We propose a signal-detection approach for detecting brain activations from PET or fMRI images in... more We propose a signal-detection approach for detecting brain activations from PET or fMRI images in a two-state ("on-off") neuroimaging study. We model the activation pattern as a superposition of an unknown number of circular spatial basis functions of unknown position, size, and amplitude. We determine the number of these functions and their parameters by maximum a posteriori (MAP) estimation. To
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006
Abstract We propose an approach to analyzing functional neuroimages in which:(1) regions of neuro... more Abstract We propose an approach to analyzing functional neuroimages in which:(1) regions of neuronal activation are described by a superposition of spatial kernel functions, the parameters of which are estimated from the data; and (2) the presence of activation is detected by means of a generalized likelihood ratio test (GLRT). In an on-off design we model the spatial activation pattern as a sum of an unknown number of kernel functions of unknown location, amplitude and/or size. We employ two Bayesian methods of estimating ...
A new signal-detection approach for detecting brain activations from PET or fMRI images in a two-... more A new signal-detection approach for detecting brain activations from PET or fMRI images in a two-state (" on-off") neuroimaging study is proposed. The activation pattern is modeled as a superposition of an unknown number of circular spatial basis functions of unknown position, size, and amplitude. Also, the number of these functions and their parameters is determined by maximum a posteriori (MAP) estimation. To maximize the posterior distribution, a reversible-jump Markov-chain Monte-Carlo (RJMCMC) algorithm ...
A Bayesian approach is proposed for statistical analysis of fMRI data sets in a two state ("... more A Bayesian approach is proposed for statistical analysis of fMRI data sets in a two state ("on-off") activation study. The approach is based on the Relevance Vector Machine (RVM) regression framework. According to this approach the shape of the activations is a superposition of kernel functions, one at each pixel of the image, and a hierarchical Bayesian model is employed
Estimation of the intrinsic dimensionality of fMRI data is an important part of data analysis tha... more Estimation of the intrinsic dimensionality of fMRI data is an important part of data analysis that helps to separate the signal of interest from noise. We have studied multiple methods of dimensionality estimation proposed in the literature and used these estimates to select a subset of principal components that was subsequently processed by linear discriminant analysis (LDA). Using simulated multivariate Gaussian data, we show that the dimensionality that optimizes signal detection (in terms of the receiver operating characteristic (ROC) metric) goes through a transition from many dimensions to a single dimension as a function of the signal-to-noise ratio. This transition happens when the loci of activation are organized into a spatial network and the variance of the networked, task-related signals is high enough for the signal to be easily detected in the data. We show that reproducibility of activation maps is a metric that captures this switch in intrinsic dimensionality. Except...
2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821), 2004
We propose the use of the relevance vector machine (RVM) regression framework for statistical ana... more We propose the use of the relevance vector machine (RVM) regression framework for statistical analysis of PET or fMRI data sets in a two state ("on-off") activation study. According to this approach the shape of the activations is a superposition of kernel functions, one at each pixel of the image, of unknown amplitude and a hierarchical Bayesian model is employed
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006
Abstract We propose an approach to analyzing functional neuroimages in which:(1) regions of neuro... more Abstract We propose an approach to analyzing functional neuroimages in which:(1) regions of neuronal activation are described by a superposition of spatial kernel functions, the parameters of which are estimated from the data; and (2) the presence of activation is detected by means of a generalized likelihood ratio test (GLRT). In an on-off design we model the spatial activation pattern as a sum of an unknown number of kernel functions of unknown location, amplitude and/or size. We employ two Bayesian methods of estimating ...
Increased physical activity and higher adherence to a Mediterranean-type diet (MeDi) have been in... more Increased physical activity and higher adherence to a Mediterranean-type diet (MeDi) have been independently associated with reduced risk of Alzheimer's disease (AD). Their association has not been investigated with the use of biomarkers. This study examines whether, among cognitively normal (NL) individuals, those who are less physically active and show lower MeDi adherence have brain biomarker abnormalities consistent with AD. Forty-five NL individuals (age 54 ± 11, 71% women) with complete leisure time physical activity (LTA), dietary information, and cross-sectional 3D T1-weigthed MRI, (11)C-Pittsburgh Compound B (PiB) and (18)F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) scans were examined. Voxel-wise multivariate partial least square (PLS) regression was used to examine the effects of LTA, MeDi and their interaction on brain biomarkers. Age, gender, ethnicity, education, caloric intake, BMI, family history of AD, Apolipoprotein E (APOE) genotype, presence ...
Digital infrared iris photography using a modified digital camera system was performed on approxi... more Digital infrared iris photography using a modified digital camera system was performed on approximately 300 subjects seen during routine clinical care and research at one facility. Because this image database offered an opportunity to gain new insight into the potential utility of infrared iris imaging, it was surveyed for unique image patterns. Then, a selection of photographs was compiled that would illustrate the spectrum of this imaging experience. Potentially informative image patterns were observed in subjects with cataracts, diabetic retinopathy, Posner-Schlossman syndrome, iridociliary cysts, long anterior lens zonules, nevi, oculocutaneous albinism, pigment dispersion syndrome, pseudophakia, suspected vascular anomaly, and trauma. Image patterns were often unanticipated regardless of preexisting information and suggest that infrared iris imaging may have numerous potential clinical and research applications, some of which may still not be recognized. These observations suggest further development and study of this technology.
To investigate near infrared iris transillumination (NIRit) imaging as a new method to quantify p... more To investigate near infrared iris transillumination (NIRit) imaging as a new method to quantify pupil shape, size, and position because the imaging modality can uniquely provide simultaneous information regarding iris structural details that influence pupil characteristics and because exploration of related techniques could promote discovery helpful to clinical research and care. Digital NIRit images of normal and diseased eyes were used along with computer-assisted techniques to quantify four primary pupil parameters, including pupil roundness (PR), pupil ovalness (PO), pupil size (PS), and pupil eccentricity (PE). A combined measure of PR and PO was also developed (the pupil circularity index [PCI]). Repeatability of the measures was studied and example analyses were performed. Pupil measures could be calculated for right eyes of 307 subjects (164 normal, 143 other), with fewer than 0.5% exclusions due to image quality. Repeatability study did not show significant bias (P < .05) for any of the four primary measures. Example analyses could show age-associated differences in pupil shape (≥ 50 year olds had less regular pupils than < 50 year olds: median PCI = 0.009 vs 0.006; P < .01) and that a group of pigment dispersion syndrome subjects (n = 27) had less regular pupils than a group of matched controls (PO = 0.9966 vs 0.9990; P < .05). Digital NIRit imaging can provide novel, reliable, and informative methods to quantify pupil characteristics while providing simultaneous information about iris structure that may influence these parameters.
We propose a signal-detection approach for detecting brain activations from PET or fMRI images in... more We propose a signal-detection approach for detecting brain activations from PET or fMRI images in a two-state ("on-off") neuroimaging study. We model the activation pattern as a superposition of an unknown number of circular spatial basis functions of unknown position, size, and amplitude. We determine the number of these functions and their parameters by maximum a posteriori (MAP) estimation. To
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006
Abstract We propose an approach to analyzing functional neuroimages in which:(1) regions of neuro... more Abstract We propose an approach to analyzing functional neuroimages in which:(1) regions of neuronal activation are described by a superposition of spatial kernel functions, the parameters of which are estimated from the data; and (2) the presence of activation is detected by means of a generalized likelihood ratio test (GLRT). In an on-off design we model the spatial activation pattern as a sum of an unknown number of kernel functions of unknown location, amplitude and/or size. We employ two Bayesian methods of estimating ...
A new signal-detection approach for detecting brain activations from PET or fMRI images in a two-... more A new signal-detection approach for detecting brain activations from PET or fMRI images in a two-state (" on-off") neuroimaging study is proposed. The activation pattern is modeled as a superposition of an unknown number of circular spatial basis functions of unknown position, size, and amplitude. Also, the number of these functions and their parameters is determined by maximum a posteriori (MAP) estimation. To maximize the posterior distribution, a reversible-jump Markov-chain Monte-Carlo (RJMCMC) algorithm ...
A Bayesian approach is proposed for statistical analysis of fMRI data sets in a two state ("... more A Bayesian approach is proposed for statistical analysis of fMRI data sets in a two state ("on-off") activation study. The approach is based on the Relevance Vector Machine (RVM) regression framework. According to this approach the shape of the activations is a superposition of kernel functions, one at each pixel of the image, and a hierarchical Bayesian model is employed
Estimation of the intrinsic dimensionality of fMRI data is an important part of data analysis tha... more Estimation of the intrinsic dimensionality of fMRI data is an important part of data analysis that helps to separate the signal of interest from noise. We have studied multiple methods of dimensionality estimation proposed in the literature and used these estimates to select a subset of principal components that was subsequently processed by linear discriminant analysis (LDA). Using simulated multivariate Gaussian data, we show that the dimensionality that optimizes signal detection (in terms of the receiver operating characteristic (ROC) metric) goes through a transition from many dimensions to a single dimension as a function of the signal-to-noise ratio. This transition happens when the loci of activation are organized into a spatial network and the variance of the networked, task-related signals is high enough for the signal to be easily detected in the data. We show that reproducibility of activation maps is a metric that captures this switch in intrinsic dimensionality. Except...
2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821), 2004
We propose the use of the relevance vector machine (RVM) regression framework for statistical ana... more We propose the use of the relevance vector machine (RVM) regression framework for statistical analysis of PET or fMRI data sets in a two state ("on-off") activation study. According to this approach the shape of the activations is a superposition of kernel functions, one at each pixel of the image, of unknown amplitude and a hierarchical Bayesian model is employed
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006
Abstract We propose an approach to analyzing functional neuroimages in which:(1) regions of neuro... more Abstract We propose an approach to analyzing functional neuroimages in which:(1) regions of neuronal activation are described by a superposition of spatial kernel functions, the parameters of which are estimated from the data; and (2) the presence of activation is detected by means of a generalized likelihood ratio test (GLRT). In an on-off design we model the spatial activation pattern as a sum of an unknown number of kernel functions of unknown location, amplitude and/or size. We employ two Bayesian methods of estimating ...
Increased physical activity and higher adherence to a Mediterranean-type diet (MeDi) have been in... more Increased physical activity and higher adherence to a Mediterranean-type diet (MeDi) have been independently associated with reduced risk of Alzheimer's disease (AD). Their association has not been investigated with the use of biomarkers. This study examines whether, among cognitively normal (NL) individuals, those who are less physically active and show lower MeDi adherence have brain biomarker abnormalities consistent with AD. Forty-five NL individuals (age 54 ± 11, 71% women) with complete leisure time physical activity (LTA), dietary information, and cross-sectional 3D T1-weigthed MRI, (11)C-Pittsburgh Compound B (PiB) and (18)F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) scans were examined. Voxel-wise multivariate partial least square (PLS) regression was used to examine the effects of LTA, MeDi and their interaction on brain biomarkers. Age, gender, ethnicity, education, caloric intake, BMI, family history of AD, Apolipoprotein E (APOE) genotype, presence ...
Digital infrared iris photography using a modified digital camera system was performed on approxi... more Digital infrared iris photography using a modified digital camera system was performed on approximately 300 subjects seen during routine clinical care and research at one facility. Because this image database offered an opportunity to gain new insight into the potential utility of infrared iris imaging, it was surveyed for unique image patterns. Then, a selection of photographs was compiled that would illustrate the spectrum of this imaging experience. Potentially informative image patterns were observed in subjects with cataracts, diabetic retinopathy, Posner-Schlossman syndrome, iridociliary cysts, long anterior lens zonules, nevi, oculocutaneous albinism, pigment dispersion syndrome, pseudophakia, suspected vascular anomaly, and trauma. Image patterns were often unanticipated regardless of preexisting information and suggest that infrared iris imaging may have numerous potential clinical and research applications, some of which may still not be recognized. These observations suggest further development and study of this technology.
To investigate near infrared iris transillumination (NIRit) imaging as a new method to quantify p... more To investigate near infrared iris transillumination (NIRit) imaging as a new method to quantify pupil shape, size, and position because the imaging modality can uniquely provide simultaneous information regarding iris structural details that influence pupil characteristics and because exploration of related techniques could promote discovery helpful to clinical research and care. Digital NIRit images of normal and diseased eyes were used along with computer-assisted techniques to quantify four primary pupil parameters, including pupil roundness (PR), pupil ovalness (PO), pupil size (PS), and pupil eccentricity (PE). A combined measure of PR and PO was also developed (the pupil circularity index [PCI]). Repeatability of the measures was studied and example analyses were performed. Pupil measures could be calculated for right eyes of 307 subjects (164 normal, 143 other), with fewer than 0.5% exclusions due to image quality. Repeatability study did not show significant bias (P < .05) for any of the four primary measures. Example analyses could show age-associated differences in pupil shape (≥ 50 year olds had less regular pupils than < 50 year olds: median PCI = 0.009 vs 0.006; P < .01) and that a group of pigment dispersion syndrome subjects (n = 27) had less regular pupils than a group of matched controls (PO = 0.9966 vs 0.9990; P < .05). Digital NIRit imaging can provide novel, reliable, and informative methods to quantify pupil characteristics while providing simultaneous information about iris structure that may influence these parameters.
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