Biomedical Commons^™

Atlas-Based Shared-Boundary Deformable Multi-Surface Models Through Multi-Material And Two-Manifold Dual Contouring, Tanweer Rashid, Sharmin Sultana, Mallar Chakravarty, Michel Albert Audette

Electrical & Computer Engineering Faculty Publications

This paper presents a multi-material dual “contouring” method used to convert a digital 3D voxel-based atlas of basal ganglia to a deformable discrete multi-surface model that supports surgical navigation for an intraoperative MRI-compatible surgical robot, featuring fast intraoperative deformation computation. It is vital that the final surface model maintain shared boundaries where appropriate so that even as the deep-brain model deforms to reflect intraoperative changes encoded in ioMRI, the subthalamic nucleus stays in contact with the substantia nigra, for example, while still providing a significantly sparser representation than the original volumetric atlas consisting of hundreds of millions of voxels. The …

Opioid Use Disorder Prediction Using Machine Learning Of Fmri Data, A. Temtam, Liangsuo Ma, F. Gerard Moeller, M. S. Sadique, K. M. Iftekharuddin, Khan M. Iftekharuddin (Ed.), Weijie Chen (Ed.)

Electrical & Computer Engineering Faculty Publications

According to the Centers for Disease Control and Prevention (CDC) more than 932,000 people in the US have died since 1999 from a drug overdose. Just about 75% of drug overdose deaths in 2020 involved Opioid, which suggests that the US is in an Opioid overdose epidemic. Identifying individuals likely to develop Opioid use disorder (OUD) can help public health in planning effective prevention, intervention, drug overdose and recovery policies. Further, a better understanding of prediction of overdose leading to the neurobiology of OUD may lead to new therapeutics. In recent years, very limited work has been done using statistical …

Evaluating Algorithms Used For Fetal Brain Scan Segmentation, Connor Stewart Burgess

Undergraduate Student Research Internships Conference

The goal for this project was to successfully segment a fetal brain scan (fetal scan) using the algorithms provided by the program Slicer3D. To better understand the hurdles that arose when segmenting a fetal scan, we first look at the segmentation of an adult brain scan. This will allow us to see the straightforward nature of a brain segmentation when a high quality, high resolution volume with distinct structures is available. After examining the adult brain scan, attention will be moved to the segmentation of the fetal scan, where we’ll first look at the algorithms used and methods followed. Finally …

Expansion Microscopy: A New Approach To Microscopic Evaluation, Ashley Ferri

Theses and Dissertations

Optical microscopy resolution is limited by the wavelengths of light and the series of microscope lenses and other optical components used to create a magnified image of cell structures in a sample. Often the cell structures are smaller or closer together than the resolution limits of a light microscope. In 2015 the Boyden group at the Massachusetts Institute of Technology (MIT) created a sample preparation technique, expansion microscopy which involves embedding biological samples in a crosslinked, swellable, hydrogel polymer that allows for uniform physical separation of cell components so that they can subsequently be resolved by light microscopy. Using the …

Development Of An Anatomically And Electrically Conductive Brain Phantom For Transcranial Magnetic Stimulation, Hamzah A. Magsood

Theses and Dissertations

Transcranial Magnetic Stimulation (TMS) is a non-invasive technique for diagnostics, prognostic, and treatments of various neurological diseases. However, the lack of anatomically realistic brain phantoms has made the experimental verification of stimulation strength in the form of induced electric fields/voltages in the brain tissues an impediment to developing new TMS coils, stimulators, and treatment protocols. There are significant technological, safety, and ethical limitations to test the potential TMS treatment procedures or develop enhancements and refine them on humans or animals. This work aims to bridge the gap by introducing and developing an innovative manufacturing and fabrications process to produce a …

An Integrated Multi-Modal Registration Technique For Medical Imaging, Xue Wang

FIU Electronic Theses and Dissertations

Registration of medical imaging is essential for aligning in time and space different modalities and hence consolidating their strengths for enhanced diagnosis and for the effective planning of treatment or therapeutic interventions. The primary objective of this study is to develop an integrated registration method that is effective for registering both brain and whole-body images. We seek in the proposed method to combine in one setting the excellent registration results that FMRIB Software Library (FSL) produces with brain images and the excellent results of Statistical Parametric Mapping (SPM) when registering whole-body images. To assess attainment of these objectives, the following …

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. …