Physical Sciences and Mathematics Commons^™

Positron Emission Tomography (Pet) For Flow Measurement, Bi Yao Zhang

Masters Theses

Positron Emission Tomography (PET) is frequently used for medical imaging. Maturity and flexibility of PET as an imaging technique has expanded its utility beyond the medical domain. It can be used as a tool for fluid flow studies in opaque fluids and for flow within complex geometry where conventional optical flow measurement approaches fail. This study explores the capabilities of PET as flow measurement tool suited to validation of computational fluid dynamic (CFD) predictions.

The MicroPET P4 scanner was used to image the diffusion process in flow around a rod bundle geometry similar to that found in a nuclear reactor …

Dna− Gold Nanoparticle Reversible Networks Grown On Cell Surface Marker Sites: Application In Diagnostics, Kyuwan Lee

Kyuwan Lee

Effective identification of breast cancer stem cells (CSC) benefits from a multiplexed approach to detect cell surface markers that can distinguish this subpopulation, which can invade and proliferate at sites of metastasis. We present a new approach for dual-mode sensing based on targeting using pointer and signal enhancement using enhancer particle networks for detection by surface plasmon resonance (SPR) and surface-enhanced Raman scattering (SERS). We demonstrate our concept to detect cell surface markers, CD44 and CD24, in three breast cancer cell lines to identify a CD44+/CD24− subpopulation of CSCs. The designed network structure can be well-controlled and has improved sensitivity …

Heterogeneous Modeling Of Medical Image Data Using B-Spline Functions, Olya Grove

USF Tampa Graduate Theses and Dissertations

Ongoing developments in the field of medical imaging modalities have pushed the frontiers of modern medicine and biomedical engineering, prompting the need for new applications to improve diagnosis, treatment and prevention of diseases.

Biomedical data visualization and modeling rely predominately on manual processing and utilization of voxel and facet based homogeneous models. Biological structures are naturally heterogeneous and in order to accurately design and biomimic biological structures, properties such as chemical composition, size and shape of biological constituents need to be incorporated in the computational biological models.

Our proposed approach involves generating a density point cloud based on the intensity …

Biological Effective Dose (Bed) Distribution Matching For Obtaining Brachytherapy Prescription Doses & Dosimetric Optimization For Hybrid Seed Brachytherapy, Jakub Pritz

USF Tampa Graduate Theses and Dissertations

Radioactive seed implant brachytherapy is a common radiotherapy treatment method for prostate cancer. In current clinical practice, a seed consists of a single isotope, such as ¹²⁵I or ¹⁰³Pd. A seed containing a mixture of two isotopes has been proposed for prostate cancer treatment. This study investigates a method for defining a prescription dose for new seed compositions based on matching the biological equivalent dose (BED) of a reference plan.

Ten prostate cancer cases previously treated using single isotope seeds (5 using ¹²⁵I seeds and 5 using ¹⁰³Pd seeds) were selected for this study. Verification of …

Bcc Skin Cancer Diagnosis Based On Texture Analysis Techniques, Shao-Hui Chuang, Xiaoyan Sun, Wen-Yu Chang, Gwo-Shing Chen, Adam Huang, Jiang Li, Frederic D. Mckenzie

Electrical & Computer Engineering Faculty Publications

In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% …

Prediction Of Brain Tumor Progression Using Multiple Histogram Matched Mri Scans, Debrup Banerjee, Loc Tran, Jiang Li, Yuzhong Shen, Frederic Mckenzie, Jihong Wang, Ronald M. Summers (Ed.), Bram Van Ginneken (Ed.)

Electrical & Computer Engineering Faculty Publications

In a recent study [1], we investigated the feasibility of predicting brain tumor progression based on multiple MRI series and we tested our methods on seven patients' MRI images scanned at three consecutive visits A, B and C. Experimental results showed that it is feasible to predict tumor progression from visit A to visit C using a model trained by the information from visit A to visit B. However, the trained model failed when we tried to predict tumor progression from visit B to visit C, though it is clinically more important. Upon a closer look at the MRI scans …