In irregular pyramids, their vertical structure is not determined beforehand as in regular pyramids. We present three methods, all based on maximal independent sets from graph theory, with the aim to simulate the majo...
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A fast data association algorithm based on the attribute intensity of space intersection for the static association problem is presented in this paper. All of sensors are passive sensors, which obtained the angle only...
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A fast data association algorithm based on the attribute intensity of space intersection for the static association problem is presented in this paper. All of sensors are passive sensors, which obtained the angle only, in presence of clutter, missed detection, false alarm, and an unknown number and location of targets. comp.rison of our method to the classical algorithm demonstrates that our algorithm is superior to the classical approach in terms of comp.tational comp.exity and association accuracy via several simulations.
Background: The preoperative planning of liver resections is commonly based on two-dimensional imaging techniques such as sonography, comp.ted tomography (CT), and magnetic resonance imaging. The operability of liver ...
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Background: The preoperative planning of liver resections is commonly based on two-dimensional imaging techniques such as sonography, comp.ted tomography (CT), and magnetic resonance imaging. The operability of liver tumors depends on the three-dimensional relation of the parenchyma to be resected to the intrahepatic vascular structures which define the autonomously functioning liver segments. Our aim was to establish a liver surgery planning system (LSPS) for major liver resections by augmented-reality (AR) techniques for the accurate evaluation of operability. Methods: The system provides methods for the processing and preparation of the input CT data, three-dimensional visualization, and resection planning. The output consists of quantitative indices (e.g., volume of liver tumors or segments) and an elaborated plan for the surgical procedure including information like the number of liver segments subject to resection and their spatial arrangement or the volume of the remaining or the removed liver tissue. Basically, the LSPS comp.ises two main comp.nents, a medical image analysis and an AR system. The medical image analysis part is responsible for the segmentation of the liver, the vascular structures, and the tumors and for liver segment approximation. The AR system is utilized for visualization and various kinds of user interaction. Results: Experiments with anonymized CT data sets demonstrated the ability of surgeons to deal with different tasks in resection planning after a brief introduction. This led also to a high acceptance by colleagues who wanted to get information for their surgical strategy as quickly as possible. Conclusions: Quantitative measurements are of major importance for the planning of liver resections, for which precise measurements of distances and volumes are required. On the basis of the patient's CT dataset, the LSPS supports an effective way to find the optimal surgical strategy for each patient. The flexible design of this system allo
Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occup...
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Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occupant and the position of the occupant's head. This paper presents a method for classification and occupant's head detection based on passive stereo vision. The proposed system uses depth surface analysis and scene statistics together with support vector machines for classification and selection of head candidates. Evaluation of the method shows 99% correct for classification and 98% correct for head detection, using large sets of image data, and image sequences recorded in a driving vehicle.
In our days the business, scientific and personal databases are growing in an exponential rate. However, what is truly valuable is the knowledge that can be extracted from the stored data. Knowledge Discovery in paten...
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In our days the business, scientific and personal databases are growing in an exponential rate. However, what is truly valuable is the knowledge that can be extracted from the stored data. Knowledge Discovery in patent databases was traditionally based on manual analysis carried out from statistical experts. Nowadays the increasing interest of many actors have led to the development of new tools for discovering and exploiting information related to technological activities and innovation, "hidden" in patent databases. In this paper we present a system that combines efficient and innovative methodologies and tools for the analysis of patent data stored in international databases and the production of scientific and technological indicators.
The skeleton is an effective representation of object shapes. Methods based on distance transformation can generate skeletons with accurate position, but connectivity of the skeleton branches must be carefully checked...
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The skeleton is an effective representation of object shapes. Methods based on distance transformation can generate skeletons with accurate position, but connectivity of the skeleton branches must be carefully checked. It is difficult to check the connectivity when the structures of the skeleton are very comp.icated. A dynamic skeleton algorithm for binary images is presented by combining with thinning method and Snake model technique. First, we comp.te the initial skeleton based on thinning technology in which the connectivity and the topology of the skeleton can be kept well. Then the initial skeleton can be led to its accurate locations in distance field based on Snake model technique. The skeletons generated by this method are not only locating at accurate positions, but also with correct connectivity and topology.
A modification to the fuzzy connectedness image segmentation is presented. Through checking the property affinity between the seed pixel and the pixel along the optimal path which has the largest fuzzy connectedness f...
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A modification to the fuzzy connectedness image segmentation is presented. Through checking the property affinity between the seed pixel and the pixel along the optimal path which has the largest fuzzy connectedness from the pixel to seed pixel, good results can be achieved, especially for those objects with blurred boundary. Additionally, an image-scanning mechanism algorithm for detecting optimal paths is proposed to calculate the fuzzy connectedness between pixels and the seed pixel one by one. This algorithm can make full use of the properties of fuzzy connectedness and property affinity, and detect the optimal path between two pixels effectively. Experimental examples show that the new method is simple, fast, and works well for some images.
Surfaces reconstruction from serial section images is a mature research in visualization of medical imaging. Traditional methods always adopt the process that starts on mesh reconstruction or isosurfaces extraction, t...
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Surfaces reconstruction from serial section images is a mature research in visualization of medical imaging. Traditional methods always adopt the process that starts on mesh reconstruction or isosurfaces extraction, then data simplification. Since the volumetric datasets are huge and segmented. Most of the existing algorithms that use large in-core data structures might be too large to off-load to disk. An algorithm is presented that is designed to reconstruct 3D surfaces from huge and segmented volumetric datasets. Approximate mesh can be reconstructed and simplified layer by layer. And user can control mesh comp.exity by parameters. Because memories are used rationally, some surfaces reconstruction from large datasets can work on PC using the algorithm.
This contribution presents a video analysis system which provides automatic content analysis and enables manual and semi-automatic annotation. In particular, we focus on object recognition and visual video indexing. W...
This contribution presents a video analysis system which provides automatic content analysis and enables manual and semi-automatic annotation. In particular, we focus on object recognition and visual video indexing. We briefly review the current state of the art based on interest point extraction (e.g. Harris points, Maximally Stable Extremal Regions) and calculation of invariant descriptors around these points (e.g. SIFT, differential invariants). The main challenge for recognition from videos is the efficiency due to the huge size of the database. We will illustrate these concepts on the recently started project, TheoMedia (joint work between TU Graz, Joanneum Research and inst.tute for Fundamental Theology at KFU Graz) where we use recognition and indexing technology for analyzing films in order to find religious symbols. The goal of the project is to use all the available information retrieval technology to substantially speed up the analysis process.
QSPR analyses of the solubility in water of 558 vapors, 786 liquids and 2045 solid organic neutral chemicals and drugs are presented. Simultaneous consideration of H-bond acceptor and donor factors leads to a good des...
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