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Experimental validation of an OSEM-type iterative reconstruction algorithm for inverse geometry computed tomography

Experimental validation of an OSEM-type iterative reconstruc...

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Conference on Medical Imaging - Physics of Medical Imaging

作者： David, Sabrina Burion, Steve Tepe, Alan Wilfley, Brian Menig, Daniel Funk, Tobias Triple Ring Technol Newark CA USA

ISBN: (纸本)9780819489623

Iterative reconstruction methods have emerged as a promising avenue to reduce dose in CT imaging. Another, perhaps less well-known, advance has been the development of inverse geometry CT (IGCT) imaging systems, which can significantly reduce the radiation dose delivered to a patient during a CT scan compared to conventional CT systems. Here we show that IGCT data can be reconstructed using iterative methods, thereby combining two novel methods for CT dose reduction. A prototype IGCT scanner was developed using a scanning beam digital X-ray system - an inverse geometry fluoroscopy system with a 9,000 focal spot x-ray source and small photon counting detector. 90 fluoroscopic projections or "superviews" spanning an angle of 360 degrees were acquired of an anthropomorphic phantom mimicking a 1 year-old boy. The superviews were reconstructed with a custom iterative reconstruction algorithm, based on the maximum-likelihood algorithm for transmission tomography (ML-TR). The normalization term was calculated based on flat-field data acquired without a phantom. 15 subsets were used, and a total of 10 complete iterations were performed. Initial reconstructed images showed faithful reconstruction of anatomical details. Good edge resolution and good contrast-to-noise properties were observed. Overall, ML-TR reconstruction of IGCT data collected by a bench-top prototype was shown to be viable, which may be an important milestone in the further development of inverse geometry CT.

关键词： Reconstruction algorithms Sensors X-ray computed tomography X-rays Computed tomography detection and tracking algorithms Imaging systems Prototyping X-ray imaging Data acquisition

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detection of Abandoned Mines/Caves Using Airborne LWIR Hyperspectral Data

Detection of Abandoned Mines/Caves Using Airborne LWIR Hyper...

引用

Conference on Imaging Spectrometry XVII

作者： Shen, Sylvia S. Roettiger, Kurt A. Aerosp Corp 15049 Conf Ctr Dr Chantilly VA 20151 USA

ISBN: (纸本)9780819492326

The detection of underground structures, both natural and man-made, continues to be an important requirement in both the military/intelligence and civil communities. There are estimates that as many as 70,000 abandoned mines/caves exist across the nation. These mines represent significant hazards to public health and safety, and they are of concern to Government agencies at the local, state, and federal levels. NASA is interested in the detection of caves on Mars and the Moon in anticipation of future manned space missions. And, the military/intelligence community is interested in detecting caves, mines, and other underground structures that may be used to conceal the production of weapons of mass destruction or to harbor insurgents or other persons of interest by the terrorists. Locating these mines/caves scattered over millions of square miles is an enormous task, and limited resources necessitate the development of an efficient and effective broad area search strategy using remote sensing technologies. This paper describes an internally-funded research project of The Aerospace Corporation (Aerospace) to assess the feasibility of using airborne hyperspectral data to detect abandoned cave/mine entrances in a broad-area search application. In this research, we have demonstrated the potential utility of using thermal contrast between the cave/mine entrance and the ambient environment as a discriminatory signature. We have also demonstrated the use of a water vapor absorption line at 12.55 mu m and a quartz absorption feature at 9.25 mu m as discriminatory signatures. Further work is required to assess the broader applicability of these signatures.

关键词： Mining Long wavelength infrared Absorption Land mines Atmospheric corrections Aerospace engineering detection and tracking algorithms Quartz Sensors Safety

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A Fast Coalescence-Avoiding JPDAF

A Fast Coalescence-Avoiding JPDAF

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Conference on Signal and Data Processing of Small Targets

作者： Romeo, Kevin Crouse, David F. Bar-Shalom, Yaakov Willett, Peter Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819490711

In this paper we present a new algorithm for approximating the target-measurement association probabilities of the Joint Probabilistic Data Association Filter (JPDAF). This algorithm is designed to robustify the JPDAF against track coalescence which can greatly degrade the performance of the JPDAF and other approximate algorithms. It is based on the works of Roecker and the JPDAF* of Blom and Bloem. We compare our new algorithm with the two it is based on, as well as the "cheap JPDAF" and the Set JPDAF, and show that it offers a significant improvement in computational complexity over the JPDAF*, and improvement in tracking error over the Roecker algorithm. We compare their performance with respect to the Mean Optimal Subpattern Assignment (MOSPA) statistic in scenarios involving several closely-spaced targets. A consistency comparison of the various algorithms considered is also presented.

关键词： detection and tracking algorithms Target detection Monte Carlo methods Error analysis Algorithm development Computer simulations Statistical analysis Time metrology Data processing Signal processing

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Deformable Registration of the Inflated and Deflated Lung for Cone-Beam CT-Guided Thoracic Surgery

Deformable Registration of the Inflated and Deflated Lung fo...

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Conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions and Modeling

作者： Uneri, Ali Nithiananthan, Sajendra Schafer, Sebastian Otake, Yoshito Stayman, J. Webster Kleinszig, Gerhard Sussman, Marc S. Taylor, Russell H. Prince, Jerry L. Siewerdsen, Jeffrey H. Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA Johns Hopkins Univ Dept Biomed Engn Baltimore MD 21218 USA Siemens Healthcare Erlangen Germany Johns Hopkins Bayview Med Ctr Dept Surg Baltimore MD 21218 USA Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD 21218 USA

ISBN: (纸本)9780819489654

Intraoperative cone-beam CT (CBCT) could offer an important advance to thoracic surgeons in directly localizing subpalpable nodules during surgery. An image-guidance system is under development using mobile C-arm CBCT to directly localize tumors in the OR, potentially reducing the cost and logistical burden of conventional preoperative localization and facilitating safer surgery by visualizing critical structures surrounding the surgical target (e. g., pulmonary artery, airways, etc.). To utilize the wealth of preoperative image/planning data and to guide targeting under conditions in which the tumor may not be directly visualized, a deformable registration approach has been developed that geometrically resolves images of the inflated (i.e., inhale or exhale) and deflated states of the lung. This novel technique employs a coarse model-driven approach using lung surface and bronchial airways for fast registration, followed by an image-driven registration using a variant of the Demons algorithm to improve target localization to within similar to 1 mm. Two approaches to model-driven registration are presented and compared - the first involving point correspondences on the surface of the deflated and inflated lung and the second a mesh evolution approach. Intensity variations (i.e., higher image intensity in the deflated lung) due to expulsion of air from the lungs are accounted for using an a priori lung density modification, and its improvement on the performance of the intensity-driven Demons algorithm is demonstrated. Preliminary results of the combined model-driven and intensity-driven registration process demonstrate accuracy consistent with requirements in minimally invasive thoracic surgery in both target localization and critical structure avoidance.

关键词： Lung Image registration Surgery Image segmentation detection and tracking algorithms Tumors Visualization Computed tomography Image-guided intervention Lung cancer

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Rotation-Invariant Fast Features for Large-Scale Recognition

Rotation-Invariant Fast Features for Large-Scale Recognition

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Conference on Applications of Digital Image Processing XXXV

作者： Takacs, Gabriel Chandrasekhar, Vijay Tsai, Sam Chen, David Grzeszczuk, Radek Girod, Bernd Nokia Res Ctr Sunnyvale CA USA Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9780819492166

We present an end-to-end feature description pipeline which uses a novel interest point detector and Rotation-Invariant Fast Feature (RIFF) descriptors. The proposed RIFF algorithm is 15x faster than SURF1 while producing large-scale retrieval results that are comparable to SIFT.(2) Such high-speed features benefit a range of applications from Mobile Augmented Reality (MAR) to web-scale image retrieval and analysis.

关键词： Databases detection and tracking algorithms Sensors Image retrieval Feature extraction Image filtering Video Image processing Augmented reality Buildings

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Virtual View Interpolation at Arbitrary View Points for Mixed-Resolution 3D Videos

Virtual View Interpolation at Arbitrary View Points for Mixe...

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Conference on Stereoscopic Displays and Applications XXIII (SD and A)/IS and T/SPIE Electronic Imaging - Science and Technology Symposium

作者： Lee, Seungsin Lee, Seok Wey, Ho-Cheon Park, Du-Sik Samsung Elect Samsung Adv Inst Technol Yongin 446712 South Korea

ISBN: (纸本)9780819489357

For a full motion parallax 3D display, it is necessary to supply multiple views obtained from a series of different locations. However, it is impractical to deliver all of the required views because it will result in a huge size of bit streams. In the previous work, authors proposed a mixed resolution 3D video format composed of color and depth information pairs with heterogeneous resolutions, and also suggested a view synthesis algorithm for mixed resolution videos. This paper reports a more refined view interpolation method and improved results.

关键词： Image resolution Video 3D displays 3D video streaming Image processing Image quality detection and tracking algorithms Video compression Cameras Stereoscopic displays

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Saccadic Eyes Recognition Using 3-D Shape Data from a 3-D Near Infrared Sensor

Saccadic Eyes Recognition Using 3-D Shape Data from a 3-D Ne...

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Conference on Mobile Multimedia/Image Processing, Security, and Applications

作者： Guo, Shenwen Tang, Jinshan Parakkat, Julia B. Robinette, Kathleen M. Alcorn State Univ Dept Adv Technol Alcorn State MS 39096 USA Michigan Technol Univ Sch Technol Houghton MI 49931 USA Air Force Res Lab Human Effectiveness Directorate Vulnerability Analysis Branch Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9780819490841

Saccadic eyes are important human behaviors and have important applications in commercial and security fields. In this paper, we focus on saccadic eyes recognition from 3-D shape data acquired from a 3-D near infrared sensor. Two salient features, normal vectors of meshes and curvatures of surfaces, are extracted. The distributions of normal vectors and curvatures are computed to represent eye states. The support vector machine (SVM) is applied to classify eyes states into saccadic and non-saccadic eyes states. To verify the proposed method, we performed three groups of experiments using different strategies for samples selected from 300 3-D data, and present experimental results that demonstrate the effectiveness and robustness of the proposed algorithm.

关键词： Eye Infrared sensors Near infrared Sensors Facial recognition systems Feature extraction Computer security 3D modeling detection and tracking algorithms Library classification systems

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Distributed pattern detection in cyber networks

Distributed pattern detection in cyber networks

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Conference on Cyber Sensing

作者： Paffenroth, Randy C. Du Toit, Philip C. Scharf, Louis L. Jayasumana, Anura P. Banadara, Vidarshana W. Nong, Ryan Numerica Corp Loveland CO USA Colorado State Univ Ft Collins CO 80523 USA

ISBN: (纸本)9780819490865

In this paper we describe an approach for the detection and classification of weak, distributed patterns in sensor networks. Of course, before one can begin development of a pattern detection algorithm, one must first define the term "pattern", which by nature is a broad and inclusive term. One of the key aspects of our work is a definition of pattern that has already proven effective in detecting anomalies in real world data. While designing detection algorithms for all classes of patterns in all types of networks sounds appealing, this approach would almost certainly require heuristic methods and only cursory statements of performance. Rather, we have specifically studied the problem of intrusion detection in computer networks in which a pattern is an abnormal or unexpected spatio-temporal dependence in the data collected across the nodes. We do not attempt to match an a priori template, but instead have developed algorithms that allow the pattern to reveal itself in the data by way of dependence or independence of observed time series. Although the problem is complex and challenging, recent advances in l(1) techniques for robust matrix completion, compressed sensing, and correlation detection provide promising opportunities for progress. Our key contribution to this body of work is the development of methods that make an accounting of uncertainty in the measurements on which the inferences are based. The performance of our methods will be demonstrated on real world data, including measured data from the Abilene Internet2 network.

关键词： Algorithm development Sensors detection and tracking algorithms Sensor networks Computer networks Matrices Databases Signal detection Compressed sensing Computer intrusion detection

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Driver/passenger discrimination for the interaction with the dual-view touch screen integrated to the automobile centre console

Driver/passenger discrimination for the interaction with the...

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Conference on Image Processing - algorithms and Systems X and Parallel Processing for Imaging Applications II

作者： Herrmann, Enrico Makrushin, Andrey Dittmann, Jana Vielhauer, Claus Otto Von Guericke Univ Univ Pl 2 D-39106 Magdeburg Germany Univ Appl Sci Brandenburg Magdeburg Germany

ISBN: (纸本)9780819489425

In an attempt to further develop and evaluate the optical recognition systems for distinguishing between driver and front-seat passenger during their interactions with dual-view touch screen integrated to the automobile centre console, this work focuses on the enhancement of both image processing algorithms and experimental environment. In addition to the motion based forearm and hand segmentation and the texture based arm direction analysis, the adaptive boosting classifiers with Haar-like features have been engaged for the learning of driver's and passenger's hand patterns. The user discrimination system was completely reproduced in a laboratory, including passenger compartment with genuine dashboard, touch screen, camera and near-infrared lamps, so that different illumination conditions could be modeled. The new acquisition system allows automatic and unambiguous registration of all touch screen interactions and their synchronization with the video stream. This results in credible evaluation of the image processing routines. The adjustment of the camera position and the active infrared illumination made it possible to reduce the recognition error rates and to achieve superior discrimination performance compared to previous works.

关键词： detection and tracking algorithms Video Algorithm development Cameras Image processing Light sources and illumination Lamps Imaging systems Image segmentation Motion analysis

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Co-occurrence steganalysis in high dimensions

Co-occurrence steganalysis in high dimensions

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Conference on Media Watermarking, Security, and Forensics

作者： Pevny, Tomas Czech Tech Univ Agent Technol Ctr Prague 12135 2 Czech Republic

ISBN: (纸本)9780819489500

The state of the art steganalytic features for spatial domain, and to some extent for transfer domains (DCT) as well, are based on histograms of co-occurrence of neighboring elements. The rationale behind is that neighboring pixels in digital images are correlated, which is caused by the smoothness of our world and by the usual image processing. The limitation of the histogram- based features is that they do not scale well with respect to the number of modeled neighboring elements, since the number of histogram bins (hence number of features) depends exponentially on this quality. The remedy adopted by the prior art is to sum values of neighboring bins together, which can be seen as a vector quantization controlled by the position of the quantization centers. so far the quantization centers has been determined manually according to the steganalyst. Here we propose to use Linde, Buso, and Gray algorithm in order to automatically find quantization centers maximizing the detection accuracy of resulting features. The quantization centers found by the proposed algorithm are experimentally compared to the ones used by the prior art in the steganalysis of Hugo algorithm. The results show a non-eligible improvements in the accuracy, especially when more complicated filtes and higher-order histograms are used.

关键词： Neodymium Picosecond phenomena Quantization Steganalysis Current controlled current source detection and tracking algorithms Digital watermarking Electronic imaging Forensic science Image processing

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