Computer Science ETDs
Publication Date
7-1-2016
Abstract
Diabetes is an incurable metabolic disease characterized by high blood sugar levels. The feet of people with diabetes are at the risk of a variety of pathological consequences including peripheral vascular disease, deformity, ulceration, and ultimately amputation. The key to managing the diabetic foot is prevention and early detection. Unfortunately, current hospital centered reactive diabetes care and the availability of inadequate qualitative diagnostic screening procedures causes physicians to miss the diagnosis in 61% of the patients. We have developed a computer aided diagnostic system for early detection of diabetic foot. The key idea is that diabetic foot exhibits significant neuropathic and vascular damages. When a diabetic foot is placed under cold stress, the thermal recovery will be much slower. This thermal recovery speed can be a quantitative measure for the diagnosis of diabetic foot condition. In our research, thermal recovery of the feet following cold stress is captured using an infrared camera. The captured infrared video is then filtered, segmented, and registered. The temperature recovery at each point on the foot is extracted and analyzed using a thermal regulation model, and the problematic regions are identified. In this thesis, we present our research on the following aspects of the developed computer aided diagnostic systems: subject measurement protocols, a trustful numerical model of the camera noise and noise parameter estimations, infrared video segmentation, new models of thermal regulations, thermal patterns classifications, and our preliminary findings based on small scale clinical study of about 40 subjects, which demonstrated the potential the new diagnostic system.
Language
English
Keywords
Diabetes, Control theory, Thermal infrared, Image processing, Video processing, cold stress, thermal recovery, thermal regulation, thermoregulation, classification, filcker noise, vasoconstriction, vasodilation
Document Type
Dissertation
Degree Name
Computer Science
Level of Degree
Doctoral
Department Name
Department of Computer Science
First Committee Member (Chair)
Estrada-Piedra, Trilce
Second Committee Member
Soliz, Peter
Third Committee Member
Yang, Yin
Project Sponsors
National Institute of Diabetes and Digestive and Kidney Diseases Grant DK093192 National Science Foundation Grant CBET-0853157
Recommended Citation
Chekh, Viktor. "COMPUTER-AIDED QUANTITATIVE EARLY DIAGNOSIS OF DIABETIC FOOT." (2016). https://digitalrepository.unm.edu/cs_etds/75