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检索条件"丛书名=Mathematics and Visualization"

共 253 条记录，以下是71-80 订阅

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Working Memory Function in Recent-Onset Schizophrenia Patients Associated with White Matter Microstructure: Connectometry Approach 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Dolatshahi, Mahsa Rahmani, Farzaneh Shadmehr, Mohammad Hadi Peoppl, Timm Shojaie, Ahmad Noorizadeh, Farsad Aarabi, Mohammad Hadi Jooyandeh, Somayeh Mohammadi Basir Eye Hlth Res Ctr Tehran Iran USERN Neuroimaging Network NIN Tehran Iran Univ Tehran Med Sci Students Sci Res Ctr Tehran Iran Univ Regensburg Dept Psychiat & Psychotherapy Regensburg Germany

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

Schizophrenia is a kind of psychosis accompanied by cognitive deficits. In addition, white matter abnormalities are observed in various brain regions and tracts in the disease. Association of some tracts like superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), inferior fronto-occipital fasciculus (IFOF) with working memory function have been observed using diffusion MRI analysis methods such as tract-based spatial statistics (TBSS). Thus, we applied connectometry, not suffering from some limitations of tract specific analysis, in a group of 29 patients and 32 healthy controls to investigate association of working memory performance (as measured by letter-number sequencing test) with white matter integrity in recent-onset schizophrenic patients, who are less affected by antipsychotic medications. Connectometry is a recently introduced approach utilized to associate local connectomes with a study variable along the fiber pathways themselves instead of finding the difference in the whole fiber pathways. This study showed that lesser integrity of some fiber tracts like the arcuate fasciculus, the inferior longitudinal fasciculus, the body of corpus callosum and also some fibers of corticospinal tract, IFOF, and cingulum bundle associated with working memory deficits in schizophrenic patients while healthy controls did not show any correlation unless the percentage threshold was increased up to 45%. These results are consistent with previous ones to a large extent but we also found some fiber tracts other than previous studies like the body of corpus callosum and some fibers of corticospinal tract. On the whole, Our study further supports disconnectivity hypothesis in schizophrenia, playing a major role in cognitive dysfunction.

关键词： Fibers

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Noise Floor Removal via Phase Correction of Complex Diffusion-Weighted Images: Influence on DTI and q-Space Metrics 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Pizzolato, Marco Fick, Rutger Boutelier, Timothe Deriche, Rachid Univ Cote dAzur INRIA Nice France Olea Med La Ciotat France

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

The non-Gaussian noise distribution in magnitude Diffusion-Weighted Images (DWIs) can severely affect the estimation and reconstruction of the true diffusion signal. As a consequence, also the estimated diffusion metrics can be biased. We study the effect of phase correction, a procedure that re-establishes the Gaussianity of the noise distribution in DWIs by taking into account the corresponding phase images. We quantify the debiasing effects of phase correction in terms of diffusion signal estimation and calculated metrics. We perform in silico experiments based on a MGH Human Connectome Project dataset and on a digital phantom, accounting for different acquisition schemes, diffusion-weightings, signal to noise ratios, and for metrics based on Diffusion Tensor Imaging and on Mean Apparent Propagator Magnetic Resonance Imaging, i.e. q-space metrics. We show that phase correction is still a challenge, but also an effective tool to debias the estimation of diffusion signal and metrics from DWIs, especially at high b-values.

关键词： Diffusion tensor imaging Diffusion Gaussian noise (electronic) Image denoising Magnetic resonance imaging Signal analysis Signal to noise ratio Tensors Complex diffusions Diffusion signals Diffusion weighted images Digital phantoms Human Connectome Noise distribution Non Gaussian noise Phase corrections

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Parcellation of Human Amygdala Subfields Using Orientation Distribution Function and Spectral K-means Clustering 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Wen, Qiuting Stirling, Brian D. Sha, Long Shen, Li Whalen, Paul J. Wu, Yu-Chien Indiana Univ Sch Med Dept Radiol & Imaging Sci Ctr Neuroimaging Goodman Hall355 West 16th StSuite 4100 Indianapolis IN 46202 USA Univ Southern Calif Div Biokinesiol & Phys Therapy Los Angeles CA 90089 USA Dartmouth Coll Dept Psychol & Brain Sci 6207 Moore Hall Hanover NH 03755 USA Dartmouth Coll Dartmouth Brain Imaging Ctr 6207 Moore Hall Hanover NH 03755 USA NYU Neurosci Inst 550 1St Ave New York NY 10016 USA

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

Amygdala plays an important role in fear and emotional learning, which are critical for human survival. Despite the functional relevance and unique circuitry of each human amygdaloid subnuclei, there has yet to be an efficient imaging method for identifying these regions in vivo. A data-driven approach without prior knowledge provides advantages of efficient and objective assessments. The present study uses high angular and high spatial resolution diffusion magnetic resonance imaging to generate orientation distribution function, which bears distinctive microstructural features. The features were extracted using spherical harmonic decomposition to assess microstructural similarity within amygdala subfields that are identified via similarity matrices using spectral k-mean clustering. The approach was tested on 32 healthy volunteers and three distinct amygdala subfields were identified including medial, posterior-superior lateral, and anterior-inferior lateral.

关键词： Distribution functions Angular distribution Clustering algorithms Diffusion Magnetic resonance imaging Microstructural evolution Data driven approach Diffusion magnetic resonance imaging Functional relevance High spatial resolution K means clustering Microstructural features Objective assessment Orientation distribution function

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Visual Data Cleansing of Low-Level Eye-Tracking Data 1st

引用

1st Workshop on Eye Tracking and visualization (ETVIS)

作者： Schulz, Christoph Burch, Michael Beck, Fabian Weiskopf, Daniel Univ Stuttgart Visualizat Res Ctr Allmandring 19 D-70569 Stuttgart Germany

ISBN: (纸本)9783319470245;9783319470238

Analysis and visualization of eye movement data from eye-tracking studies typically take into account gazes, fixations, and saccades of both eyes filtered and fused into a combined eye. Although this is a valid strategy, we argue that it is also worth investigating low-level eye-tracking data prior to high-level analysis, because today's eye-tracking systems measure and infer data from both eyes separately. In this work, we present an approach that supports visual analysis and cleansing of low-level time-varying data for eye-tracking experiments. The visualization helps researchers get insights into the quality of the data in terms of its uncertainty, or reliability. We discuss uncertainty originating from eye tracking, and how to reveal it for visualization, using a comparative approach for disagreement between plots, and a density-based approach for accuracy in volume rendering. Finally, we illustrate the usefulness of our approach by applying it to eye movement data recorded with two state-of-the-art eye trackers.

关键词： Eye tracking

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Eye Fixation Metrics for Large Scale Evaluation and Comparison of Information visualizations 1st

引用

1st Workshop on Eye Tracking and visualization (ETVIS)

作者： Bylinskii, Zoya Borkin, Michelle A. Kim, Nam Wook Pfister, Hanspeter Oliva, Aude MIT Comp Sci & Artificial Intelligence Lab 32 Vassar St Boston MA 02139 USA Northeastern Univ Coll Comp & Informat Sci 360 Huntington Ave Boston MA 02115 USA Harvard Univ Sch Engn & Appl Sci 33 Oxford St Boston MA 02115 USA

ISBN: (纸本)9783319470245;9783319470238

An observer's eye movements are often informative about how the observer interacts with and processes a visual stimulus. Here, we are specifically interested in what eye movements reveal about how the content of information visualizations is processed. Conversely, by pooling over many observers' worth of eye movements, what can we learn about the general effectiveness of different visualizations and the underlying design principles employed? The contribution of this manuscript is to consider these questions at a large data scale, with thousands of eye fixations on hundreds of diverse information visualizations. We survey existing methods and metrics for collective eye movement analysis, and consider what each can tell us about the overall effectiveness of different information visualizations and designs at this large data scale.

关键词： Eye movements

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GazeGIS: A Gaze-Based Reading and Dynamic Geographic Information System 1st

引用

1st Workshop on Eye Tracking and visualization (ETVIS)

作者： Tateosian, Laura G. Glatz, Michelle Shukunobe, Makiko Chopra, Pankaj North Carolina State Univ Ctr Geospatial Analyt Raleigh NC 27695 USA Emory Univ Dept Human Genet Atlanta GA 30322 USA

ISBN: (纸本)9783319470245;9783319470238

Location is an important component of a narrative. Mapped place names provide vital geographical, economic, historical, political, and cultural context for the text. Online sources such as news articles, travel logs, and blogs frequently refer to geographic locations, but often these are not mapped. When a map is provided, the reader is still responsible for matching references in the text with map positions. As they read a place name within the text, readers must locate its map position, then find their place again in the text to resume reading, and repeat this for each toponym. We propose a gaze-based reading and dynamic geographic information system (GazeGIS) which uses eye tracking and geoparsing to enable a more cohesive reading experience by dynamically mapping locations just as they are encountered within the text. We developed a prototype GazeGIS application and demonstrated its application to several narrative passages. We conducted a study in which participants read text passages using the system and evaluated their experience. We also explored an application for intelligence analysis and discuss how experts in this domain envision its use. Layman and intelligence expert evaluations indicate a positive reception for this new reading paradigm. This could change the way we read online news and e-books, the way school children study political science and geography, the way officers study military history, the way intelligence analysts consume reports, and the way we plan our next vacation.

关键词： Geographic information systems

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Colocalization of Functional Activity and Neurite Density Within Cortical Areas 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Teillac, Achille Lefrance, Sandrine Duchesnay, Edouard Poupon, Fabrice Fuster, Maite Alaitz Ripoll Le Bihan, Denis Mangin, Jean-Francois Poupon, Cyril CEA I2BM NeuroSpin UNIRS Gif Sur Yvette France CEA I2BM NeuroSpin UNATI Gif Sur Yvette France

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

In this work, we investigated the link between the blood-oxygen-level dependant (BOLD) effect observed using functional magnetic resonance imaging (fMRI) and the neurite density inferred from the Neurite Orientation Dispersion and Density Imaging (NODDI) model in some well-known lateralized cortical areas. We found a strong colocalization between those two parameters in lateralized areas such as the primary motor cortex, the language network, but also the primary visual cortex, which might indicate a strong link between microstructure and functional activity.

关键词： Visual languages

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Groupwise Structural Parcellation of the Cortex: A Sound Approach Based on Logistic Models 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Gallardo, Guillermo Fick, Rutger Wells, William, III Deriche, Rachid Wassermann, Demian Univ Cote dAzur INRIA Nice France Harvard Med Sch Boston MA USA

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

Current theories hold that brain function is highly related with long-range physical connections through axonal bundles, namely extrinsic connectivity. However, obtaining a groupwise cortical parcellation based on extrinsic connectivity remains challenging. Current parcellation methods are computationally expensive;need tuning of several parameters or rely on ad-hoc constraints. Furthermore, none of these methods present a model for the cortical extrinsic connectivity. To tackle these problems, we propose a parsimonious model for the extrinsic connectivity and an efficient parcellation technique based on clustering of tractograms. Our technique allows the creation of single subject and groupwise parcellations of the whole cortex. The parcellations obtained with our technique are in agreement with anatomical and functional parcellations in the literature. In particular, the motor and sensory cortex are subdivided in agreement with the human homunculus of Penfield. We illustrate this by comparing our resulting parcels with an anatomical atlas and the motor strip mapping included in the Human Connectome Project data.

关键词： Medical imaging

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Capturing You Watching You: Characterizing Visual-Motor Dynamics in Touchscreen Interactions 1st

引用

1st Workshop on Eye Tracking and visualization (ETVIS)

作者： Blaha, Leslie M. Houpt, Joseph W. Frame, Mary E. Kern, Jacob A. US Air Force Res Lab Dayton OH USA Wright State Univ Dayton OH 45435 USA Miami Univ Oxford OH 45056 USA

ISBN: (纸本)9783319470245;9783319470238

The relationship between where people look and where people reach has been studied since the dawn of experimental psychology. This relationship has implications for the designs of interactive visualizations, particularly for applications involving touchscreens. We present a new visual-motor analytics dashboard for the joint study of eye movement and hand/finger movement dynamics. Our modular approach combines real-time playback of gaze and finger-dragging behavior together with statistical models quantifying the dynamics of both modalities. To aid in visualization and inference with these data, we apply Gaussian process regression models which capture the similarities and differences between eye and finger movements, while providing a statistical model of the observed functional data. Smooth estimates of the dynamics are included in the dashboard to enable visual-analytic exploration of visual-motor behaviors on touchscreen interfaces.

关键词： Dynamics

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Multi-Spherical Diffusion MRI: Exploring Diffusion Time Using Signal Sparsity 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Fick, Rutger H. J. Petiet, Alexandra Santin, Mathieu Philippe, Anne-Charlotte Lehericy, Stephane Deriche, Rachid Wassermann, Demian Univ Cote dAzur INRIA Nice France CENIR Inst Cerveau & Moelle Epineere Paris France

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

Effective representation of the diffusion signal's dependence on diffusion time is a sought-after, yet still unsolved, challenge in diffusion MRI (dMRI). We propose a functional basis approach that is specifically designed to represent the dMRI signal in this four-dimensional space-varying over gradient strength, direction and diffusion time. In particular, we provide regularization tools imposing signal sparsity and signal smoothness to drastically reduce the number of measurements we need to probe the properties of this multi-spherical space. We illustrate a novel application of our approach, which is the estimation of time-dependent q-space indices, on both synthetic data generated using Monte-Carlo simulations and in vivo data acquired from a C57B16 wild-type mouse. In both cases, we find that our regularization approach stabilizes the signal fit and index estimation as we remove samples, which may bring multi-spherical diffusion MRI within the reach of clinical application.

关键词： Magnetic resonance imaging

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