidhard-Doll

Abstract

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.

Keywords

Biomedical Engineering, Electrical Engineering, Engineering, bone density from DICOM, osteoporosis screening tool, patient specific, artificial intelligence, medical image processing, MATLAB

Rights Statement

Copyright © 2019, author

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