Term of Award
Summer 2021
Degree Name
Master of Science in Mathematics (M.S.)
Document Type and Release Option
Thesis (restricted to Georgia Southern)
Copyright Statement / License for Reuse
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Department of Mathematical Sciences
Committee Chair
Jiehua Zhu
Committee Member 1
Yan Wu
Committee Member 2
Yongki Lee
Abstract
In this thesis, we analyze and perform image classification on lung X-Ray images with three state of the art convolutional neural networks. The design of Inception Resnetv2, Weakly Supervised Data Augmentation, and Discriminative Filter Bank convolutional neural networks are analyzed. We conduct image classification using the aforementioned methods with clinical x-ray chest images and review the results. The image set consists of three types of lung conditions: Normal, COVID 19, and Viral Pneumonia. It is shown that these methods effectively detect differences between COVID 19 and Viral Pneumonia.
OCLC Number
1267991485
Catalog Permalink
https://galileo-georgiasouthern.primo.exlibrisgroup.com/permalink/01GALI_GASOUTH/1r4bu70/alma9916469450102950
Recommended Citation
Douglas, Leslie J., "Automated Detection of COVID-19 with X-ray images by Neural Network Based Algorithms" (2021). Electronic Theses and Dissertations. 2284.
https://digitalcommons.georgiasouthern.edu/etd/2284
Research Data and Supplementary Material
No
