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检索条件"丛书名=Mathematics and Visualization"

共 253 条记录，以下是81-90 订阅

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Visualizing Eye Movements in Formal Cognitive Models 1st

引用

1st Workshop on Eye Tracking and visualization (ETVIS)

作者： Balint, J. Timothy Reynolds, Brad Blaha, Leslie M. Halverson, Tim George Mason Univ Fairfax VA 22030 USA Wright State Univ Dayton OH 45435 USA Air Force Res Lab Wright Patterson AFB OH USA Oregon Res Cognit Applicat LLC Springfield OR USA

ISBN: (纸本)9783319470245;9783319470238

We present two visualization approaches illustrating the value of formal cognitive models for predicting, capturing, and understanding eye tracking as a manifestation of underlying cognitive processes and strategies. Computational cognitive models are formal theories of cognition which can provide predictions for human eye movements in visual decision-making tasks. Visualizing the internal dynamics of a model provides insights into how the interplay of cognitive mechanisms influences the observable eye movements. Animation of those model behaviors in virtual human agents gives explicit, high fidelity visualizations of model behavior, providing the analyst with an understanding of the simulated human's behavior. Both can be compared to human data for insight about cognitive mechanisms engaged in visual tasks and how eye movements are affected by changes in internal cognitive strategies, external interface properties, and task demands. We illustrate the visualizations on two models of visual multitasking and juxtapose model performance against a human operator performing the same task.

关键词： Eye movements

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The MR Physics of Advanced Diffusion Imaging 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Hall, Matt G. UCL UCL GOS Inst Child Hlth Dev Imaging & Biophys London England

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

Over the last decade, the number of models used to analyse and interpret diffusion MRI data has increased dramatically. Exponentials and biexponentials have been joined by stretched exponentials, HARDI methods, compartment-based microstructure models and effective medium theories. At the same time, the field has experienced a cultural shift away from MR physics and towards computer science, emphasising Bayesian statistics and Machine Learning. This has meant that understanding imaging methodology whilst still keeping in mind the underlying physical assumptions can be challenging. This chapter reviews the Diffusion MR modelling literature from the point of view of the underlying physics. We show how the Bloch-Torrey equation can be derived, and then how different physical assumptions and formulations lead to different models. The intention is to show the different assumptions made in different models, to aid understanding and model selection.

关键词： Magnetic resonance imaging

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Denoising Diffusion-Weighted Images Using Grouped Iterative Hard Thresholding of Multi-Channel Framelets 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Zhang, Jian Chen, Geng Zhang, Yong Dong, Bin Shen, Dinggang Yap, Pew-Thian Hunan Univ Sci & Technol Sch Informat & Elect Engn Xiangtan Peoples R China Univ N Carolina Dept Radiol Chapel Hill NC 27599 USA Univ N Carolina Biomed Res Imaging Ctr Chapel Hill NC 27599 USA Northwestern Polytech Univ Data Proc Ctr Xian Shaanxi Peoples R China Stanford Univ Dept Psychiat & Behav Sci Stanford CA 94305 USA Peking Univ Beijing Int Ctr Math Res Beijing Peoples R China

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

Noise in diffusion-weighted (DW) images increases the complexity of quantitative analysis and decreases the reliability of inferences. Hence, to improve analysis, it is often desirable to remove noise and at the same time preserve relevant image features. In this paper, we propose a tight wavelet frame based approach for edge-preserving denoising of DW images. Our approach (1) employs the unitary extension principle (UEP) to generate frames that are discrete analogues to differential operators of various orders;(2) introduces a very efficient method for solving an l(0) denoising problem that involves only thresholding and solving a trivial inverse problem;and (3) groups DW images acquired with neighboring gradient directions for collaborative denoising. Experiments using synthetic data with noncentral chi noise and real data with repeated scans confirm that our method yields superior performance compared with denoising using state-of-the-art methods such as non-local means.

关键词： Inverse problems

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Sensitivity of OGSE ActiveAx to Microstructural Dimensions on a Clinical Scanner 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Kakkar, Lebina S. Atkinson, David Chan, Rachel W. Siow, Bernard Ianus, Andrada Drobnjak, Ivana UCL Ctr Med Image Comp London England Ctr Med Imaging Wolfson House4 Stephenson Way London England UCL Ctr Adv Biomed Imaging London England

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

Axon diameter can play a key role in the function and performance of nerve pathways of the central and peripheral nervous system. Previously, a number of techniques to measure axon diameter using diffusion MR I have been proposed, majority of which uses single diffusion encoding (SDE) spin-echo sequence. However, recent theoretical research suggests that low-frequency oscillating gradient spin echo (OGSE ) offers benefits over SDE for imaging diameters when fibres are of unknown orientation. Furthermore, it suggests that resolution limit for clinical scanners (gradient strength of 60-80 mT/m) is approximate to 6 mu m. Here we investigate the sensitivity of OGSE to fibre diameters experimentally on a clinical scanner, using microcapillaries of unknown orientation. We use the orientationally invariant OGSE ActiveAx method to image microcapillaries with diameters of 5, 10 or 20 mu m. As predicted by theory, we find that 5 mu m diameters are undistinguishable from zero. Furthermore, we find accurate and precise estimates for 10 and 20 mu m. Finally, we find that low frequency oscillating gradient waveforms are optimal for accurate diameter estimation.

关键词： Scanning

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Comparison of Biomarkers in Transgenic Alzheimer Rats Using Multi-Shell Diffusion MRI 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Fick, Rutger H. J. Daianu, Madelaine Pizzolato, Marco Wassermann, Demian Jacobs, Russell E. Thompson, Paul M. Town, Terrence Deriche, Rachid Univ Cote Azur INRIA Valbonne France Univ Southern Calif Imaging Genet Ctr Mark & Mary Stevens Neuroimaging & Informat Inst Marina Del Rey CA USA CALTECH Beckman Inst Div Biol & Biol Engn Pasadena CA 91125 USA Univ Southern Calif Zilkha Neurogenet Inst Dept Physiol & Biophys Los Angeles CA USA

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

In this study, we assessed the evolution of diffusion MRI (dMRI) derived markers from different white matter models as progressive neurodegeneration occurs in transgenic Alzheimer rats (TgF344-AD) at 10, 15 and 24 months. We compared biomarkers reconstructed from Diffusion Tensor Imaging (DTI), Neurite Orientation Dispersion and Density Imaging (NODDI) and Mean Apparent Propagator (MAP)-MRI in the hippocampus, cingulate cortex and corpus callosum using multi-shell dMRI. We found that NODDI's dispersion and MAP-MRI's anisotropy markers consistently changed over time, possibly indicating that these measures are sensitive to age-dependent neuronal demise due to amyloid accumulation. Conversely, we found that DTI's mean diffusivity, NODDI's isotropic volume fraction and MAP-MRI's restriction-related metrics all followed a two-step progression from 10 to 15 months, and from 15 to 24 months. This two-step pattern might be linked with a neuroinflammatory response that may be occurring prior to, or during microstructural breakdown. Using our approach, we are able to provide- for the first time-preliminary and valuable insight on relevant biomarkers that may directly describe the underlying pathophysiology in Alzheimer's disease.

关键词： Magnetic resonance imaging

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Regularized Dictionary Learning with Robust Sparsity Fitting for Compressed Sensing Multishell HARDI 1

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Gupta, Kratika Adlakha, Deepali Agarwal, Vishal Awate, Suyash P. Indian Inst Technol Comp Sci & Engn Dept Bombay Maharashtra India Facebook Ads Team London England

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541303;9783319541297

This paper presents a new compressed sensing framework for multishell HARDI. Unlike methods that model diffusion signals using analytical bases, we learn a dictionary of multishell diffusion signals, with a proposed regularization term to handle low signal-to-noise ratios at high b values. We combine the dictionary model for diffusion signals together with a multiscale (wavelet-based) spatial model on images for compressed sensing. To control overfitting of the dictionary to tracts with unknown orientations, we use a strong non-sparsity penalty that behaves close to the desirable L-0 pseudo-norm. Our framework allows undersampling gradient directions, shells, and k-space. The results show improved reconstructions from our framework, over the state of the art.

关键词： Compressed sensing

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Accuracy of Monocular Gaze Tracking on 3D Geometry 1st

引用

1st Workshop on Eye Tracking and visualization (ETVIS)

作者： Wang, Xi Lindlbauer, David Lessig, Christian Alexa, Marc TU Berlin Berlin Germany

ISBN: (纸本)9783319470245;9783319470238

Many applications such as data visualization or object recognition benefit from accurate knowledge of where a person is looking at. We present a system for accurately tracking gaze positions on a three dimensional object using a monocular head mounted eye tracker. We accomplish this by (1) using digital manufacturing to create stimuli whose geometry is know to high accuracy, (2) embedding fiducial markers into the manufactured objects to reliably estimate the rigid transformation of the object, and, (3) using a perspective model to relate pupil positions to 3D locations. This combination enables the efficient and accurate computation of gaze position on an object from measured pupil positions. We validate the of our system experimentally, achieving an angular resolution of 0.8 degrees and a 1.5% depth error using a simple calibration procedure with 11 points.

关键词： Eye tracking

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Computational Diffusion MRI 1st ed. 2017

引用

丛书名： mathematics and visualization

2017年

作者： Andrea Fuster Aurobrata Ghosh Enrico Kaden Yogesh Rathi Marco Reisert

ISBN: (数字)9783319541303

ISBN: (纸本)9783319541297

This volume offers a valuable starting point for anyone interested in learning computational diffusion MRI and mathematical methods for brain connectivity, while also sharing new perspectives and insights on the latest research challenges for those currently working in the field. Over the last decade, interest in diffusion MRI has virtually exploded. The technique provides unique insights into the microstructure of living tissue and enables in-vivo connectivity mapping of the brain. Computational techniques are key to the continued success and development of diffusion MRI and to its widespread transfer into the clinic, while new processing methods are essential to addressing issues at each stage of the diffusion MRI pipeline: acquisition, reconstruction, modeling and model fitting, image processing, fiber tracking, connectivity mapping, visualization, group studies and inference. These papers from the 2016 MICCAI Workshop Computational Diffusion MRI which was intended to provide a snapshot of the latest developments within the highly active and growing field of diffusion MR cover a wide range of topics, from fundamental theoretical work on mathematical modeling, to the development and evaluation of robust algorithms and applications in neuroscientific studies and clinical practice. The contributions include rigorous mathematical derivations, a wealth of rich, full-color visualizations, and biologically or clinically relevant results. As such, they will be of interest to researchers and practitioners in the fields of computer science, MR physics, and applied mathematics.

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visualization in Medicine and Life Sciences III 1st ed. 2016

引用

丛书名： mathematics and visualization

2016年

作者： Lars Linsen Bernd Hamann Hans-Christian Hege

ISBN: (数字)9783319245232

ISBN: (纸本)9783319245218

The book discusses novel visualization techniques driven by the needs in medicine and life sciences as well as new application areas and challenges for visualization within these fields. It presents ideas and concepts for visual analysis of data from scientific studies of living organs or to the delivery of healthcare. Target scientific domains include the entire field of biology at all scales - from genes and proteins to organs and populations - as well as interdisciplinary research based on technological advances such as bioinformatics, biomedicine, biochemistry, or biophysics. Moreover, they comprise the field of medicine and the application of science and technology to healthcare problems. This book does not only present basic research pushing the state of the art in the field of visualization, but it also documents the impact in the fields of medicine and life sciences.

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A Temperature Phantom to Probe the Ensemble Average Propagator Asymmetry: An In-Silico Study

引用

MICCAI Workshop on Computational Diffusion MRI

作者： Pizzolato, Marco Wassermann, Demian Duval, Tanguy Campbell, Jennifer S. W. Boutelier, Timothe Cohen-Adad, Julien Deriche, Rachid Inria Sophia Antipolis Mediterranee Athena Sophia Antipolis France Polytech Montreal Montreal PQ Canada McGill Univ Montreal PQ Canada Olea Med La Ciotat France

ISBN: (纸本)9783319285887;9783319285863

The detection and quantification of asymmetry in the Ensemble Average Propagator (EAP) obtained from the Diffusion-Weighted (DW) signal has been shown only for theoretical models. EAP asymmetry appears for instance when diffusion occurs within fiberswith particular geometries. However the quantification of EAP asymmetry corresponding to such geometries in controlled experimental conditions is limited by the difficulty of designing fiber geometries on a micrometer scale. To overcome this limitation we propose to adopt an alternative paradigm to induce asymmetry in the EAP. We apply a temperature gradient to a spinal cord tract to induce a corresponding diffusivity profile that alters locally the diffusion process to be asymmetric. We simulate the EAP and the corresponding complex DW signal in such a scenario. We quantify EAP asymmetry and investigate its relationship with the applied experimental conditions and with the acquisition parameters of a Pulsed Gradient Spin-Echo sequence. Results show that EAP asymmetry is sensible to the applied temperature-induced diffusivity gradient and that its quantification is influenced by the selected acquisition parameters.

关键词： Diffusion

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