visualization is a young and booming research field with a growing community and increasingly competitive conferences and journals. Often, the 1987 NSF Report on visualization in Scientific computing (by McCormick et ...
ISBN:
(纸本)9781450307697
visualization is a young and booming research field with a growing community and increasingly competitive conferences and journals. Often, the 1987 NSF Report on visualization in Scientific computing (by McCormick et al.) is seen as an important starting point into a more explicit form of visualization research. In the mid-nineties then information visualization shaped itself as an own research (sub-)field and recently we see again new developments, including the visual analytics initiative as started in 2005. visualization is bound to deliver advantages to related application fields -- if no (application) user gains an advantage from using visualization, e.g., to speed up a process, to improve results, etc., then visualization cannot consider itself successful. There are many examples by now, where visualization was successfully applied, including biomedical applications, engineering, meteorology and climate research, business, and others. In this talk, I am giving my subjective view on the state of visualization as a research field and aim at carefully predicting a bit of its future.
NLP-NG is a new NLP system consisting of three components: NG-CORE (language processing), NG-DB (database management), and NG-SEE (interactive visualization and entry). The ultimate goal of NLP-NG is to produce inform...
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NLP-NG is a new NLP system consisting of three components: NG-CORE (language processing), NG-DB (database management), and NG-SEE (interactive visualization and entry). The ultimate goal of NLP-NG is to produce information retrieval systems in which users can choose full-text schema, adding specific items to focus their queries. Schema are created by a normalization process which elides adjunctive constructions as well as replacing items by prototypes. biomedical text contains domain-specific constructions which are revealed by normalization. NLP-NG is based on Construction Grammar. Computationally, all representations are integer-based, allowing efficient storage, indexing, and retrieval. SEE, an Ajax web browser client, allows developers, linguists, and users to view a corpus and modify its properties. NLP-NG uses a 300 million word BioMed Central corpus. NLP-NG does not focus on specific strategies to extract limited classes of information from papers. Instead, it is a universal approach that can codify a wide variety of text in papers.
A segment-based protein sequence analyzing system (SPSAS), based on an established protein segment subsequence database, is described. Using this system, users can manage and partition the raw protein sequences, extra...
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A segment-based protein sequence analyzing system (SPSAS), based on an established protein segment subsequence database, is described. Using this system, users can manage and partition the raw protein sequences, extract segment subsequence, align segment-based protein sequence and visualize the raw protein sequence. The aim of SPSAS is to provide a convenient tool for biologists to analyze the segment-based protein sequences.
The size of volumetric data generated by medical imaging and scientific simulations is increased significantly due to the dramatic advances in medical imaging modalities and computing technologies. The volumetric data...
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The size of volumetric data generated by medical imaging and scientific simulations is increased significantly due to the dramatic advances in medical imaging modalities and computing technologies. The volumetric data generally need to be visualized and marching cubes algorithm (MC for short) is one of the standard methods of the isosurface extraction for the medical applications. However, MC algorithm requires a large amount of data computing power. The cell broadband engine (Cell for short) processor, which is a typical COTS (commodity off-the-shelf) heterogeneous designed to handle extremely demanding computations, can be used to hasten isosurface extraction in medial application. In this paper, we present a streaming model-based scheme to efficiently map MC algorithm to Cell. Specifically, a block-based filter running on PPE is imposed as a preprocessing stage to avoid unnecessary data transfer and computation, and the MC kernel runs on SPEs as the subsequent stage. Through tuning the size of the block, the workload of PPE and SPE is orchestrated harmoniously. The experimental results demonstrate that overall isosurface extraction speedup of more than 10 times is achieved compared with conventional heavy iron CPUs.
Medical diagnosis is often made on the basis of information from visualisation instruments such as CT scanners. This information is currently used by medics only and, in most cases, browsed manually. This paper presen...
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Medical diagnosis is often made on the basis of information from visualisation instruments such as CT scanners. This information is currently used by medics only and, in most cases, browsed manually. This paper presents technical issues which are prerequisite to decision-support systems which analyse such data and provide new ways to present the data so as to make it most useful to clinicians, taking the domain of renal (kidney) cancer care as an example. In the long term such systems can also be used to improve communication between medics and patient, and may also enable communication with remote consultants.
Providing affordable, high-quality healthcare to the elderly while enabling them to live independently longer is of critical importance. In our Smart Condo project, we have deployed a wireless sensor network in an 850...
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Providing affordable, high-quality healthcare to the elderly while enabling them to live independently longer is of critical importance. In our Smart Condo project, we have deployed a wireless sensor network in an 850-square-foot condominium for assisted living. The sensor network records a variety of events and environmental parameters and feeds the related data into our web-based system. This system is responsible for inferring higher-order information about the activities of the condo's occupant and visualizing the collected information in both a 2D Geographic Information System (GIS) and a 3D virtual world. The architecture is flexible in terms of supported sensor types, analyses, and visualizations through which it communicates this information to its users, including the condo's occupant, their family, and their healthcare providers.
In radiotherapy simulations, Monte Carlo-based radiotherapy simulation is applied to a high accurate calculation of dose distributions in a patient or optimization of the beam delivery system. Geant4 toolkit has come ...
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In radiotherapy simulations, Monte Carlo-based radiotherapy simulation is applied to a high accurate calculation of dose distributions in a patient or optimization of the beam delivery system. Geant4 toolkit has come to be utilized to build a Monte Carlo simulator for that purpose. It needs the volume rendering capability to display a complex volume data by a visualizer. However, there is no volume rendering capability in the visualization system in Geant4. A volume visualization driver for Geant4 is described in this paper, which is available to display a complex patient image and a dose distribution calculated in a Geant4-based radiotherapy simulation with an external volume visualizer. The volume visualization driver extracts a patient data set, calculated dose distributions, particle trajectories and geometrical information of beam delivery modules in the simulation, and then saves their information as a data file. With that data file, the external volume visualizer is able easily to display results of the simulation.
Volume rendering techniques have been used widely for high quality visualization of 3D data sets, especially in the fields of biomedical image processing. However, when rendering very large (out-of-core) volume data s...
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Volume rendering techniques have been used widely for high quality visualization of 3D data sets, especially in the fields of biomedical image processing. However, when rendering very large (out-of-core) volume data sets, the conventional incore volume rendering algorithms cannot run efficiently due to the impossibility of fitting the entire input data in the internal memory of a computer. In order to solve this problem, an efficient out-of-core volume rendering method based on volume ray casting and GPU acceleration, with a new out-of-core framework for visualizing large volume data sets, are proposed in this paper. The new framework gives a transparent and efficient access to the volume data set cached in the hard disk, while the new volume rendering method minimize the times of reloading volume data from the hard disk to the internal memory and perform comparatively fast high-quality volume rendering. The experimental results indicate that the new method and framework are effective and efficient for the visualization of out-of-core medical data sets.
This paper is concerned with extracting 3D models from volumetric images. Building models of 3D shape relies on placement of landmarks and in many biological and medical applications automatic landmark placement is im...
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This paper is concerned with extracting 3D models from volumetric images. Building models of 3D shape relies on placement of landmarks and in many biological and medical applications automatic landmark placement is impractical. We introduce a system, called uFeel, which allows manual placement of landmarks in 3D using a combination of stereo and haptics. This system is used to capture and analyse data on growing Arabidopsis leaves.
Navigation during minimally invasive surgery (MIS) has recognized difficulties due to limited field-of-view, off-axis visualization and loss of direct 3D vision. This can cause visual-spatial disorientation when explo...
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Navigation during minimally invasive surgery (MIS) has recognized difficulties due to limited field-of-view, off-axis visualization and loss of direct 3D vision. This can cause visual-spatial disorientation when exploring complex in vivo structures. In this paper, we present an approach to dynamic view expansion which builds a 3D textured model of the MIS environment to facilitate in vivo navigation. With the proposed technique, no prior knowledge of the environment is required and the model is built sequentially while the laparoscope is moved. The method is validated on simulated data with known ground truth. Its potential clinical value is also demonstrated with in vivo experiments.
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