A. James Clark School of Engineering

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Subject: search.filters.subject.Health Sciences, Medicine and Surgery

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    Humeral Fracture Fixation Techniques: A FEA comparison of locing and compression techniques with cadaveric pullout comparison of cortical compression and internal locking screws.
    (2007-08-13) Johnson, Aaron; Barker, Donald; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Locking and non-locking humeral repair techniques provide different mechanical constructs for securing fractures, and consequently could generate different strain fields at the callus. The purpose of this study was to investigate the strain field callus, and to compare to determine if one construct offers a healing advantage over another. An FEA analysis was conducted using ABAQUS, with all contact surfaces modeled as friction interfaces; additionally, a pretension was applied to the non-locking construct to simulate the effect of installation. The models were subjected to axial tension loads, and results were compared with existing cadaveric and synthetic experimental loading. Additional validation involved screw pullout testing conducted on cadaveric humeri. Results showed that the strain fields at the fracture site showed no significant variation in distribution, shape, or magnitude, therefore concluding that the locking plate offered no biomechanical healing advantage.
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    HARDWARE-ACCELERATED AUTOMATIC 3D NONRIGID IMAGE REGISTRATION
    (2007-05-02) Hemaraj, Yashwanth; Shekhar, Raj; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Software implementations of 3D nonrigid image registration, an essential tool in medical applications like radiotherapies and image-guided surgeries, run excessively slow on traditional computers. These algorithms can be accelerated using hardware methods by exploiting parallelism at different levels in the algorithm. We present here, an implementation of a free-form deformation-based algorithm on a field programmable gate array (FPGA) with a customized, parallel and pipelined architecture. We overcome the performance bottlenecks and gain speedups of up to 40x over traditional computers while achieving accuracies comparable to software implementations. In this work, we also present a method to optimize the deformation field using a gradient descent-based optimization scheme and solve the problem of mesh folding, commonly encountered during registration using free-form deformations, using a set of linear constraints. Finally, we present the use of novel dataflow modeling tools to automatically map registration algorithms to hardware like FPGAs while allowing for dynamic reconfiguration.