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检索条件"任意字段=Conference on Visualization in Biomedical Computing"

共 893 条记录，以下是261-270 订阅

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Wear Your Heart on Your Sleeve: Visible Psychophysiology for Contextualized Relaxation 7

Wear Your Heart on Your Sleeve: Visible Psychophysiology for...

引用

7th International conference on Affective computing and Intelligent Interaction (ACII)

作者： Hair, Adam Texas A&M Univ Dept Comp Sci & Engn College Stn TX 77843 USA

ISBN: (纸本)9781538605639

Chronic stress is a global epidemic, but in the United States, 42% of adults say they are not doing enough to manage stress. Additionally, 1 in 5 adults report doing nothing to manage their stress. A variety of relaxation methods attempt to mitigate the effects of long-term stress, but they can be non-intuitive, difficult to use, or unsuited for daily life. This paper proposes to study the usability and design of deep breathing biofeedback guides for in-situ relaxation. The author will achieve this by designing a biofeedback guide, developing robust measures of arousal from wearable sensors, and conducting a long-term study with the intervention in a workplace environment. When completed, these studies will compose the foundation for the authors dissertation.

关键词： Heart rate variability Biological control systems Stress Sensors visualization Heart beat biomedical monitoring

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Curation of Image Data for Medical Research

Curation of Image Data for Medical Research

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IEEE International conference on e-Science and Grid computing

作者： Lasse Wollatz Mark Scott Steven J. Johnston Peter M. Lackie Simon J. Cox Faculty of Engineering and Physical Sciences University of Southampton Southampton UK Faculty of Medicine University of Southampton Southampton UK

Microfocus X-ray computed tomography (μCT) and 3D microscopy scanning create scientific data in the form images. These images are each several tens of gigabytes in size. E-Scientists in medicine require a user-friendly way of storing the data and related metadata and accessing it. Existing management systems allow computer scientists to create automatic image workflows through the use of application programming interfaces (APIs) but do not offer an easy alternative for users less familiar with programming. We present a new approach to the management and curation of biomedical image data and related metadata. Our system, Mata, uses a network file share to give users direct access to their data and also provides access to metadata. Mata also enables a variety of visualization options as required by e-Scientists in medicine.

关键词： Metadata biomedical imaging Software Databases Tag clouds Computed tomography Pediatrics

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Big Data Analytics in Healthcare

Big Data Analytics in Healthcare

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International conference on Advanced computing, ICAC

作者： M. Ambigavathi D. Sridharan Research Scholar Anna University Chennai India Professor Anna University Chennai India

The pace of both digital innovation and technology disruption is refining the healthcare industry at an exponential rate. The large volume of healthcare data continues to mount every second, making it harder and very difficult to find any form of useful information. Recently, big data is shifting the traditional way of data delivery into valuable insights using big data analytics method. Big data analytics provides a lot of benefits in the healthcare sector to detect critical diseases at the initial stage and deliver better healthcare services to the right patient at the right time so that it improves the quality of life care. Big data analytics tools play an essential role to analyze and integrate large volumes of structured, semi-structured and unstructured vital data rapidly produced by the various clinical, hospitals, other social web sources and medical data lakes. However, there are several issues to be addressed in the current health data analytics platforms that offer technical mechanisms for data collection, aggregation, process, analysis, visualization, and interpretation. Due to lack of detailed study in the previous literature, this article inspects the promising field of big data analytics in healthcare. This article examines the unique characteristics of big data, big data analytical tools, different phases followed by the healthcare economy from data collection to the data delivery stage. Further, this article briefly summarizes the open research challenges with feasible findings, and then finally offers the conclusion.

关键词： Medical services Big Data Tools biomedical imaging Data mining Data analysis Data models

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Building NDStore Through Hierarchical Storage Management and Microservice Processing

Building NDStore Through Hierarchical Storage Management and...

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IEEE International conference on e-Science and Grid computing

作者： Kunal Lillaney Dean Kleissas Alexander Eusman Eric Perlman William Gray Roncal Joshua T. Vogelstein Randal Burns Dept. of Computer Science Applied Physics Laboratory Center for Imaging Science Dept. of Biomedical Engineering Johns Hopkins University Baltimore Maryland

We describe NDStore, a scalable multi-hierarchical data storage deployment for spatial analysis of neuroscience data on the AWS cloud. The system design is inspired by the requirement to maintain high I/O throughput for workloads that build neural connectivity maps of the brain from peta-scale imaging data using computer vision algorithms. We store all our data on the AWS object store S3 to limit our deployment costs. S3 serves as our base-tier of storage. Redis, an in-memory key-value engine, is used as our caching tier. The data is dynamically moved between the different storage tiers based on user access. All programming interfaces to this system are RESTful web-services. We include a performance evaluation that shows that our production system provides good performance for a variety of workloads by combining the assets of multiple cloud services.

关键词： Cloud computing Neuroscience Data visualization Indexes Computer architecture Imaging Bandwidth

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A Single-sensor High-resolution Panoramic Optical Mapping Configuration for Simultaneous Non-overlapped Complete Atrial and Ventricular Parametric Imaging 44

A Single-sensor High-resolution Panoramic Optical Mapping Co...

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44th computing in Cardiology conference (CinC)

作者： Calvo, Conrado J. Guill, Antonio Tormos, Alvaro Such-Miquel, Luis Zarzoso, Manuel Arias, Oscar Such, Luis Chorro, Javier Millet, Jose Univ Politecn Valencia Dept Elect Engn ITACA Valencia Spain Univ Valencia Dept Physiol Valencia Spain Univ Valencia Dept Med Valencia Spain Univ Valencia Dept Physiotherapy Valencia Spain Hosp Clin Univ IIS Incl Cardiol Unit CiberCV Valencia Spain

ISBN: (纸本)9781538645550;9781538666302

Nowadays optical mapping (OM) is the primary method for imaging electrophysiologically relevant parameters from the outer surface of Langendorff-perfused hearts. This technique has become essential for comprehensively understanding mechanisms of cardiac propagation during physiological activation, arrhythmia, and therapeutic antiarrhythmic interventions in translational hearts. Panoramic whole heart optical mapping systems, using either multiple cameras, plane mirrors or a combination of both, have been developed to overcome intrinsic visualization limitations to traditional single-sensor designs. However current panoramic OM systems are financially challenging for physiology and engineering research labs since require multiple sensors to completely map wide areas of the surface, which further results on overlapping regions and/or missing areas of interest due to the intrinsic shape of the heart. In this study, we propose and validate a new spatially resolved low-cost single-sensor configuration to simultaneously record atrial and ventricular function in relation to its anatomy without overlapping regions.

关键词： Heart Optical imaging biomedical monitoring Image reconstruction Optical sensors Optical filters biomedical monitoring Heart OPTICAL FILTER optical sensors Optical Imaging image reconstruction Heart Atria MAPPING(MATHEMATICAL) surface area Engineering research

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A method of volume calculation for 3D models described by Bézier surfaces using example objects of biomedical origin 11

A method of volume calculation for 3D models described by B...

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11th International conferences on Computer Graphics, visualization, Computer Vision and Image Processing, CGVCVIP 2017 and International conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2017

作者： Sisojevs, Aleksandrs Bolocko, Katrina Krutikova, Olga Ventspils University College 101 Inženieru Str. VentspilsLV-3601 Latvia Riga Technical University Faculty of Computer Science and Information Technology 2 Daugavgrivas Str. RigaLV-1048 Latvia

ISBN: (纸本)9789898533661

This paper describes a method of computing volume for 3D objects bounded by Bézier surfaces using example models of biomedical origin. The authors present three different theorems for volume calculation, based, based on different properties of researched models, acquired by projection of surface vertices on coordinate system origin point, axis and plane. The proposed approach is based on using methods of differential geometry: surface integrals of scalar fields, Euler integral of the first kind and Beta functions. Experimental results prove the accuracy of presented theorems. The proposed method can be successfully used to calculate the volume of different 3D models, including objects of biomedical origin. © 2017.

关键词： Geometry

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Modeling, Design and Simulation of Systems 1st ed. 2017

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丛书名： Communications in Computer and Information Science

2017年

作者： Mohamed Sultan Mohamed Ali Herman Wahid Nurul Adilla Mohd Subha Shafishuhaza Sahlan Mohd Amri Md. Yunus Ahmad Ridhwan Wahap

ISBN: (数字)9789811065026

ISBN: (纸本)9789811065019

This two-volume set CCIS 751 and CCIS 752 constitutes the proceedings of the 17th Asia Simulation conference, AsiaSim 2017, held in Malacca, Malaysia, in August/September 2017. The 124 revised full papers presented in thistwo-volume setwere carefully reviewed and selected from 267 submissions. The papers contained in these proceedings address challenging issues in modeling and simulation in various fields such as embedded systems; symbiotic simulation; agent-based simulation; parallel and distributed simulation; high performance computing; biomedical engineering; big data; energy, society and economics; medical processes; simulation language and software; visualization; virtual reality; modeling and Simulation for IoT; machine learning; as well as the fundamentals and applications of computing.

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Data visualization Using Interactive Dimensionality Reduction and Improved Color-Based Interaction Model 7th

Data Visualization Using Interactive Dimensionality Reductio...

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6th International Work-conference on the Interplay Between Natural and Artificial Computation (IWINAC)

作者： Rosero-Montalvo, P. D. Pena-Unigarro, D. F. Peluffo, D. H. Castro-Silva, J. A. Umaquinga, A. Rosero-Rosero, E. A. Univ Tecn Norte Ibarra Ecuador Inst Tecnol Super 17 Julio Ibarra Ecuador Univ Narino Pasto Colombia Corporac Univ Autonoma Narino Pasto Colombia Univ Surcolombiana Neiva Huila Colombia

ISBN: (纸本)9783319597737;9783319597720

This work presents an improved interactive data visualization interface based on a mixture of the outcomes of dimensionality reduction (DR) methods. Broadly, it works as follows: The user can input the mixture weighting factors through a visual and intuitive interface with a primary-light-colors-based model (Red, Green, and Blue). By design, such a mixture is a weighted sum of the color tone. Additionally, the low-dimensional representation space produced by DR methods are graphically depicted using scatter plots powered via an interactive data-driven visualization. To do so, pairwise similarities are calculated and employed to define the graph to simultaneously be drawn over the scatter plot. Our interface enables the user to interactively combine DR methods by the human perception of color, while providing information about the structure of original data. Then, it makes the selection of a DR scheme more intuitive -even for non-expert users.

关键词： Color-based model Data visualization Dimensionality reduction Pairwise similarity

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Real-time 3D ultrasound reconstruction and visualization in the context of laparoscopy 1

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20th International conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2017

作者： Jayarathne, Uditha L. Moore, John Chen, Elvis C. S. Pautler, Stephen E. Peters, Terry M. Robarts Research Institute London Canada Department of Biomedical Engineering Western University London Canada Department of Surgery Western University London Canada

ISBN: (数字)9783319661858

ISBN: (纸本)9783319661841

In the context of laparoscopic interventions involving intracorporeal ultrasound, we present a method to visualize hidden targets in 3D. As the surgeon scans the organ surface, we stitch tracked 2D ultrasound images into a 3D volume in real-time. This volume, registered in space with the surface view provided by the laparoscope, is visualized through a transparent window in the surface image. The efficacy of the proposed method is demonstrated by conducting a psychophysical study with phantoms, involving experienced ultrasound users and laparoscopic surgeons. The results reveal that the proposed method demands significantly less cognitive and physical effort compared to the 2D ultrasound visualization method conventionally used in the operating room. © Springer International Publishing AG 2017.

关键词： Laparoscopy

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First-person Action Decomposition and Zero-shot Learning 17

First-person Action Decomposition and Zero-shot Learning

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17th IEEE Winter conference on Applications of Computer Vision (WACV)

作者： Zhang, Yun C. Li, Yin Rehg, James M. Georgia Inst Technol Ctr Behav Imaging Atlanta GA 30332 USA Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA Georgia Inst Technol Coll Comp Atlanta GA 30332 USA

ISBN: (纸本)9781509048229

In this work, we decompose a first-person action into verb and noun. We then study how the coupling of an action's constituent verb and noun affects the learners' ability to learn them separately and to combine them to perform recognition. We compare different information fusion methods on conventional action recognition and zero-shot learning, of which the latter is a strong indication of the feature's ability to capture one concept (verb/noun) and not be confounded by the other. To achieve the decoupling of verb/noun concepts, we extract features that are specialized for each of them. Specifically, we use improved dense trajectories and convolutional neural network activations. We show that by constructing specialized features for the decomposed concepts, our method succeeds in zero-shot learning. More surprisingly, it also outperforms previous results in conventional action recognition when the performance gaps of different features on verb/noun concepts are significant.

关键词： Trajectory Cameras visualization Training Feature extraction Image recognition Adaptation models

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