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27th image and vision Computing New Zealand conference, IvCNZ 2012

作者： Romaniuk, Barbara Younes, Lara Bittar, Éric Reims University CReSTIC-SIC Lab. Rue des Crayères 51687 Reims Cedex 2 France

ISBN: (纸本)9781450314732

We present the first step of the Rheims city (France) 3D reconstruction based on old postcards. Rheims endured drastic destruction during the First and then the Second World Wars. Old postcards, embodying the period from the beginning to the end of the 20th century, establish a testimony of the evolution in time and space of the most important places and monuments in the city. We aim to localize, render and visualize in 3D the buildings of this city, by using this sparse dataset and incomplete cadastral surveys. image matching is initially required for locating a building in the city space. In this paper we propose a performance comparison of state-of-the-art detector-descriptor couples. We focus on their robustness and their transformations invariance when low resolution data is subject to temporal and space modifications. © 2012 ACM.

关键词： image matching

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EM reconstruction of Dual Isotope PET with Staggered Injections and Prompt Gamma Positron Emitters

EM Reconstruction of Dual Isotope PET with Staggered Injecti...

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IEEE Nuclear Science Symposium / Medical Imaging conference Record (NSS/MIC) / 19th Room-Temperature Semiconductor X-ray and Gamma-ray Detector Workshop

作者： Andreyev, Andriy Sitek, Arkadiusz Celler, Anna Univ British Columbia Med Imaging Res Grp Vancouver BC V5Z 1M9 Canada Brigham & Womens Hosp Harvard Med Sch Dept Radiol Boston MA 02115 USA

ISBN: (纸本)9781467320306;9781467320283

The aim of Dual Isotope Positron Emission Tomography (DIPET) is to create two independent images of two co-injected radiotracers. DIPET shortens the duration of the study, reduces patient discomfort and produces perfectly co-registered images. Its implementation is difficult because positron decay of any isotope creates only 511 kev photons. Recently, we have proposed a DIPET technique that uses a combination of radiotracer A which is a pure positron emitter (such as F-18 or C-11) and radiotracer B in which positron decay is followed by the emission of a high-energy (HE) prompt gamma (such as K-38 or Cu-60). Events that are detected as triple coincidences of HE gammas with the corresponding two 511 kev photons identify the line-of-responses (LORs) that originate from isotope B (similar to 10% of all events). These LORs are used to separate the two intertwined distributions, using a dedicated image reconstruction algorithm based on Expectation Maximization (EM). However, this approach is suboptimal as it combines high-statistics data (radiotracers A and B), with low-statistics (radiotracer B) to create separate images of radiotracers A and B. We hypothesize that from the performance of DIPET could be improved if an independent estimate of radiotracer A distribution is available by using staggered injections method. Here we investigate this hypothesis by developing and testing an EM-based algorithm for image reconstruction of such data. Our algorithm is general, i.e. can reconstruct staggered data, positron and HE gamma data or a combination of both. reconstruction of DIPET data obtained from Monte-Carlo simulations shows that the combined method provides the best results in terms of separation of images corresponding to radiotracers A and B. Our EM algorithm provides not only good image separation for the combined method but also when only staggered injections or only prompt gamma data are used.

关键词： Monte Carlo methods expectation-maximisation algorithm image reconstruction medical image processing positron emission tomography

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Extraction of blood droplet flight trajectories from videos for forensic analysis

Extraction of blood droplet flight trajectories from videos ...

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1st International conference on Pattern Recognition Applications and Methods, ICPRAM 2012

作者： Zarrabeitia, L.A. Aruliah, D.A. Qureshi, F.Z. Faculty of Science University of Ontario Institute of Technology Oshawa ON Canada

ISBN: (纸本)9789898425980

We present a method for extracting three-dimensional flight trajectories of liquid droplets from video data. A high-speed stereo camera pair records videos of experimental reconstructions of projectile impacts and ensuing droplet scattering. After background removal and segmentation of individual droplets in each video frame, we introduce a model-based matching technique to accumulate image paths for individual droplets. Our motion detection algorithm is designed to deal gracefully with the lack of feature points, with the similarity of droplets in shape, size, and color, and with incomplete droplet paths due to noise, occlusions, etc. The final reconstruction algorithm pairs two-dimensional paths accumulated from each of the two cameras'videos to reconstruct trajectories in three dimensions. The reconstructed droplet trajectories constitute a starting point for a physically accurate model of blood droplet flight for forensic bloodstain pattern analysis.

关键词： image reconstruction

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SPECT Imaging With Resolution Recovery

SPECT Imaging With Resolution Recovery

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2nd International conference on Advancements in Nuclear Instrumentation, Measurement Methods and their Applications

作者： Bronnikov, Andrei v. Bronnikov Algorithms NL-6800 AB Arnhem Netherlands

ISBN: (纸本)9781457709258

Single-photon emission computed tomography (SPECT) is a method of choice for imaging spatial distributions of radioisotopes. Applications of this method are found in medicine, biomedical research and nuclear industry. This paper deals with improving spatial resolution in SPECT by applying correction for the point-spread function (PSF) in the reconstruction algorithm and optimizing the collimator. Several approaches are considered: the use of a depth-dependent PSF model for a parallel-beam collimator derived from experimental data, the extension of this model to a fan-beam collimator, a triangular approximation of the PSF for reconstruction acceleration, and a method for optimal fan-beam collimator design. An unmatched projector/backprojector ordered subsets expectation maximization (OSEM) algorithm is used for image reconstruction. Experimental results with simulated and physical phantom data of a micro-SPECT system show a significant improvement of spatial resolution with the proposed methods.

关键词： image quality nuclear medicine single photon emission computed tomography (SPECT)

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A robust multi-scale integration method to obtain the depth from gradient maps

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COMPUTER vISION AND image UNDERSTANDING 2012年第8期116卷 882-895页

作者： Saracchini, Rafael F. v. Stolfi, Jorge Leitao, Helena C. G. Atkinson, Gary A. Smith, Melvyn L. Univ Estadual Campinas Inst Comp Campinas SP Brazil Univ Fed Fluminense Inst Comp BR-24220000 Niteroi RJ Brazil Univ W England Machine Vis Lab Bristol BS16 1QY Avon England

We describe a robust method for the recovery of the depth map (or height map) from a gradient map (or normal map) of a scene, such as would be obtained by photometric stereo or interferometry. Our method allows for uncertain or missing samples, which are often present in experimentally measured gradient maps, and also for sharp discontinuities in the scene's depth, e.g. along object silhouette edges. By using a multi-scale approach, our integration algorithm achieves linear time and memory costs. A key feature of our method is the allowance for a given weight map that flags unreliable or missing gradient samples. We also describe several integration methods from the literature that are commonly used for this task. Based on theoretical analysis and tests with various synthetic and measured gradient maps, we argue that our algorithm is as accurate as the best existing methods, handling incomplete data and discontinuities, and is more efficient in time and memory usage, especially for large gradient maps. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Computer vision Multi-scale methods Gradient map integration Surface reconstruction

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Improvements in image Quality When Using Patient Outline Constraints with a Generalized Scatter PET reconstruction Algorithm

Improvements in Image Quality When Using Patient Outline Con...

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IEEE Nuclear Science Symposium / Medical Imaging conference Record (NSS/MIC) / 19th Room-Temperature Semiconductor X-ray and Gamma-ray Detector Workshop

作者： Sun, Hongyan Pistorius, Stephen Univ Manitoba Winnipeg MB R3E 0V9 Canada

ISBN: (纸本)9781467320306;9781467320283

Scattered coincidences degrade image contrast and compromise quantitative accuracy in Positron Emission Tomography (PET). A number of approaches for estimating and correcting scattered coincidences have been proposed, but most of them are based on estimating and subtracting a scatter sinogram from the measured data. We have previously shown that both true and scattered coincidences can be treated similarly by using Compton scattering kinematics to define a locus of scattering which may in turn be used to reconstruct the activity using a Generalized Scatter Maximum-likelihood Expectation-Maximization (GS-MLEM) algorithm. The annihilation position can be further confined by taking advantage of the patient outline (or a geometrical shape that encompasses the patient outline). The proposed method was tested on a phantom generated using GATE based Monte Carlo simulation. The results have shown that for scatter fractions of 10 to 60% this algorithm improves the Contrast Recovery Coefficients (CRC) by 4.0 to 28.6% for a hot source and 5.1 to 40% for a cold source while the Relative Standard Deviation (RSD) was reduced. Including scattered photons directly into the reconstruction eliminates the need for (often empirical) scatter corrections and increases the system's sensitivity and image contrast. This could be used to either improve the diagnostic quality and/or to reduce patient dose and radiopharmaceutical cost.

关键词： Monte Carlo methods image reconstruction maximum likelihood estimation medical image processing phantoms positron emission tomography

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Predicting image popularity in an incomplete social media community by a weighted bi-partite graph

Predicting image popularity in an incomplete social media co...

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2012 13th IEEE International conference on Multimedia and Expo, ICME 2012

作者： Niu, Xiang Li, Lusong Mei, Tao Shen, Jialie Xu, Ke Beihang University Beijing China National University of Singapore Singapore Singapore Microsoft Research Asia Beijing China Singapore Management University Singapore Singapore

ISBN: (纸本)9781467316590

Popularity prediction is a key problem in networks to analyze the information diffusion, especially in social media communities. Recently, there have been some custom-build prediction models in Digg and YouTube. However, these models are hardly transplant to an incomplete social network site (e.g., Flickr) by their unique parameters. In addition, because of the large scale of the network in Flickr, it is difficult to get all of the photos and the whole network. Thus, we are seeking for a method which can be used in such incomplete network. Inspired by a collaborative filtering method - Network-based Inference (NBI), we devise a weighted bipartite graph with undetected users and items to represent the resource allocation process in an incomplete network. Instead of image analysis, we propose a modified interdisciplinary models, called incomplete Network-based Inference (INI). Using the data from 30 months in Flickr, we show the proposed INI is able to increase prediction accuracy by over 58.1%, compared with traditional NBI. We apply our proposed INI approach to personalized advertising application and show that it is more attractive than traditional Flickr advertising. © 2012 IEEE.

关键词： Marketing

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DECA: Recovering fields of physical quantities from incomplete sensory data

DECA: Recovering fields of physical quantities from incomple...

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2012 9th Annual IEEE Communications Society conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2012

作者： Xiang, Liu Luo, Jun Deng, Chenwei vasilakos, Athanasios v. Lin, Weisi School of Computer Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Technical University Athens Greece

ISBN: (纸本)9781467319058

Although wireless sensor networks (WSNs) are powerful in monitoring physical events, the data collected from a WSN are almost always incomplete if the surveyed physical event spreads over a wide area. The reason for this incompleteness is twofold: i) insufficient network coverage and ii) data aggregation for energy saving. Whereas the existing recovery schemes only tackle the second aspect, we develop Dual-lEvel Compressed Aggregation (DECA) as a novel framework to address both aspects. Specifically, DECA allows a high fidelity recovery of a widespread event, under the situations that the WSN only sparsely covers the event area and that an in-network data aggregation is applied for traffic reduction. Exploiting both the low-rank nature of real-world events and the redundancy in sensory data, DECA combines matrix completion with a fine-tuned compressed sensing technique to conduct a dual-level reconstruction process. We demonstrate that DECA can recover a widespread event with less than 5% of the data (with respect to the dimension of the event) being collected. Performance evaluation based on both synthetic and real data sets confirms the recovery fidelity and energy efficiency of our DECA framework. © 2012 IEEE.

关键词： Wireless sensor networks

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Social image tagging by mining sparse tag patterns from auxiliary data

Social image tagging by mining sparse tag patterns from auxi...

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2012 13th IEEE International conference on Multimedia and Expo, ICME 2012

作者： Lin, Jie Yuan, Junsong Duan, Ling-Yu Luo, Siwei Gao, Wen School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China Institute of Digital Media School of EE and CS Peking University Beijing 100871 China School of EEE Nanyang Technological University 639798 Singapore Singapore

ISBN: (纸本)9781467316590

User-given tags associated with social images from photo-sharing websites (e.g., Flickr) are valuable auxiliary resources for the image tagging task. However, social images often suffer from noisy and incomplete tags, heavily degrading the effectiveness of previous image tagging approaches. To alleviate the problem, we introduce a Sparse Tag Patterns (STP) model to discover noiseless and complementary co-occurrence tag patterns from large scale user contributed tags among auxiliary web data. To fulfill the compactness and discriminability, we formulate the STP model as a problem of minimizing quadratic loss function regularized by bi-layer $l-1$ norm. We treat the learned STP as a universal knowledge base and verify its superiority within a data-driven image tagging framework. Experimental results over 1 million auxiliary data demonstrate superior performance of the proposed method compared to the state-of-the-art. © 2012 IEEE.

关键词： Knowledge based systems

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Comparison of Two Small Animal PET Scanners: Pinhole Collimation vs. Electronic Collimation

Comparison of Two Small Animal PET Scanners: Pinhole Collima...

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IEEE Nuclear Science Symposium / Medical Imaging conference Record (NSS/MIC) / 19th Room-Temperature Semiconductor X-ray and Gamma-ray Detector Workshop

作者： Walker, Matthew D. Ramakers, Ruud M. Blinder, Stephan Dinelle, Katherine Shirmohammad, Maryam van der Have, Frans Goorden, Marlies C. Beekman, Freek J. Sossi, vesna Univ British Columbia Vancouver BC V6T 2B5 Canada MILabs Utrecht Netherlands Delft Univ Technol Delft Netherlands

ISBN: (纸本)9781467320306;9781467320283

PET imaging of rodents is increasingly used in preclinical research, but its utility is limited by the spatial resolution and statistical quality of the images. In a new approach, a specially designed pinhole collimator enables high-resolution, simultaneous imaging of PET and SPECT tracers. Such a physical collimation technique strongly departs from traditional electronic collimation achieved via coincidence detection in PET. This work compares two small animal PET scanners, one with electronic collimation (FocusI20) and one with physical collimation using clustered pinholes (vECTor). data were compared from Jaszczak (hot-rod) and uniform phantoms and point source measurements. Mouse brain images from [F-18]FDG PET were acquired on both systems, and compared with quantitative ex-vivo autoradiography as a gold standard. Using typical reconstruction settings, the pinhole system resolved the smallest rods (0.85 mm diameter) in the Jaszczak phantom while the coincidence system resolved 1.3 mm diameter rods. This was in agreement with the recovered contrast. The contrast-to-noise ratio was better for the pinhole system when imaging small rods <1.1 mm) for a wide range of activity levels, but this reversed for larger rods. image uniformity on the coincidence system <3 %) was superior to that on the pinhole system (10 %), as was the peak sensitivity (4 % compared to 0.4 %). The high [18(F)]FDG uptake in the striatum of the mouse brain was fully resolved using the pinhole system with contrast to nearby regions equaling that from autoradiography;a lower contrast was found using the coincidence PET system. To conclude, in cases where small regions need to be resolved in scans with reasonably high activity or reasonably long scan times, a lower sensitivity clustered pinhole system with higher reconstructed spatial resolution (in this case the first generation vECTor with sub-optimal reconstruction software) can provide superior image quality in terms of contrast and the contra

关键词： brain collimators image reconstruction image resolution medical image processing phantoms positron emission tomography single photon emission computed tomography statistical analysis

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