Browsing by Subject "Fourier analysis"

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    The effects of remodeling with heart failure on mode of initiation of ventricular fibrillation and its spatiotemporal organization
    (Springer, 2015-09) Everett, Thomas H.; Hulley, George S.; Lee, Ken W.; Chang, Roger; Wilson, Emily E.; Olgin, Jeffrey E.; Department of Medicine, IU School of Medicine
    Purpose The effect of the heart failure substrate on the initiation of ventricular fibrillation (VF) and its resulting mechanism is not known. The objective of this study was to determine the effects of substrate on VF initiation and its spatiotemporal organization in the heart failure model. Methods Optical action potentials were recorded from LV wedge preparations either from structurally normal hearts (control, n = 11) or from congestive heart failure (CHF; n = 7), at the epicardial surface, endocardial surface which included a papillary muscle, and a transmural cross section. Action potential duration (APD80) was determined, and VF was initiated. A fast Fourier transform was calculated, and the dominant frequency (DF) was determined. Results The CHF group showed increased VF vulnerability (69 vs 26 %, p < 0.03), and every mapped surface showed an APD80 gradient which included islands of higher APDs on the transmural surface (M cells) which was not observed in controls. VF in the CHF group was characterized by stable, discrete, high-DF areas that correlated to either foci or spiral waves located on the transmural surface at the site of the papillary muscle. Overall, the top 10 % of DFs correlated to an APD of 101 ms while the bottom 10 % of DFs correlated to an APD of 126 ms (p < 0.01). Conclusions In the CHF model, APD gradients correlated with an increased vulnerability to VF, and the highest stable DFs were located on the transmural surface which was not seen in controls. This indicates that the CHF substrate creates unique APD and DF characteristics.
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    Morphometric analysis of hippocampal subfields : segmentation, quantification and surface modeling
    (2014) Cong, Shan; Rizkalla, Maher E.; Shen, Li (Radiologist); Du, Yingzi, 1975-
    Object segmentation, quantification, and shape modeling are important areas inmedical image processing. By combining these techniques, researchers can find valuableways to extract and represent details on user-desired structures, which can functionas the base for subsequent analyses such as feature classification, regression, and prediction. This thesis presents a new framework for building a three-dimensional (3D) hippocampal atlas model with subfield information mapped onto its surface, with which hippocampal surface registration can be done, and the comparison and analysis can be facilitated and easily visualized. This framework combines three powerful tools for automatic subcortical segmentation and 3D surface modeling. Freesurfer and Functional magnetic resonance imaging of the brain's Integrated Registration and Segmentation Tool (FIRST) are employed for hippocampal segmentation and quantification, while SPherical HARMonics (SPHARM) is employed for parametric surface modeling. This pipeline is shown to be effective in creating a hippocampal surface atlas using the Alzheimer's Disease Neuroimaging Initiative Grand Opportunity and phase 2 (ADNI GO/2) dataset. Intra-class Correlation Coefficients (ICCs) are calculated for evaluating the reliability of the extracted hippocampal subfields. The complex folding anatomy of the hippocampus offers many analytical challenges, especially when informative hippocampal subfields are usually ignored in detailed morphometric studies. Thus, current research results are inadequate to accurately characterize hippocampal morphometry and effectively identify hippocampal structural changes related to different conditions. To address this challenge, one contribution of this study is to model the hippocampal surface using a parametric spherical harmonic model, which is a Fourier descriptor for general a 3D surface. The second contribution of this study is to extend hippocampal studies by incorporating valuable hippocampal subfield information. Based on the subfield distributions, a surface atlas is created for both left and right hippocampi. The third contribution is achieved by calculating Fourier coefficients in the parametric space. Based on the coefficient values and user-desired degrees, a pair of averaged hippocampal surface atlas models can be reconstructed. These contributions lay a solid foundation to facilitate a more accurate, subfield-guided morphometric analysis of the hippocampus and have the potential to reveal subtle hippocampal structural damage associated.