Biomedical Engineering and Bioengineering Commons^™

Mobile Cloud Computing Based Non Rigid Registration For Image Guided Surgery, Arun Brahmavar Vishwanatha

Computer Science Theses & Dissertations

In this thesis we present the design and implementation of a Mobile Cloud computing platform for non-rigid registration required in Image Guided Surgery (MCIGS). MCIGS contributes in flexible, portable and accurate alignment of pre-operative brain data with intra-operative MRI, for image guided diagnosis and therapy and endoscopic skull base surgery. Improved precision of image guided therapy and specifically neurosurgery procedures is known to result in the improved prognosis for brain tumor patients. MCI GS system is tested with Physics Based Non-Rigid Registration method form ITK. Our preliminary results for brain images indicate that the proposed system over Wi-Fi can be …

A Comparative Study Of Two Prediction Models For Brain Tumor Progression, Deqi Zhou, Loc Tran, Jihong Wang, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images.

We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. …

Evaluation Of The Effects Of A Plasma Activated Medium On Cancer Cells, S. Mohades, M. Laroussi, J. Sears, N. Barekzi, H. Razavi

Electrical & Computer Engineering Faculty Publications

The interaction of low temperature plasma with liquids is a relevant topic of study to the field of plasma medicine. This is because cells and tissues are normally surrounded or covered by biological fluids. Therefore, the chemistry induced by the plasma in the aqueous state becomes crucial and usually dictates the biological outcomes. This process became even more important after the discovery that plasma activated media can be useful in killing various cancer cell lines. Here, we report on the measurements of concentrations of hydrogen peroxide, a species known to have strong biological effects, produced by application of plasma to …

Killing Adherent And Nonadherent Cancer Cells With The Plasma Pencil, Mounir Laroussi, Soheila Mohades, Nazir Barekzi

Electrical & Computer Engineering Faculty Publications

The application of low temperature plasmas in biology and medicine may lead to a paradigm shift in the way various diseases can be treated without serious side effects. Low temperature plasmas generated in gas mixtures that contain oxygen or air produce several chemically reactive species that have important biological implications when they interact with eukaryotic or prokaryotic cells. Here, a review of the effects of low temperature plasma generated by the plasma pencil on different cancerous cells is presented. Results indicate that plasma consistently shows a delayed killing effect that is dose dependent. In addition, there is some evidence that …

Adaptive Graph Construction For Isomap Manifold Learning, Loc Tran, Zezhong Zheng, Guoquing Zhou, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the ℓ₁ norm. The ℓ₁ enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than …

Proton-Electrostatic Localization: Explaining The Bioenergetic Conundrum In Alkalophilic Bacteria, James Weifu Lee

Chemistry & Biochemistry Faculty Publications

The decades-longstanding energetic conundrum of alkalophilic bacteria as to how they are able to synthesize ATP has now, for the first time, been clearly solved using the proton-electrostatics localization hypothesis. This is a major breakthrough advance in understanding proton-coupling bioenergetics over the Nobel-prize work of Peter Mitchell’s chemiosmotic theory. The widespread textbook Mitchellian proton motive force (pmf) equation has now been significantly revised. Use of the newly derived equation results in an overall pmf value (215~233 mV) that is more than 4 times larger than that (44.3 mV) calculated from the Mitchellian equation for the alkalophilic bacteria growing at pH …

Multi-Surface Simplex Spine Segmentation For Spine Surgery Simulation And Planning, Rabia Haq

Computational Modeling & Simulation Engineering Theses & Dissertations

This research proposes to develop a knowledge-based multi-surface simplex deformable model for segmentation of healthy as well as pathological lumbar spine data. It aims to provide a more accurate and robust segmentation scheme for identification of intervertebral disc pathologies to assist with spine surgery planning. A robust technique that combines multi-surface and shape statistics-aware variants of the deformable simplex model is presented. Statistical shape variation within the dataset has been captured by application of principal component analysis and incorporated during the segmentation process to refine results. In the case where shape statistics hinder detection of the pathological region, user-assistance is …