Engineering Commons^™

On The Application Of Mechanical Vibration In Robotics-Assisted Soft Tissue Intervention, Iman Khalaji

Electronic Thesis and Dissertation Repository

Mechanical vibration as a way of transmitting energy has been an interesting subject to study. While cyclic oscillation is usually associated with fatigue effect, and hence a detrimental factor in failure of structures and machineries, by controlled transmission of vibration, energy can be transferred from the source to the target. In this thesis, the application of such mechanical vibration in a few surgical procedures is demonstrated.

Three challenges associated with lung cancer diagnosis and treatment are chosen for this purpose, namely, Motion Compensation, tumor targeting in lung Needle Insertion and Soft Tissue Dissection:

1. A robotic solution is proposed …

Modeling And Development Of Iterative Reconstruction Algorithms In Emerging X-Ray Imaging Technologies, Jiaofeng Xu

All Theses and Dissertations (ETDs)

Many new promising X-ray-based biomedical imaging technologies have emerged over the last two decades. Five different novel X-ray based imaging technologies are discussed in this dissertation: differential phase-contrast tomography (DPCT), grating-based phase-contrast tomography (GB-PCT), spectral-CT (K-edge imaging), cone-beam computed tomography (CBCT), and in-line X-ray phase contrast (XPC) tomosynthesis. For each imaging modality, one or more specific problems prevent them being effectively or efficiently employed in clinical applications have been discussed. Firstly, to mitigate the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods in DPCT, we analyze the numerical and statistical properties of two classes …

Quantized Nonnegative Matrix Factorization, Ruairí De Fréin

Conference papers

Even though Nonnegative Matrix Factorization (NMF) in its original form performs rank reduction and signal compaction implicitly, it does not explicitly consider storage or transmission constraints. We propose a Frobenius-norm Quantized Nonnegative Matrix Factorization algorithm that is 1) almost as precise as traditional NMF for decomposition ranks of interest (with in 1-4dB), 2) admits to practical encoding techniques by learning a factorization which is simpler than NMF’s (by a factor of 20-70) and 3) exhibits a complexity which is comparable with state-of-the-art NMF methods. These properties are achieved by considering the quantization residual via an outer quantization optimization step, in …