Engineering Commons^™

Pre-Differentiation Of Human Neural Stem Cells Into Gabaergic Neurons Prior To Transplant Results In Greater Repopulation Of The Damaged Brain And Accelerates Functional Recovery After Transient Ischemic Stroke, Hima C. S Abeysinghe, Laita Bokhari, Anita F. Quigley, Mahesh A. Choolani, Jerry Chan, Gregory J. Dusting, Jeremy M. Crook, Nao R. Kobayashi, Carli Roulston

Australian Institute for Innovative Materials - Papers

2015 Abeysinghe et al. Introduction: Despite attempts to prevent brain injury during the hyperacute phase of stroke, most sufferers end up with significant neuronal loss and functional deficits. The use of cell-based therapies to recover the injured brain offers new hope. In the current study, we employed human neural stem cells (hNSCs) isolated from subventricular zone (SVZ), and directed their differentiation into GABAergic neurons followed by transplantation to ischemic brain. Methods: Pre-differentiated GABAergic neurons, undifferentiated SVZ-hNSCs or media alone were stereotaxically transplanted into the rat brain (n=7/group) 7 days after endothelin-1 induced stroke. Neurological outcome was assessed by neurological deficit …

Functional Brain Network Classification With Compact Representation Of Sice Matrices, Jianjia Zhang, Luping Zhou, Lei Wang, Wanqing Li

Faculty of Engineering and Information Sciences - Papers: Part A

Recently, sparse inverse covariance estimation (SICE) technique has been employed to model functional brain connectivity. The inverse covariance matrix (SICE matrix in short) estimated for each subject is used as a representation of brain connectivity to discriminate Alzheimers disease from normal controls. However, we observed that direct use of the SICE matrix does not necessarily give satisfying discrimination, due to its high dimensionality and the scarcity of training subjects. Looking into this problem, we argue that the intrinsic dimensionality of these SICE matrices shall be much lower, considering i) an SICE matrix resides on a Riemannian manifold of symmetric positive …

Neuroimaging And Neuromodulation Approaches To Study Eating Behavior And Prevent And Treat Eating Disorders And Obesity, D. Val-Laillet, E. Aarts, B. Weber, M. Ferrari, V. Quaresima, L. E. Stoeckel, M. Alonso-Alonso, M. Audette, C. H. Malbert, E. Stice

Computational Modeling & Simulation Engineering Faculty Publications

Functional, molecular and genetic neuroimaging has highlighted the existence of brain anomalies and neural vulnerability factors related to obesity and eating disorders such as binge eating or anorexia nervosa. In particular, decreased basal metabolism in the prefrontal cortex and striatum as well as dopaminergic alterations have been described in obese subjects, in parallel with increased activation of reward brain areas in response to palatable food cues. Elevated reward region responsivity may trigger food craving and predict future weight gain. This opens the way to prevention studies using functional and molecular neuroimaging to perform early diagnostics and to phenotype subjects at …

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. …

Registration Of In-Vivo To Ex-Vivo Mri Of Surgically Resected Specimens: A Pipeline For Histology To In-Vivo Registration., Maged Goubran, Sandrine De Ribaupierre, Robert R Hammond, Catherine Currie, Jorge G Burneo, Andrew G Parrent, Terry M Peters, Ali R Khan

Robarts Imaging Publications

BACKGROUND: Advances in MRI have the potential to improve surgical treatment of epilepsy through improved identification and delineation of lesions. However, validation is currently needed to investigate histopathological correlates of these new imaging techniques. The purpose of this work is to develop and evaluate a protocol for deformable image registration of in-vivo to ex-vivo resected brain specimen MRI. This protocol, in conjunction with our previous work on ex-vivo to histology registration, completes a registration pipeline for histology to in-vivo MRI, enabling voxel-based validation of novel and existing MRI techniques with histopathology.

NEW METHOD: A combination of image-based and landmark-based 3D …

The Multimodal Brain Tumor Image Segmentation Benchmark (Brats), Bjoern H. Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Khan M. Iftekharuddin, Syed M.S. Reza

Electrical & Computer Engineering Faculty Publications

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low-and high-grade glioma patients-manually annotated by up to four raters-and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%-85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions …

Technical Note: Phantom Study To Evaluate The Dose And Image Quality Effects Of A Computed Tomography Organ-Based Tube Current Modulation Technique, Diksha Gandhi, Dominic J. Crotty, Grant M. Stevens, Taly Gilat Schmidt

Biomedical Engineering Faculty Research and Publications

Purpose

This technical note quantifies the dose and image quality performance of a clinically available organ-dose-based tube current modulation (ODM) technique, using experimental and simulation phantom studies. The investigated ODM implementation reduces the tube current for the anterior source positions, without increasing current for posterior positions, although such an approach was also evaluated for comparison.

Methods

Axial CT scans at 120 kV were performed on head and chest phantoms on an ODM-equipped scanner (Optima CT660, GE Healthcare, Chalfont St. Giles, England). Dosimeters quantified dose to breast, lung, heart, spine, eye lens, and brain regions for ODM and 3D-modulation (SmartmA) settings. …