Date Available
5-1-2014
Year of Publication
2014
Document Type
Doctoral Dissertation
Degree Name
Doctor of Philosophy (PhD)
College
Engineering
Department/School/Program
Computer Science
Advisor
Dr. Nathan Jacobs
Co-Director of Graduate Studies
Dr. Judy Goldsmith
Abstract
This dissertation was inspired by difficult decisions patients of chronic diseases have to make about about treatment options in light of uncertainty. We look at rheumatoid arthritis (RA), a chronic, autoimmune disease that primarily affects the synovial joints of the hands and causes pain and deformities. In this work, we focus on several parts of a computer-based decision tool that patients can interact with using gestures, ask questions about the disease, and visualize possible futures. We propose a hand gesture based interaction method that is easily setup in a doctor's office and can be trained using a custom set of gestures that are least painful. Our system is versatile and can be used for operations like simple selections to navigating a 3D world. We propose a point distribution model (PDM) that is capable of modeling hand deformities that occur due to RA and a generalized fitting method for use on radiographs of hands. Using our shape model, we show novel visualization of disease progression. Using expertly staged radiographs, we propose a novel distance metric learning and embedding technique that can be used to automatically stage an unlabeled radiograph. Given a large set of expertly labeled radiographs, our data-driven approach can be used to extract different modes of deformation specific to a disease.
Recommended Citation
Mihail, Radu P., "Visualizing and Predicting the Effects of Rheumatoid Arthritis on Hands" (2014). Theses and Dissertations--Computer Science. 19.
https://uknowledge.uky.edu/cs_etds/19
