|
|
Creator | Title | Description | Subject | Date |
| 1 |
 |
Pascucci, Valerio | Exploring performance data with boxfish | The growth in size and complexity of scaling applications and the systems on which they run pose challenges in analyzing and improving their overall performance. With metrics coming from thousands or millions of processes, visualization techniques are necessary to make sense of the increasing amount... | | 2012-01-01 |
| 2 |
 |
Gerig, Guido | Spatiotemporal modeling of distribution-valued data applied to DTI tract evolution in infant neurodevelopment | This paper proposes a novel method that extends spatiotemporal growth modeling to distribution-valued data. The method relaxes assumptions on the underlying noise models by considering the data to be represented by the complete probability distributions rather than a representative, single-valued su... | | 2013-01-01 |
| 3 |
 |
Pascucci, Valerio | Multivariate volume visualization through dynamic projections | We propose a multivariate volume visualization framework that tightly couples dynamic projections with a high-dimensional transfer function design for interactive volume visualization. We assume that the complex, high-dimensional data in the attribute space can be well-represented through a collecti... | | 2014-01-01 |
| 4 |
 |
Anderson, Erik Wesley | Discovering and visualizing patterns in EEG data | Brain activity data is often collected through the use of electroen-cephalography (EEG). In this data acquisition modality, the electric fields generated by neurons are measured at the scalp. Although this technology is capable of measuring activity from a group of neurons, recent efforts provide ev... | | 2013-01-01 |
| 5 |
 |
Pascucci, Valerio | Characterization and modeling of PIDX parallel I/O for performance optimization | Parallel I/O library performance can vary greatly in re- sponse to user-tunable parameter values such as aggregator count, file count, and aggregation strategy. Unfortunately, manual selection of these values is time consuming and dependent on characteristics of the target machine, the underlying fi... | | 2013-01-01 |
| 6 |
 |
Gerig, Guido | Geodesic regression of image and shape data for improved modeling of 4D trajectories | A variety of regression schemes have been proposed on images or shapes, although available methods do not handle them jointly. In this paper, we present a framework for joint image and shape regression which incorporates images as well as anatomical shape information in a consistent manner. Evolutio... | | 2014-01-01 |
| 7 |
 |
Gerig, Guido | Spatio-temporal analysis of early brain development | Analysis of human brain development is a crucial step for improved understanding of neurodevelopmental disorders. We focus on normal brain development as is observed in the multimodal longitudinal MRI/DTI data of neonates to two years of age. We present a spatio-temporal analysis framework using Gom... | | 2010-01-01 |
| 8 |
 |
Pascucci, Valerio | Exploring power behaviors and trade-offs of in-situ data analytics | As scientific applications target exascale, challenges related to data and energy are becoming dominating concerns. For example, coupled simulation workflows are increasingly adopting in-situ data processing and analysis techniques to address costs and overheads due to data movement and I/O. However... | | 2013-01-01 |
| 9 |
 |
Gerig, Guido | Multivariate longitudinal statistics for neonatal-pediatric brain tissue development | The topic of studying the growth of human brain development has become of increasing interest in the neuroimaging community. Cross-sectional studies may allow comparisons between means of different age groups, but they do not provide a growth model that integrates the continuum of time, nor do they ... | | 2008-01-01 |
| 10 |
 |
Gerig, Guido | Building spatiotemporal anatomical models using joint 4-D segmentation, registration, and subject-specific atlas estimation | Longitudinal analysis of anatomical changes is a vital component in many personalized-medicine applications for predicting disease onset, determining growth/atrophy patterns, evaluating disease progression, and monitoring recovery. Estimating anatomical changes in longitudinal studies, especially th... | | 2012-01-01 |
| 11 |
 |
Gerig, Guido | Estimation of smooth growth trajectories with controlled acceleration from time series shape data | Longitudinal shape analysis often relies on the estimation of a realistic continuous growth scenario from data sparsely distributed in time. In this paper, we propose a new type of growth model para-meterized by acceleration, whereas standard methods typically control the velocity. This mimics the b... | | 2011-01-01 |
| 12 |
 |
Gerig, Guido | Parametric regression scheme for distributions: analysis of DTI fiber tract diffusion changes in early Brain Development | Temporal modeling frameworks often operate on scalar variables by summarizing data at initial stages as statistical summaries of the underlying distributions. For instance, DTI analysis often employs summary statistics, like mean, for regions of interest and properties along fiber tracts for populat... | | 2014-01-01 |
| 13 |
 |
Gerig, Guido | Mixed-effects shape models for estimating longitudinal changes in anatomy | | | 2012-01-01 |
| 14 |
 |
Gerig, Guido | A joint framework for 4D segmentation and estimation of smooth temporal appearance changes | Medical imaging studies increasingly use longitudinal images of individual subjects in order to follow-up changes due to development, degeneration, disease progression or efficacy of therapeutic intervention. Repeated image data of individuals are highly correlated, and the strong causality of infor... | | 2014-01-01 |
| 15 |
 |
Gerig, Guido | Quality control of diffusion weighted images | Diffusion Tensor Imaging (DTI) has become an important MRI procedure to investigate the integrity of white matter in brain in vivo. DTI is estimated from a series of acquired Diffusion Weighted Imaging (DWI) volumes. DWI data suffers from inherent low SNR, overall long scanning time of multiple dire... | | 2010-01-01 |
| 16 |
 |
Gerig, Guido | A framework for longitudinal data analysis via shape regression | Traditional longitudinal analysis begins by extracting desired clinical measurements, such as volume or head circumference, from discrete imaging data. Typically, the continuous evolution of a scalar measurement is estimated by choosing a 1D regression model, such as kernel regression or fitting a p... | | 2012-01-01 |
| 17 |
 |
Gerig, Guido | Constrained data decomposition and regression for analyzing healthy aging from fiber tract diffusion properties | It has been shown that brain structures in normal aging undergo significant changes attributed to neurodevelopmental and neurodegeneration processes as a lifelong, dynamic process. Modeling changes in healthy aging will be necessary to explain differences to neurodegenerative patterns observed in m... | | 2009-01-01 |
| 18 |
 |
Gerig, Guido | Statistical growth modeling of longitudinal DT-MRI for regional characterization of early brain development | A population growth model that represents the growth trajectories of individual subjects is critical to study and understand neurodevelopment. This paper presents a framework for jointly estimating and modeling individual and population growth trajectories, and determining significant regional diffe... | | 2012-01-01 |
| 19 |
 |
Meyer, Miriah Dawn | Design activity framework for visualization design | An important aspect in visualization design is the connection between what a designer does and the decisions the designer makes. Existing design process models, however, do not explicitly link back to models for visualization design decisions. We bridge this gap by introducing the design activity fr... | | 2014-01-01 |
| 20 |
 |
Gerig, Guido | Longitudinal growth modeling of discrete-time functions with application to DTI tract evolution in early neurodevelopment | We present a new framework for spatiotemporal analysis of parameterized functions attributed by properties of 4D longitudinal image data. Our driving application is the measurement of temporal change in white matter diffusivity of fiber tracts. A smooth temporal modeling of change from a discrete-ti... | | 2012-01-01 |
| 21 |
 |
Gerig, Guido | Geodesic image regression with a sparse parameterization of diffeomorphisms | Image regression allows for time-discrete imaging data to be modeled continuously, and is a crucial tool for conducting statistical analysis on longitudinal images. Geodesic models are particularly well suited for statistical analysis, as image evolution is fully characterized by a baseline image an... | | 2013-01-01 |
| 22 |
 |
Gerig, Guido | A new framework for analyzing white matter maturation in early brain development | The trajectory of early brain development is marked by rapid growth presented by volume but also by tissue property changes. Capturing regional characteristics of axonal structuring and myelination via neuroimaging requires analysis of longitudinal image data with multiple modalities. Complementary ... | | 2010-01-01 |
| 23 |
 |
Gerig, Guido | Assessment of reliability of multi-site neuroimaging via traveling phantom study | This paper describes a framework for quantitative analysis of neuroimaging data of traveling human phantoms used for cross-site validation. We focus on the analysis of magnetic resonance image data including intra- and intersite comparison. Locations and magnitude of geometric deformation is studied... | | 2008-01-01 |
| 24 |
 |
Gerig, Guido | Analysis of longitudinal shape variability via subject specific growth modeling | Statistical analysis of longitudinal imaging data is crucial for understanding normal anatomical development as well as disease progression. This fundamental task is challenging due to the difficulty in modeling longitudinal changes, such as growth, and comparing changes across different populations... | | 2012-01-01 |
| 25 |
 |
Gerig, Guido | Geodesic shape regression in the framework of currents | Shape regression is emerging as an important tool for the statistical analysis of time dependent shapes. In this paper, we develop a new generative model which describes shape change over time, by extending simple linear regression to the space of shapes represented as currents in the large deformat... | | 2013-01-01 |
