Doctoral Dissertations

Abstract

Medical imaging ranges in modality including computer tomography imaging, x-ray imaging, digital microscopy, and macro-focus dermoscopy images. The latter two modalities are the focus of the presented work.

To perform a diagnostic evaluation on the captured dermoscopy image, it begins with what is usually a labor-intensive operation that requires an expert to perform the initial segmentation for localizing a region of interest (ROI). Once that ROI is obtained, a physician with years of training and experience will observe biological markers that can be used to visually differentiate whether a lesion is benign or malignant. A similar process is used for digital microscopy images. Once a sample has been prepared by slicing and staining a specimen, the ROI of the captured image is also localized and again a physician then judges the subtle difference in the ROI to deduce a diagnostic score.

All this relies on having image data to use for machine learning as well as creating image-processing algorithms. Research is a way to infer how much data is needed given the current state-of-the-art methodologies. Data collection is hampered by the fact that, traditionally, medical data is treated differently than other forms of images and metadata in that a patient is entitled to privacy thus making assembling a large medical dataset difficult as well as limiting its release via open source.

The presented work demonstrates methods that machine learning and image processing researchers could leverage to overcome the previously mentioned difficulties with the goal being to aid the physician in an effort to increase the number of cases that can be screened and/or evaluated.

Advisor(s)

Stanley, R. Joe

Committee Member(s)

Kim, Chang-Soo
Wunsch, Donald C.
Moss, Randy Hays, 1953-
Stoecker, William V.

Department(s)

Electrical and Computer Engineering

Degree Name

Ph. D. in Computer Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2025

Journal article titles appearing in thesis/dissertation

Paper I, found on pages 4–29, has been published in the IEEE Journal of Biomedical and Health Informatics, in July 2019.
Paper II, found on pages 30–59, has been published in the Journal of Pathology Informatics, in March 2020.
Paper III, found on pages 60–74, has been published in Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, in February 2017.

Pagination

xi, 78 pages

Note about bibliography

Includes_bibliographical_references_(page 77)

Rights

© 2025 Jason Hagerty , All Rights Reserved

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 12509

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