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Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction 1

1st International Workshop on Graph Learning in Medical Imaging, GLMI 2019 held in conjunction with the 22nd International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2019

作者： Dzyubachyk, Oleh Koolstra, Kirsten Pezzotti, Nicola Lelieveldt, Boudewijn P. F. Webb, Andrew Börnert, Peter Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands C.J. Gorter Center for High Field MRI Department of Radiology Leiden University Medical Center Leiden Netherlands Computer Graphics and Visualization Group Delft University of Technology Delft Netherlands Philips Research Eindhoven Eindhoven Netherlands Intelligent Systems Department Delft University of Technology Delft Netherlands Philips Research Hamburg Hamburg Germany

ISBN: (数字)9783030358174

ISBN: (纸本)9783030358167

Quality assessment of different Magnetic Resonance Fingerprinting (MRF) sequences and their corresponding dictionaries remains an unsolved problem. In this work we present a method in which we approach analysis of MRF dictionaries by performing dimensionality reduction and representing them as low-dimensional point sets (embeddings). Dimensionality reduction was performed using a modification of the t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm. First, we demonstrated stability of calculated embeddings that allows neglecting the stochastic nature of t-SNE. Next, we proposed and analyzed two algorithms for comparing the embeddings. Finally, we performed two simulations in which we reduced the MRF sequence/dictionary in length or size and analyzed the influence of this reduction on the resulting embedding. We believe that this research can pave the way to development of a software tool for analysis, including better understanding, optimization and comparison, of different MRF sequences. © 2019, Springer Nature Switzerland AG.

关键词： Magnetic resonance

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Comparative visualization for diffusion tensor imaging group study at multiple levels of detail

Comparative visualization for diffusion tensor imaging group...

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2017 Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2017

作者： Zhang, C. Höllt, T. Caan, M.W.A. Eisemann, E. Vilanova, A. Computer Graphics and Visualization Delft University of Technology Delft Netherlands Computational Biology Center Leiden University Medical Center Leiden Netherlands Brain Imaging Center Academic Medical Center University of Amsterdam Amsterdam Netherlands

ISBN: (纸本)9783038680369

Diffusion Tensor Imaging (DTI) group studies often require the comparison of two groups of 3D diffusion tensor fields. The total number of datasets involved in the study and the multivariate nature of diffusion tensors together make this a challenging process. The traditional approach is to reduce the six-dimensional diffusion tensor to some scalar quantities, which can be analyzed with univariate statistical methods, and visualized with standard techniques such as slice views. However, this provides merely part of the whole story due to information reduction. If to take the full tensor information into account, only few methods are available, and they focus on the analysis of a single group, rather than the comparison of two groups. Simultaneously comparing two groups of diffusion tensor fields by simple juxtaposition or superposition is rather impractical. In this work, we extend previous work by Zhang et al. [ZCH∗17] to visually compare two groups of diffusion tensor fields. To deal with the wealth of information, the comparison is carried out at multiple levels of detail. In the 3D spatial domain, we propose a details-on-demand glyph representation to support the visual comparison of the tensor ensemble summary information in a progressive manner. The spatial view guides analysts to select voxels of interest. Then at the detail level, the respective original tensor ensembles are compared in terms of tensor intrinsic properties, with special care taken to reduce visual clutter. We demonstrate the usefulness of our visual analysis system by comparing a control group and an HIV positive patient group. © 2017 The Eurographics Association.

关键词： Tensors

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Comparative cellular analysis of motor cortex in human, marmoset and mouse (vol 598, pg 111, 2021)

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NATURE 2022年第7904期604卷 E8-E8页

作者： Bakken, Trygve E. Jorstad, Nikolas L. Hu, Qiwen Lake, Blue B. Tian, Wei Kalmbach, Brian E. Crow, Megan Hodge, Rebecca D. Krienen, Fenna M. Sorensen, Staci A. Eggermont, Jeroen Yao, Zizhen Aevermann, Brian D. Aldridge, Andrew I. Bartlett, Anna Bertagnolli, Darren Casper, Tamara Castanon, Rosa G. Crichton, Kirsten Daigle, Tanya L. Dalley, Rachel Dee, Nick Dembrow, Nikolai Diep, Dinh Ding, Song-Lin Dong, Weixiu Fang, Rongxin Fischer, Stephan Goldman, Melissa Goldy, Jeff Graybuck, Lucas T. Herb, Brian R. Hou, Xiaomeng Kancherla, Jayaram Kroll, Matthew Lathia, Kanan van Lew, Baldur Li, Yang Eric Liu, Christine S. Liu, Hanqing Lucero, Jacinta D. Mahurkar, Anup McMillen, Delissa Miller, Jeremy A. Moussa, Marmar Nery, Joseph R. Nicovich, Philip R. Niu, Sheng-Yong Orvis, Joshua Osteen, Julia K. Owen, Scott Palmer, Carter R. Pham, Thanh Plongthongkum, Nongluk Poirion, Olivier Reed, Nora M. Rimorin, Christine Rivkin, Angeline Romanow, William J. Sedeno-Cortes, Adriana E. Siletti, Kimberly Somasundaram, Saroja Sulc, Josef Tieu, Michael Torkelson, Amy Tung, Herman Wang, Xinxin Xie, Fangming Yanny, Anna Marie Zhang, Renee Ament, Seth A. Behrens, M. Margarita Bravo, Hector Corrada Chun, Jerold Dobin, Alexander Gillis, Jesse Hertzano, Ronna Hof, Patrick R. Hollt, Thomas Horwitz, Gregory D. Keene, C. Dirk Kharchenko, Peter V. Ko, Andrew L. Lelieveldt, Boudewijn P. Luo, Chongyuan Mukamel, Eran A. Pinto-Duarte, Antonio Preiss, Sebastian Regev, Aviv Ren, Bing Scheuermann, Richard H. Smith, Kimberly Spain, William J. White, Owen R. Koch, Christof Hawrylycz, Michael Tasic, Bosiljka Macosko, Evan Z. McCarroll, Steven A. Ting, Jonathan T. Zeng, Hongkui Zhang, Kun Feng, Guoping Ecker, Joseph R. Linnarsson, Sten Lein, Ed S. Allen Institute for Brain Science Seattle WA USA Department of Physiology and Biophysics University of Washington Seattle WA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Bioengineering University of California San Diego La Jolla CA USA The Salk Institute for Biological Studies La Jolla CA USA Epilepsy Center of Excellence Department of Veterans Affairs Medical Center Seattle WA USA Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory Cold Spring Harbor NY USA Department of Genetics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA LKEB Department of Radiology Leiden University Medical Center Leiden The Netherlands Pattern Recognition and Bioinformatics group Delft University of Technology Delft The Netherlands J. Craig Venter Institute La Jolla CA USA Department of Pathology University of California San Diego CA USA Division of Vaccine Discovery La Jolla Institute for Immunology La Jolla CA USA Genomic Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA Computer Science and Engineering Program University of California San Diego La Jolla CA USA Howard Hughes Medical Institute The Salk Institute for Biological Studies La Jolla CA USA Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA Institute for Genomes Sciences University of Maryland School of Medicine Baltimore MD USA Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA Ludwig Institute for Cancer Research La Jolla CA USA Department of Computer Science University of Maryland College Park College Park MD USA Sanford Burnham Prebys Medical Discovery Institute La Jolla CA USA Biomedical Sciences Program School of Medicine University of California San Diego La Jolla CA USA University of Connecticut Storrs CT USA Department

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Impact of Implementing Game Elements in Gamifying Educational Environment: A Study

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Journal of Physics: Conference Series 2019年第1期1358卷

作者： F Durin R Lee A Bade C K On N Hamzah Mathematics Graphics and Visualization Research Group (M-GRAVS) Faculty of Science and Natural Resources Universiti Malaysia Sabah 88450 Kota Kinabalu Sabah Malaysia Mathematics and Computer Graphics Faculty of Science and Natural Resources Universiti Malaysia Sabah Center of Excellence in Semantic Agents Universiti Malaysia Sabah Sabah Malaysia

Gamification is the use of game elements in a non-gaming environments. The aims of implementing game elements in gamifying educational environment is to make the learners engaged and motivated in the learning process. But, some of the research result giving bad impacts in implementing gamification in education. The objective of this research is to study the impact of implementing game elements in education. The aim of this research is to study which game elements is most commonly used in gamifying educational environment. The study is done by reviewing previous research on impacts of implementing game element in education from 2008 until 2018 to see whether the elements giving positive or negative impacts on education. The results shows the most common game elements used in gamification is rewards, feedback, challenge, quest/mission/goal, level/stage, point/score, avatars/players, task, character, time-limit, narrative/dialogue, leaderboards, progress bars, and badges. Majority of the research on gamification in education reports positive impacts by introducing gamification in education. In conclusion, by implementing game elements in the gamifying educational environment is a good method to create a good adjustment in learners' behavior and assertiveness in the learning process, it can develop engagement and motivation of the learners'.

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IDEAS: Immersive dome experiences for accelerating science

arXiv

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arXiv 2019年

作者： Faherty, Jacqueline K. SubbaRao, Mark Wyatt, Ryan Ynnerman, Anders deGrasse Tyson, Neil Geller, Aaron Weber, Maria Rosenfield, Philip Stoeckle, Gabriel Weiskopf, Daniel Magnor, Marcus Williams, Peter K.G. Abbott, Brian Marchetti, Lucia Jarrrett, Thomas Fay, Jonathan Peek, Joshua Graur, Or Durrell, Patrick Homeier, Derek Preston, Heather Müller, Thomas Vos, Johanna M. Brown, David Godfrey, Paige Giorla Rice, Emily Gagliuffi, Daniella Bardalez Bock, Alexander American Museum of Natural History Hayden Planetarium Adler Planetarium International Planetarium Society California Academy of Sciences Linköping University Adler Planetarium University of Chicago AAS WorldWide Telescope Instituto de Astronomiá UNAM Natural History Museum Vienna Austria Visualization Research Center University of Stuttgart Computer Graphics Lab TU Braunschweig Center for Astrophysics | Harvard & Smithsonian American Astronomical Society American Museum of Natural History Hayden Planetarium University of Cape Town Iziko Planetarium & Digital Dome Space Telescope Science Institute Johns Hopkins University Youngstown State University Ward Beecher Planetarium Förderkreis Planetarium Göttingen Germany Calusa Nature Center & Planetarium Haus der Astronomie MPIA Microsoft Research Slooh CUNY Macaulay Honors College Scientific Computing and Imaging Institute University of Utah

Astrophysics lies at the crossroads of big datasets (such as the Large Synoptic Survey Telescope and Gaia), open source software to visualize and interpret high dimensional datasets (such as Glue, WorldWide Telescope, and OpenSpace), and uniquely skilled software engineers who bridge data science and research fields. At the same time, more than 4,000 planetariums across the globe immerse millions of visitors in scientific data. We have identified the potential for critical synergy across data, software, hardware, locations, and content that-if prioritized over the next decade-will drive discovery in astronomical research. Planetariums can and should be used for the advancement of scientific research. Current facilities such as the Hayden Planetarium in New York City, Adler Planetarium in Chicago, Morrison Planetarium in San Francisco, the Iziko Planetarium & Digital Dome Research Consortium in Cape Town, and visualization center C in Norrköping are already developing software which ingests catalogs of astronomical and multi-disciplinary data critical for exploration research primarily for the purpose of creating scientific storylines for the general public. We propose a transformative model whereby scientists become the audience and explorers in planetariums, utilizing software for their own investigative purposes. In this manner, research benefits from the authentic and unique experience of data immersion contained in an environment bathed in context and equipped for collaboration. Consequently, in this white paper we argue that over the next decade the research astronomy community should partner with planetariums to create visualization-based research opportunities for the field. Realizing this vision will require new investments in software and human capital. Copyright © 2019, The Authors. All rights reserved.

关键词： Planetariums

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PO-260 Deep phenotyping of colorectal cancers by high-dimensional mass cytometry reveals tumor-specific immune landscapes

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ESMO Open 2018年 3卷 A328-A329页

作者： Vries, N. De Unen, V. Van Abdelaal, T. Herk, M. Van Van der Breggen, R. Sarasqueta, A. Farina Höllt, T. Lelieveldt, B. Koning, F. Miranda, N. De Leiden University Medical Center Immunohematology and Blood Transfusion Leiden The Netherlands Delft University of Technology Pattern Recognition and Bioinformatics Group Delft The Netherlands Leiden University Medical Center Pathology Leiden The Netherlands Delft University of Technology Computer Graphics and Visualization Group Delft The Netherlands Leiden University Medical Center Computational Biology Center Leiden The Netherlands Leiden University Medical Center Radiology Leiden The Netherlands

ABSTRACTIntroductionImmune checkpoint blockade has revolutionised cancer treatment. However, clinical outcomes are highly variable as only a proportion of cancer patients benefit from this treatment. To understand the mechanisms that determine responses to current immunotherapies and for the design of alternative approaches, it is crucial to characterise the immune landscape of the tumour microenvironment. An in-depth understanding of anti-tumour immunity requires a comprehensive analysis of the immune cell populations that participate in the process of tumorigenesis. The aim of this study is to unravel local and systemic profiles of lymphoid and myeloid immune subsets in colorectal cancer (CRC) using high-dimensional immunophenotyping by mass cytometry. Material and methodsThe expression of 36 immune cell markers was simultaneously assessed at the single-cell level by mass cytometry in tumour tissues (n=19), tumor-associated lymph nodes (n=17), adjacent normal mucosa (n=4), and peripheral blood samples (n=9) derived from 18 CRC patients. In total, 9 million cells were included in the analysis. Cytosplore and HSNE (Hierarchical Stochastic Neighbour Embedding) analysis tools were used to identify and visualise the composition of the lymphoid and myeloid cell populations of the innate and adaptive immune compartments in the tissues. Results and discussionsWe identified 220 immune cell subsets, including tumor-resident CD8 +CD45RO +CD103 +PD-1 +, CD4 +CD45RO +CD103 +PD-1 + and CD4 +CD45RO +ICOS +CD27 - T cell populations that were not found in tumor-associated lymph nodes, adjacent normal mucosa, and peripheral blood samples of CRC patients. In addition, we identified an overrepresentation of CD3 -CD7 +CD56 +CD45RO +CD127 - intermediate innate lymphoid cells in mismatch-repair deficient cancers and an enrichment of CD14 - myeloid populations in mismatch-repair proficient cancers. Unsupervised clustering of the samples based on the composite immune profile separated the

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visualization of Biomolecular Structures: State of the Art 17

Visualization of Biomolecular Structures: State of the Art

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17th Eurographics Conference on visualization - State of the Art Reports, EuroVis-STAR 2015

作者： Kozlíková, B. Krone, M. Lindow, N. Falk, M. Baaden, M. Baum, D. Viola, I. Parulek, J. Hege, H.-C. Faculty of Informatics Masaryk University Czech Republic Visualization Research Center University of Stuttgart Germany Department of Visual Data Analysis Zuse Institute Berlin Germany Immersive Visualization Group Linköping University Sweden Laboratoire de Biochimie Théorique UPR 9080 CNRS France Department of Informatics University of Bergen Norway Institute of Computer Graphics and Algorithms Vienna University of Technology Austria

ISBN: (纸本)9783905674996

Structural properties of molecules are of primary concern in many fields. This report provides a comprehensive overview on techniques that have been developed in the fields of molecular graphics and visualization with a focus on applications in structural biology. The field heavily relies on computerized geometric and visual representations of three-dimensional, complex, large, and time-varying molecular structures. The report presents a taxonomy that demonstrates which areas of molecular visualization have already been extensively investigated and where the field is currently heading. It discusses visualizations for molecular structures, strategies for efficient display regarding image quality and frame rate, covers different aspects of level of detail, and reviews visualizations illustrating the dynamic aspects of molecular simulation data. The report concludes with an outlook on promising and important research topics to enable further success in advancing the knowledge about interaction of molecular structures. © The Eurographics Association 2015.

关键词： visualization

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Constructing Multiple Scene Graphs in Distributed Environment

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computer Aided Drafting,Design and Manufacturing 2015年第1期25卷 16-21页

作者： XIA Rui WANG Guo-ping LI Sheng WANG Heng Shenzhen Key Lab for Cloud Computing Technology and Applications Shenzhen Graduate School of Peking University Graphics & Interaction Lab. School of Electronics Engineering and Computer SciencesPeking University Beijing Engineering Technology Research Center of Virtual Simulation and Visualization Peking University

Scene graph is a infrastructure of the virtual reality system to organize the virtual scene with abstraction, it can provide facility for the rendering engine and should be integrated effectively on demand into a real-time system, where a large quantities of scene objects and resources can be manipulated and managed with high flexibility and reliability. We present a new scheme of multiple scene graphs to accommodate the features of rendering engine and distributed systems. Based upon that, some other functions, e.g. block query, interactive editing, permission management, instance response, ＂redo＂ and ＂undo＂, are implemented to satisfy various requirements. At the same time, our design has compatibility to popular C/S architecture with good concurrent performance. Above all, it is convenient to be used for further development. The results of experiments including responding time demonstrate its good performance.

关键词： multiple scene graphs authority scene editing distributed systems

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Information technology for communities: Development of a web-based 3D visualization and cluster computing system for disaster management

Information technology for communities: Development of a web...

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121st ASEE Annual Conference and Exposition: 360 Degrees of Engineering Education

作者： Jin, Ge Dekker, Gerald A. Moreland, John Nicolai, Barbara Jean Department of Computer Information Technology and Graphics College of Technology Purdue University Calumet United States Department of Computer Science Purdue University Calumet United States Center for Innovation through Visualization and Simulation Purdue University Calumet United States

Natural disasters can cause huge loss of life, enormous amounts of property damage to the local communities. Although it is impossible to avoid the natural disasters, human sufferings can be reduced by adopting information technologies to the disaster response missions. In this paper, a web-based 3D visualization and cluster computing system was developed to facilitate and expedite the resource distribution process during a disaster. Our disaster management system utilizes state-of- The- Art computing cluster with 16 nodes of Intel Xeon-E5 processors (16 cores per node) to process the emergency supply requests from the disaster victims, and calculate the optimal resource distribution routes with the consideration of the damaged transportation infrastructures. The optimized resource distribution problem was solved with distributed all pair shortest path algorithm and the vehicle routing algorithm. The web-based 3D visualization system was developed with Google earth engine to display the disaster areas, affected households and resource distribution routes. The computation result from the cluster was automatically uploaded to the web-based 3D visualization system, enabling the users to immediately see the optimal resource distribution routes in a virtual 3D environment. The visualization system is flexible and can be easily adapted to a Google earth enabled mobile devices, desktop monitors as well as a Cave automatic virtual environment (CAVE). A historical disaster data from the Northwest Indiana was used to demonstrate the functionalities of the developed system. © American Society for Engineering Education, 2013.

关键词： Virtual reality

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User-guided Compressed Sensing for Magnetic Resonance Angiography

User-guided Compressed Sensing for Magnetic Resonance Angiog...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Changgong Zhang Martijn van de Giessen Elmar Eisemann Anna Vilanova Section of Computer Graphics and Visualization Delft University of Technology Division of Image Processing Department of Radiology Leiden University Medical Center

ISBN: (纸本)9781424479276

Compressed sensing (CS) magnetic resonance imaging (MRI) enables the reconstruction of MRI images with fewer samples in k-space. One requirement is that the acquired image has a sparse representation in a known transform domain. MR angiograms are already sparse in the image domain. They can be further sparsified through finite-differences. Therefore, it is a natural application for CS-MRI. However, low-contrast vessels are likely to disappear at high under-sampling ratios, since the commonly used l_1 reconstruction tends to underestimate the magnitude of the transformed sparse coefficients. These vessels, however, are likely to be clinically important for medical diagnosis. To avoid the fading of low-contrast vessels, we propose a user-guided CS MRI that is able to mitigate the reduction of vessel contrast within a region of interest (ROI). Simulations show that these low-contrast vessels can be well maintained via our method which results in higher local quality compared to conventional CS.

关键词： Image reconstruction Magnetic resonance imaging Compressed sensing Minimization Angiography Transforms Fading

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