Biomedical Engineering and Bioengineering Commons^™

A 3d Printed Axon-Mimetic Diffusion Mri Phantom, Tristan K. Kuehn

Electronic Thesis and Dissertation Repository

Diffusion MRI is used to non-invasively characterize the microstructure of the brain. However, the accuracy of the characterization is difficult to verify because no other non-invasive imaging modality provides the same information. This thesis presents a novel 3D printed axon-mimetic (3AM) diffusion MRI phantom, a synthetic object designed to mimic the brain's microstructure.

The phantoms were characterized using microscopy, synchrotron micro-computed tomography, and diffusion MRI, and found to have sufficiently axon-mimetic properties to be useful as diffusion MRI phantoms. A set of phantoms designed to have anatomically realistic and complex fibre structures was used to test the response of diffusion …

Computer-Assisted Characterization Of Prostate Cancer On Magnetic Resonance Imaging, Derek J. Soetemans

Electronic Thesis and Dissertation Repository

Prostate cancer (PCa) is one of the most prevalent cancers among men. Early diagnosis can improve survival and reduce treatment costs. Current inter-radiologist variability for detection of PCa is high. The use of multi-parametric magnetic resonance imaging (mpMRI) with machine learning algorithms has been investigated both for improving PCa detection and for PCa diagnosis. Widespread clinical implementation of computer-assisted PCa lesion characterization remains elusive; critically needed is a model that is validated against a histologic reference standard that is densely sampled in an unbiased fashion. We address this using our technique for highly accurate fusion of mpMRI with whole-mount …

Automated Segmentation Of Left And Right Ventricles In Mri And Classification Of The Myocarfium Abnormalities, Cyrus (Mohammad Saleh) Nambakhsh

Electronic Thesis and Dissertation Repository

A fundamental step in diagnosis of cardiovascular diseases, automated left and right ventricle (LV and RV) segmentation in cardiac magnetic resonance images (MRI) is still acknowledged to be a difficult problem. Although algorithms for LV segmentation do exist, they require either extensive training or intensive user inputs. RV segmentation in MRI has yet to be solved and is still acknowledged a completely unsolved problem because its shape is not symmetric and circular, its deformations are complex and varies extensively over the cardiac phases, and it includes papillary muscles. In this thesis, I investigate fast detection of the LV endo- and …