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"abstract": "Molecular communication is a novel nanoscale communication method. The information can be encoded by using different molecules for transmission. However, as a result of various symbol molecules are easy to interfere with each other and the stochastic behaviour of the molecules, molecular communication is easily susceptible to a low reliability. Therefore, reliability is a vital issue in the field of molecular communication. At present, the reliability analysis of existing molecular communication has not taken the drift velocity into consideration. In this paper, we introduce the drift velocity of molecules and propose a reliability model of molecular communication based on drift diffusion in the single link and single path. Furthermore, retransmission mechanism is introduced on the condition of the transmission failure. Finally, our simulation experiments show how the parameters in the model affect the reliability of molecular communication based on drift diffusion, which can guide us how to improve the reliability of molecular communication based on drift diffusion in the future.",
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"title": "2011 Eighth International Symposium on Voronoi Diagrams in Science and Engineering",
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"abstract": "Molecular shape is one of the most critical factors that determine molecular function. To properly understand the function of a molecule, it is necessary to explore its geometric properties more effectively and efficiently in addition to its physicochemical properties. Due to the complexity of the problems in biomolecular structure, in-silico approach is inevitable for many cases and is becoming more popular. In this paper, we introduce BetaMol, a comprehensive, powerful graphics-based software for molecular modeling, analysis, and visualization. BetaMol is based on the recent theory of the beta-complex which is derived from the Voronoi diagram of spheres. The entire set of powerful features of BetaMol is completely based on a single framework of the mathematically rigorous and computationally efficient theory of beta-complex. BetaMol is implemented in the standard C++ language with the OpenGL graphics library on Windows platform. Both BetaMol and some of its important functions ported for Linux platform are freely available at Voronoi Diagram Research Center website (http://voronoi.hanyang.ac.kr).",
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"content": "Molecular shape is one of the most critical factors that determine molecular function. To properly understand the function of a molecule, it is necessary to explore its geometric properties more effectively and efficiently in addition to its physicochemical properties. Due to the complexity of the problems in biomolecular structure, in-silico approach is inevitable for many cases and is becoming more popular. In this paper, we introduce BetaMol, a comprehensive, powerful graphics-based software for molecular modeling, analysis, and visualization. BetaMol is based on the recent theory of the beta-complex which is derived from the Voronoi diagram of spheres. The entire set of powerful features of BetaMol is completely based on a single framework of the mathematically rigorous and computationally efficient theory of beta-complex. BetaMol is implemented in the standard C++ language with the OpenGL graphics library on Windows platform. Both BetaMol and some of its important functions ported for Linux platform are freely available at Voronoi Diagram Research Center website (http://voronoi.hanyang.ac.kr).",
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"abstract": "There are several computational models and algorithms for the visualization of biomolecules (e.g. proteins and DNA), usually as three-dimensional surfaces called molecular surfaces. Based on the Van-der-Waals model, which represents a molecule as a set of spheres (i.e. atoms), a major approach in modeling and visualization of molecular surfaces, called blobby molecules, represents an implicitly-defined molecular surface as the result of the sum of implicit functions, where each function describes a Van-der-Walls sphere (i.e. the geometry of an atom). In general, these surfaces are polygonized using the well known marching cubes algorithm or similar space-partitioning method. In contrast, this paper presents a very accurate continuation algorithm to polygonize blobby molecules with a very high mesh quality, smoothness and scalability.",
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"abstract": "Visualization of tubular structures such as blood vessels is an important topic in medical imaging. One way to display tubular structures for diagnostic purposes is to generate longitudinal cross-sections in order to show their lumen, wall, and surrounding tissue in a curved plane. This process is called Curved Planar Reformation (CPR). We present three different methods to generate CPR images. A tube-phantom was scanned with Computed Tomography (CT) to illustrate the properties of the different CPR methods. Furthermore we introduce enhancements to these methods: thick-CPR, rotating-CPR and multi-path-CPR.",
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"affiliation": "Vienna University of Technology",
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"affiliation": "University of Vienna",
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"title": "Numerical simulations of wake structure generated by rotating blades using a time marching, free vortex blob method",
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"abstract": "Vorticity fields in the wake generated by rotating blades are calculated using a time accurate, free vortex blob method without a non physical model of the far wake. The computed free wake geometry of single rotor in hover is represented by the three wake regions: well defined tip vortex region, intermediate entangled region, and initially generated wake bundle. The air loads and simulated wake geometries in the radial and axial directions agree well with those obtained using a prescribed wake method for a one blade rotor, and with the experimental data for a two blade rotor. This agreement can be obtained with the correct initial condition of a slowly rotating blade instead of an impulsively rotating blade. The wake geometry and unsteady air loads of helicopter rotor in forward flight is also calculated in forward flight. The rotor blade and wake interaction is critical to vibration and noise problem of the helicopter. Because the computational time of the free vortex blob method is proportional to the square of the element number, the reduction method of computational time is also considered.",
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"content": "Vorticity fields in the wake generated by rotating blades are calculated using a time accurate, free vortex blob method without a non physical model of the far wake. The computed free wake geometry of single rotor in hover is represented by the three wake regions: well defined tip vortex region, intermediate entangled region, and initially generated wake bundle. The air loads and simulated wake geometries in the radial and axial directions agree well with those obtained using a prescribed wake method for a one blade rotor, and with the experimental data for a two blade rotor. This agreement can be obtained with the correct initial condition of a slowly rotating blade instead of an impulsively rotating blade. The wake geometry and unsteady air loads of helicopter rotor in forward flight is also calculated in forward flight. The rotor blade and wake interaction is critical to vibration and noise problem of the helicopter. Because the computational time of the free vortex blob method is proportional to the square of the element number, the reduction method of computational time is also considered.",
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"Aerospace Propulsion Numerical Simulations Wake Structure Rotating Blades Time Marching Free Vortex Blob Method Vorticity Fields Free Wake Geometry Hover Tip Vortex Region Intermediate Entangled Region Initially Generated Wake Bundle Air Loads Simulated Wake Geometries Axial Directions Radial Directions One Blade Rotor Two Blade Rotor Slowly Rotating Blade Unsteady Air Loads Helicopter Rotor Forward Flight"
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{
"affiliation": "Dept. of Aerosp. Eng., Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea",
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"title": "Optimal Threshold and LoG Based Feature Identification and Tracking of Bat Flapping Flight",
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"abstract": "Flapping flight observed in bats offers a promising model for bio-inspiration of small air vehicles because of their high maneuverability, load carrying capacity, and energy efficiency. However, the flight mechanics of bats is very complex due to the highly articulated wing skeleton and the anisotropic, internally-actuated wing membrane. As a result of these complexities, the shape of bat wings can deform quickly and substantially which causes periodic occlusions and large baseline nonlinear deformations of point trajectories in image space. Tracking these points in image space is difficult because the resolution of the images (720 1280) and the frame rate (120Hz) used in these experiments are substantially lower than those used historically. This paper presents a computational approach that utilizes a novel combination of Laplacian-of-Gaussian (LoG) filtering and optimal threshold segmentation to locate markers in images. Using images from 32 cameras, our technique achieved an average hit rate of 83%, with an average false rate of 12%. Our algorithm is shown to perform better than other techniques, including those based on SIFT or LoG filtering alone. In addition to the improved feature detection algorithm, optical flow based tracking is bootstrapped with a spatially recursive unscented Kalman filter to track the identified points during state estimation. The spatially recursive estimator returns as many or more correct correspondences when compared to the standard unscented Kalman filter.",
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"content": "Flapping flight observed in bats offers a promising model for bio-inspiration of small air vehicles because of their high maneuverability, load carrying capacity, and energy efficiency. However, the flight mechanics of bats is very complex due to the highly articulated wing skeleton and the anisotropic, internally-actuated wing membrane. As a result of these complexities, the shape of bat wings can deform quickly and substantially which causes periodic occlusions and large baseline nonlinear deformations of point trajectories in image space. Tracking these points in image space is difficult because the resolution of the images (720 1280) and the frame rate (120Hz) used in these experiments are substantially lower than those used historically. This paper presents a computational approach that utilizes a novel combination of Laplacian-of-Gaussian (LoG) filtering and optimal threshold segmentation to locate markers in images. Using images from 32 cameras, our technique achieved an average hit rate of 83%, with an average false rate of 12%. Our algorithm is shown to perform better than other techniques, including those based on SIFT or LoG filtering alone. In addition to the improved feature detection algorithm, optical flow based tracking is bootstrapped with a spatially recursive unscented Kalman filter to track the identified points during state estimation. The spatially recursive estimator returns as many or more correct correspondences when compared to the standard unscented Kalman filter.",
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"fullName": "Hui Chen",
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"proceeding": {
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"title": "2017 IEEE Pacific Visualization Symposium (PacificVis)",
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"title": "In situ magnetic flux vortex visualization in time-dependent Ginzburg-Landau superconductor simulations",
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"abstract": "We present an in situ visualization framework to capture comprehensive details of vortex dynamics in superconductor simulations. Vortices, which determine all electromagnetic properties of type-II superconductors, are extracted and tracked at the same time with GPU-based time-dependent Ginzburg-Landau superconductor simulations. The in situ workflow involves three parts: (1) a tightly coupled GPU-accelerated algorithm that detects primitives for ambiguity-free vortex tracking, (2) a loosely coupled task-parallel feature-tracking method, and (3) a web-based remote visualization tool for vortex dynamics analysis. Our design minimizes the data movement and storage, maximizes the resource utilization, and reduces the slowdown of the simulation. Our solution captures all vortex dynamics in the simulation, previously impossible with traditional post hoc methods. We also demonstrate in situ visualization cases that help scientists understand how vortices cut each other and recombine into new vortices, which are directly related to energy dissipation of superconducting materials.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present an in situ visualization framework to capture comprehensive details of vortex dynamics in superconductor simulations. Vortices, which determine all electromagnetic properties of type-II superconductors, are extracted and tracked at the same time with GPU-based time-dependent Ginzburg-Landau superconductor simulations. The in situ workflow involves three parts: (1) a tightly coupled GPU-accelerated algorithm that detects primitives for ambiguity-free vortex tracking, (2) a loosely coupled task-parallel feature-tracking method, and (3) a web-based remote visualization tool for vortex dynamics analysis. Our design minimizes the data movement and storage, maximizes the resource utilization, and reduces the slowdown of the simulation. Our solution captures all vortex dynamics in the simulation, previously impossible with traditional post hoc methods. We also demonstrate in situ visualization cases that help scientists understand how vortices cut each other and recombine into new vortices, which are directly related to energy dissipation of superconducting materials.",
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"normalizedAbstract": "We present an in situ visualization framework to capture comprehensive details of vortex dynamics in superconductor simulations. Vortices, which determine all electromagnetic properties of type-II superconductors, are extracted and tracked at the same time with GPU-based time-dependent Ginzburg-Landau superconductor simulations. The in situ workflow involves three parts: (1) a tightly coupled GPU-accelerated algorithm that detects primitives for ambiguity-free vortex tracking, (2) a loosely coupled task-parallel feature-tracking method, and (3) a web-based remote visualization tool for vortex dynamics analysis. Our design minimizes the data movement and storage, maximizes the resource utilization, and reduces the slowdown of the simulation. Our solution captures all vortex dynamics in the simulation, previously impossible with traditional post hoc methods. We also demonstrate in situ visualization cases that help scientists understand how vortices cut each other and recombine into new vortices, which are directly related to energy dissipation of superconducting materials.",
"fno": "08031581",
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{
"affiliation": "Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, USA",
"fullName": "Hanqi Guo",
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"affiliation": "Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, USA",
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{
"affiliation": "Materials Science Division, Argonne National Laboratory, Lemont, IL, USA",
"fullName": "Andreas Glatz",
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{
"proceeding": {
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"title": "Electronics, Robotics and Automotive Mechanics Conference",
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"doi": "10.1109/CERMA.2011.36",
"title": "Vortex Swarm Path Planning Algorithm",
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"abstract": "This paper presents an algorithm for trajectory planing using potential fields and swarms with vortex behavior. This algorithm is called Vortex Swarm Path Planning Algorithm (VSPP). There are several methods for trajectory planning in robotics, the most popular is the one based on artificial potential fields. However this method has the disadvantage of local minima which can make the robot fail when reaching the destination point. The proposed algorithm here presented employs a model of active Brownian particles with vortex behavior that allows the trajectory planning evading local minima.",
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"abstract": "In this paper, a new method for multiresolution volume representation is presented. The method is based on wavelets and it can be used for representing volumetric data defined on non structured grids. The basic contribution is the extension of wavelets to volumetric domains of arbitrary topological type. This extension is made by constructing a wavelet basis defined on any tetrahedrized volume. This basis construction is achieved using multiresolution analysis and lifting scheme.",
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"content": "In this paper, a new method for multiresolution volume representation is presented. The method is based on wavelets and it can be used for representing volumetric data defined on non structured grids. The basic contribution is the extension of wavelets to volumetric domains of arbitrary topological type. This extension is made by constructing a wavelet basis defined on any tetrahedrized volume. This basis construction is achieved using multiresolution analysis and lifting scheme.",
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"affiliation": "University Nac. Del Sur",
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"abstract": "Brain image 3D reconstruction and segmentation is one important part of it, and plays a critical role in computer vision of brain, functional analysis in brain and clinical application. The paper illustrates some wide-prevailed 3D reconstruction method applied to brain image and a method of combining ray-casting with segmentation. We describe a method applied to one implementation of space-based segmentation, which shows the region of interest (ROI) that can help clinicians detect and evaluate segmentation.",
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"content": "Brain image 3D reconstruction and segmentation is one important part of it, and plays a critical role in computer vision of brain, functional analysis in brain and clinical application. The paper illustrates some wide-prevailed 3D reconstruction method applied to brain image and a method of combining ray-casting with segmentation. We describe a method applied to one implementation of space-based segmentation, which shows the region of interest (ROI) that can help clinicians detect and evaluate segmentation.",
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"abstract": "An expert consensus survey based on electronic communication of Delphi method is conducted to develop the TCM clinical pathway for acute ischemie stroke. An initial protocol of the clinical pathway is developed based on literature survey and by an internal panel of experts, which forms the basis of the questionnaire of the Delphi survey. The content of the initial questionnaire is classified into two aspects. A national expert panel is called up for the expert consensus by the e-Delphi method. 100% of the panel members replied in the first round, and only 3 members missed in the second round. The total authority coefficient (Cr) is 0.84 and the Kendall's W for coordination is kept below 0.5 in all domains. In conclusion, we believe the finalized version of the clinical pathway developed by Delphi method in the study is reliable and feasible for the clinical TCM and IM management of acute ischemie stroke.",
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"content": "An expert consensus survey based on electronic communication of Delphi method is conducted to develop the TCM clinical pathway for acute ischemie stroke. An initial protocol of the clinical pathway is developed based on literature survey and by an internal panel of experts, which forms the basis of the questionnaire of the Delphi survey. The content of the initial questionnaire is classified into two aspects. A national expert panel is called up for the expert consensus by the e-Delphi method. 100% of the panel members replied in the first round, and only 3 members missed in the second round. The total authority coefficient (Cr) is 0.84 and the Kendall's W for coordination is kept below 0.5 in all domains. In conclusion, we believe the finalized version of the clinical pathway developed by Delphi method in the study is reliable and feasible for the clinical TCM and IM management of acute ischemie stroke.",
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"title": "2022 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)",
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"title": "Pneumothorax segmentation of chest X-rays using improved UNet++",
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"abstract": "Pneumothorax is a life-threatening medical emergency that results in a state of pneumoperitoneum in the chest due to the entry of gas into the pleural cavity. Pneumothorax usually overlaps with tissues such as ribs and clavicles, which are usually difficult to identify on chest X-rays and have a large clinical underdiagnosis. In recent years, breakthroughs have been achieved in many medical image segmentation tasks using deep learning methods. However, the blurred boundary and tissue overlap in chest X-ray pneumothorax segmentation make it difficult for many algorithms to achieve better results in pneumothorax segmentation. To address these problems, we propose a deep learning network ResNeSt-UNet++ based on UNet++ and ResNeSt. In detail, ResNeSt-UNet++ designs a context-aware feature encoder with residual blocks to extract multi-scale features and introduces hybrid jump paths to obtain and fuse image features at different scales. Moreover, the ResNeSt- UNet++ network uses spatial and channel squeezes and excitation (scSE) modules as decoders to refine. Further, ResNeSt-UNet++ defines a loss function based on Binary Cross Entropy to train the network. The Dice similarity coefficient values and IOUs obtained using this method on the X-ray pneumothorax dataset are 88.31% and 83.1%, respectively, which achieve better performance in pneumothorax segmentation compared with networks such as traditional FPN and UNet++. The experimental results show that this method can segment X-ray pneumothorax with high accuracy and help doctors to provide a reference for accurate judgment of X-ray pneumothorax.",
"abstracts": [
{
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"content": "Pneumothorax is a life-threatening medical emergency that results in a state of pneumoperitoneum in the chest due to the entry of gas into the pleural cavity. Pneumothorax usually overlaps with tissues such as ribs and clavicles, which are usually difficult to identify on chest X-rays and have a large clinical underdiagnosis. In recent years, breakthroughs have been achieved in many medical image segmentation tasks using deep learning methods. However, the blurred boundary and tissue overlap in chest X-ray pneumothorax segmentation make it difficult for many algorithms to achieve better results in pneumothorax segmentation. To address these problems, we propose a deep learning network ResNeSt-UNet++ based on UNet++ and ResNeSt. In detail, ResNeSt-UNet++ designs a context-aware feature encoder with residual blocks to extract multi-scale features and introduces hybrid jump paths to obtain and fuse image features at different scales. Moreover, the ResNeSt- UNet++ network uses spatial and channel squeezes and excitation (scSE) modules as decoders to refine. Further, ResNeSt-UNet++ defines a loss function based on Binary Cross Entropy to train the network. The Dice similarity coefficient values and IOUs obtained using this method on the X-ray pneumothorax dataset are 88.31% and 83.1%, respectively, which achieve better performance in pneumothorax segmentation compared with networks such as traditional FPN and UNet++. The experimental results show that this method can segment X-ray pneumothorax with high accuracy and help doctors to provide a reference for accurate judgment of X-ray pneumothorax.",
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"normalizedAbstract": "Pneumothorax is a life-threatening medical emergency that results in a state of pneumoperitoneum in the chest due to the entry of gas into the pleural cavity. Pneumothorax usually overlaps with tissues such as ribs and clavicles, which are usually difficult to identify on chest X-rays and have a large clinical underdiagnosis. In recent years, breakthroughs have been achieved in many medical image segmentation tasks using deep learning methods. However, the blurred boundary and tissue overlap in chest X-ray pneumothorax segmentation make it difficult for many algorithms to achieve better results in pneumothorax segmentation. To address these problems, we propose a deep learning network ResNeSt-UNet++ based on UNet++ and ResNeSt. In detail, ResNeSt-UNet++ designs a context-aware feature encoder with residual blocks to extract multi-scale features and introduces hybrid jump paths to obtain and fuse image features at different scales. Moreover, the ResNeSt- UNet++ network uses spatial and channel squeezes and excitation (scSE) modules as decoders to refine. Further, ResNeSt-UNet++ defines a loss function based on Binary Cross Entropy to train the network. The Dice similarity coefficient values and IOUs obtained using this method on the X-ray pneumothorax dataset are 88.31% and 83.1%, respectively, which achieve better performance in pneumothorax segmentation compared with networks such as traditional FPN and UNet++. The experimental results show that this method can segment X-ray pneumothorax with high accuracy and help doctors to provide a reference for accurate judgment of X-ray pneumothorax.",
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"authors": [
{
"affiliation": "Southwest University of Science and Technology,Department of electronic information,Mianyang,China",
"fullName": "Xing Zhang",
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"affiliation": "Southwest University of Science and Technology,School of Computer Science and Technology,Mianyang,China",
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"affiliation": "Southwest University of Science and Technology,School of Computer Science and Technology,Mianyang,China",
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"abstract": "Abstract: In this paper, we present a new volume visualization scheme-context based volume visualization to assist the surgeon in surgical planning. This visualization scheme differs from ordinary surface based rendering and volume rendering by providing a frame work to combine surface based rendering and volume rendering. We can achieve the powerful manipulating capability of surface based rendering and good rendering effect as volume rendering in the same time. Using a special data structured-segment tree to mange the visualization scene, which includes all the volume objects and graphics objects (the surgical tools) needed to be visualized, this visualization scheme provides a common context based interface for both graphics objects and volume objects, through which, we can control graphics and volume objects easily in the same way. The context based visualization scheme can greatly increase the performance of volume visualization by generating the scene much faster through selectively revisualizing the affected objects. Based on these ideas, we implement an interactive surgical planning system-Virtual Doctor based on OpenGL 1.1 on WinNT platform and VolumePro vg500 card. This system is a good 3D volume visualization tool and augmented reality system for interactive surgical planning and further research in this area.",
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"abstract": "Workflow is a set of tasks which are systematized to achieve certain business goal(s), where the tasks run in a particular order under automatic control. Artifacts, collections of data items, are necessary for task (process) executions in a workflow. However, an execution may yield unexpected results due to improper artifact manipulation: e.g., activities miss artifact or artifact conflict occur at an activity dynamically. Therefore, the analyses on artifact usage in design phase are very important for quality insurance. This paper presents a model of artifact flow diagrams to state the artifact usage anomalies in processes transmitting artifacts based on DCDC, Distinct Control and Data Channel, model. There are four types of artifact usage anomalies identified in DCDC and the formal statement of each anomaly is described correspondingly for future study of anomaly search.",
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"title": "ICPR 2008 19th International Conference on Pattern Recognition",
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"title": "A practical method to reducing metal artifact for dental CT scanners",
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"abstract": "An integrated and effective metal artifact reduction method named Metal Erasing (ME) especially suited to dental applications is proposed. Layout of metals is identified as metal-only tomogram, using its characteristics of X-ray opacity and simple image processing technique of binarization together with backward projection. Metal-only sinogram is calculated by forward projection of the metal-only tomogram, and identifies corrupted areas on the original sinogram. The areas are then replaced by interpolation, and filtered back projection (FBP) produces a tomogram without figures of metals. The metals can be reproduced by overlaying already obtained metal-only tomogram utilizing linear characteristics of FBP. It is expected that the ME method can be incorporated into commercial CT scanners easily with reasonable computational overhead.",
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"content": "An integrated and effective metal artifact reduction method named Metal Erasing (ME) especially suited to dental applications is proposed. Layout of metals is identified as metal-only tomogram, using its characteristics of X-ray opacity and simple image processing technique of binarization together with backward projection. Metal-only sinogram is calculated by forward projection of the metal-only tomogram, and identifies corrupted areas on the original sinogram. The areas are then replaced by interpolation, and filtered back projection (FBP) produces a tomogram without figures of metals. The metals can be reproduced by overlaying already obtained metal-only tomogram utilizing linear characteristics of FBP. It is expected that the ME method can be incorporated into commercial CT scanners easily with reasonable computational overhead.",
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"Dentistry",
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"Interpolation",
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"Dental Applications",
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"Image Processing",
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"Interpolation",
"Filtered Back Projection",
"Linear Characteristics",
"Dentistry",
"Computed Tomography",
"Interpolation",
"Reconstruction Algorithms",
"X Ray Imaging",
"Research And Development",
"Image Processing",
"Implants",
"Teeth",
"Biological Materials"
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"abstract": "The increasing use of computed tomography (CT) as a diagnostic tool creates the need for an efficient means of evaluating the performance of the CT systems now in use. Usually the metal products have the defects during manufacturing and are inevitable. In the NDT system, ability for evaluate the casting defects such as cracks and pores is also very important. In the present study, several phantoms were made for evaluating CT system and defect analysis tools. The phantoms were CT scanned, and the result of CT scan was discussed. For the accuracy matters, measurements were made and compared with real objects. It is expected that phantoms used in the present study help to validate defect detection softwares.",
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"abstract": "Computed tomography (CT) is an imaging modality widely used for medical diagnosis and treatment. CT images are often corrupted by undesirable artifacts when metallic implants are carried by patients, which creates the problem of metal artifact reduction (MAR). Existing methods for reducing the artifacts due to metallic implants are inadequate for two main reasons. First, metal artifacts are structured and non-local so that simple image domain enhancement approaches would not suffice. Second, the MAR approaches which attempt to reduce metal artifacts in the X-ray projection (sinogram) domain inevitably lead to severe secondary artifact due to sinogram inconsistency. To overcome these difficulties, we propose an end-to-end trainable Dual Domain Network (DuDoNet) to simultaneously restore sinogram consistency and enhance CT images. The linkage between the sigogram and image domains is a novel Radon inversion layer that allows the gradients to back-propagate from the image domain to the sinogram domain during training. Extensive experiments show that our method achieves significant improvements over other single domain MAR approaches. To the best of our knowledge, it is the first end-to-end dual-domain network for MAR.",
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"content": "Computed tomography (CT) is an imaging modality widely used for medical diagnosis and treatment. CT images are often corrupted by undesirable artifacts when metallic implants are carried by patients, which creates the problem of metal artifact reduction (MAR). Existing methods for reducing the artifacts due to metallic implants are inadequate for two main reasons. First, metal artifacts are structured and non-local so that simple image domain enhancement approaches would not suffice. Second, the MAR approaches which attempt to reduce metal artifacts in the X-ray projection (sinogram) domain inevitably lead to severe secondary artifact due to sinogram inconsistency. To overcome these difficulties, we propose an end-to-end trainable Dual Domain Network (DuDoNet) to simultaneously restore sinogram consistency and enhance CT images. The linkage between the sigogram and image domains is a novel Radon inversion layer that allows the gradients to back-propagate from the image domain to the sinogram domain during training. Extensive experiments show that our method achieves significant improvements over other single domain MAR approaches. To the best of our knowledge, it is the first end-to-end dual-domain network for MAR.",
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"abstract": "Metal artifact reduction (MAR) methods are continuously used for minimizing artifacts in Computed Tomography (CT/CAT scans) and although they are largely used, there is a lack of suggestions to evaluate such methods (especially the interpolation-based ones). In this paper, we propose an approach for assessment of a MAR method based on interpolation techniques. We have used four interpolation techniques, evaluating their performances in two different scenarios: an artificial image simulation for quantitative assessment, and one real image for qualitative assessment. We have adopted the Sinogram Completion method, widely used for metal artifact reduction. The linear interpolation had presented better results in comparison to other interpolation techniques in both scenarios. The MAR method (Sinogram Completion) associated to the linear interpolation technique presents the most efficient results, which justifies the current researchers' interest in this particular technique.",
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"affiliation": "Center of Strategic Health Technologies, State University of Paraiba,Campina Grande,PB,Brasil",
"fullName": "Jose Alberto Souza Paulino",
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"abstract": "With the increasing security threats from infrastructure attacks such as worms and distributed denial of service attacks, it is clear that the cooperation among different organizations is necessary to defend against these attacks. However, organizations? privacy concerns for the incident and security alert data require that sensitive data be sanitized before they are shared with other organizations. Such sanitization process usually has negative impacts on intrusion analysis (such as alert correlation). To balance the privacy requirements and the need for intrusion analysis, we propose a privacy-preserving alert correlation approach based on concept hierarchies. Our approach consists of two phases. The first phase is entropy guided alert sanitization, where sensitive alert attributes are generalized to high-level concepts to introduce uncertainty into the dataset with partial semantics. To balance the privacy and the usability of alert data, we propose to guide the alert sanitization process with the entropy or differential entropy of sanitized attributes. The second phase is sanitized alert correlation. We focus on defining similarity functions between sanitized attributes and building attack scenarios from sanitized alerts. Our preliminary experimental results demonstrate the effectiveness of the proposed techniques.",
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"abstract": "Privacy Preserving Data Mining (PPDM) has become a popular topic in the research community. How to strike a balance between privacy protection and knowledge discovery in the sharing process is an important issue. This study focuses on Privacy Preserving Utility Mining (PPUM) and presents two novel algorithms, HHUIF and MSICF, to achieve the goal of hiding sensitive itemsets so that the adversaries can not mine them from the modified database. In addition, we minimize the impact on the sanitized database in the process of hiding sensitive itemsets. The experimental results show that HHUIF achieves the lower miss costs than MSICF does on two synthetic datasets. On the other hand, MSICF generally has the lower difference between the original and sanitized databases than HHUIF does.",
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"abstract": "Two tasks in Graph Visualization require partitioning: the assignment of visual attributes and divisive clustering. Often, we would like to assign a color or other visual attributes to a node or edge that indicates an associated value. In an application involving divisive clustering, we would like to partition the graph into subsets of graph elements based on metric values in such a way that all subsets are evenly populated. Assuming a uniform distribution of metric values during either partitioning or coloring can have undesired effects such as empty clusters or only one level of emphasis for the entire graph. Probability density functions derived from statistics about a metric can help systems succeed at these tasks.",
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"content": "Notice of Violation of IEEE Publication Principles \"The Exploration of Web Sites with Link Structure Graphs\" by Jun Yang and Zhigang Tang in Proceedings of the 2009 International Conference on Management of eCommerce and eGovernment, Sept. 2009, pp. 209-212 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article: \"Link Structure Graphs for Representing and Analyzing Web Sites,\" by Eduarda Mendes Rodrigues, Natasa Milic-Frayling, Martin Hicks, Gavin Smyth, in Microsoft Research Technical Report MSR-TR-2006-94, June 2006 ",
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"abstract": "The problem of drawing a graph in the plane so that edges appear as straight lines and the minimum angle formed by any pair of incident edges is maximized is studied. The resolution of a layout is defined to be the size of the minimum angle formed by incident edges of the graph, and the resolution of a graph is defined to be the maximum resolution of any layout of the graph. The resolution R of a graph is characterized in terms of the maximum node degree d of the graph by proving that Omega (1/d/sup 2/)<or=R<or=2 pi /d for any graph. Moreover, it is proved that R= Theta (1/d) for many graphs, including planar graphs, complete graphs, hypercubes, multidimensional meshes and tori, and other special networks. It is also shown that the problem of deciding if R=2 pi /d for a graph is NP-hard for d=4, and a counting argument is used to show that R=O(log d/d/sup 2/) for many graphs.",
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"content": "The problem of drawing a graph in the plane so that edges appear as straight lines and the minimum angle formed by any pair of incident edges is maximized is studied. The resolution of a layout is defined to be the size of the minimum angle formed by incident edges of the graph, and the resolution of a graph is defined to be the maximum resolution of any layout of the graph. The resolution R of a graph is characterized in terms of the maximum node degree d of the graph by proving that Omega (1/d/sup 2/)<or=R<or=2 pi /d for any graph. Moreover, it is proved that R= Theta (1/d) for many graphs, including planar graphs, complete graphs, hypercubes, multidimensional meshes and tori, and other special networks. It is also shown that the problem of deciding if R=2 pi /d for a graph is NP-hard for d=4, and a counting argument is used to show that R=O(log d/d/sup 2/) for many graphs.",
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