Engineering Commons^™

Next Generation In-Vivo Forward Solution Physiological Model Of The Human Lower Limb To Predict Implanted Knee Mechanics, Bradley Allen Meccia

Doctoral Dissertations

Current total knee arthroplasty (TKA) evaluation methods are both time consuming and expensive. They require fabrication of the TKA and then utilize a wear or cadaveric simulator which does not necessarily replicate in-vivo conditions. Other analysis methods involve following the long-term success of TKA in subjects for five or more years. Mathematical modeling of TKA provide an efficient method at a greatly reduced cost for evaluating TKA. Obviously, the accuracy of a mathematical model is extremely important to the validity of the results.

Mathematical modeling of the knee faces many difficulties. The number of muscles actuating the knee is much …

Adaptive Kernel Estimation For Enhanced Filtering And Pattern Classification Of Magnetic Resonance Imaging: Novel Techniques For Evaluating The Biomechanics And Pathologic Conditions Of The Lumbar Spine, Nicholas Vincent Battaglia

Doctoral Dissertations

This dissertation investigates the contribution the lumbar spine musculature has on etiological and pathogenic characteristics of low back pain and lumbar spondylosis. This endeavor necessarily required a two-step process: 1) design of an accurate post-processing method for extracting relevant information via magnetic resonance images and 2) determine pathological trends by elucidating high-dimensional datasets through multivariate pattern classification. The lumbar musculature was initially evaluated by post-processing and segmentation of magnetic resonance (MR) images of the lumbar spine, which characteristically suffer from nonlinear corruption of the signal intensity. This so called intensity inhomogeneity degrades the efficacy of traditional intensity-based segmentation algorithms. Proposed …