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A common pre-processing challenge associated with group level fMRI analysis is spatial registration of multiple subjects to a standard space. Spatial normalization, using a reference image such as the Montreal Neurological Institute brain template, is the most common technique currently in use to achieve spatial congruence across multiple subjects. This(More)
Diagnosis of Autism Spectrum Disorder (ASD) using structural magnetic resonance imaging (sMRI) of the brain has been a topic of significant research interest. Previous studies using small datasets with well-matched Typically Developing Controls (TDC) report high classification accuracies (80-96%) but studies using the large heterogeneous ABIDE dataset(More)
Low success (<60%) in autism spectrum disorder (ASD) classification using brain morphometry from the large multi-site ABIDE dataset and inconsistent findings on brain morphometric abnormalities in ASD can be attributed to the ASD heterogeneity. In this study, we show that ASD brain morphometry is highly heterogeneous, and demonstrate that the heterogeneity(More)
We present the results of the analysis of a set of medium resolution spectra, obtained by the Space Telescope Imaging Spectrograph on board the Hubble Space Telescope, of the emission line gas present in the nuclei of a complete sample of 21 nearby, early-type galaxies with radio jets (the UGC FR-I Sample). For each galaxy nucleus we present spectroscopic(More)
Previous studies applying automatic preprocessing methods on Structural Magnetic Resonance Imaging (sMRI) report inconsistent neuroanatomical abnormalities in Autism Spectrum Disorder (ASD). In this study we investigate inter-method differences as a possible cause behind these inconsistent findings. In particular, we focus on the estimation of the following(More)
Little is known about how the care received in emergency departments (ED) by the elderly population differs from that received by younger people. We prospectively abstracted ED records of 1620 consecutive patients visiting a large community hospital ED over a 22-day period in 1984 for demographic and medical variables. Charts of patients presenting with(More)
We present a novel integrated wavelet-domain based framework (w-ICA) for 3-D denoising functional magnetic resonance imaging (fMRI) data followed by source separation analysis using independent component analysis (ICA) in the wavelet domain. We propose the idea of a 3-D wavelet-based multi-directional denoising scheme where each volume in a 4-D fMRI data(More)
Denoising is amongst the most challenging steps involved in analyzing fMRI data. The conventionally used Gaussian smoothing improves the SNR at the cost of spatial sensitivity and specificity. We briefly describe a 3-D framework for wavelet based fMRI analysis that includes denoising and signal separation followed by a detailed illustration of the benefits(More)
We present the final results from our deep HST imaging study of the host galaxies of radio-quiet quasars (RQQs), radio-loud quasars (RLQs) and radio galaxies (RGs). We describe and analyze new WFPC2 R-band observations for 14 objects which, when combined with the first tranche of HST imaging reported in McLure et al (1999), provide a complete and consistent(More)
Abnormalities in white matter (WM) brain regions are attributed as a possible biomarker for schizophrenia (SZ). Diffusion tensor imaging (DTI) is used to capture WM tracts. Psychometric tests that evaluate the severity of symptoms of SZ are clinically used in the diagnosis process. In this study we investigate the correlates of scalar DTI measures, such as(More)