Conferences related to Image reconstruction

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2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting

The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science


2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2018 will be the 15th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2018 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2017 will be the 14th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2017 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forumfor the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2016 willbe the thirteenth meeting in this series. The previous meetings have played a leading role in facilitatinginteraction between researchers in medical and biological imaging. The 2016 meeting will continue thistradition of fostering crossfertilization among different imaging communities and contributing to an integrativeapproach to biomedical imaging across all scales of observation.

  • 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2015 will be the 12th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2014 will be the eleventh meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)

    To serve the biological, biomedical, bioengineering, bioimaging and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI 2010)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2009 IEEE 6th International Symposium on Biomedical Imaging (ISBI 2009)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2008 IEEE 5th International Symposium on Biomedical Imaging (ISBI 2008)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2007 IEEE 4th International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2007)

  • 2006 IEEE 3rd International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2006)

  • 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2004)

  • 2002 1st IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2002)


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


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Periodicals related to Image reconstruction

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Automation Science and Engineering, IEEE Transactions on

The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...


Biomedical Engineering, IEEE Reviews in

The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.


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Most published Xplore authors for Image reconstruction

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Xplore Articles related to Image reconstruction

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Comparison of two image reconstruction algorithms for microwave tomography

Radio Science, 2005

Two image reconstruction algorithms for microwave tomography are compared and contrasted. One is a general, gradient-based minimization algorithm. The other is the chirp pulse microwave computed tomography (CP-MCT) method, which is a highly computationally efficient reconstruction method but also a method best suited for low contrasts. The results of the simulations show that when imaging high-contrast objects, such as a ...


Optimized implementation of the FDK algorithm on one digital signal processor

Tsinghua Science and Technology, 2010

This paper presents an optimized implementation of the FDK algorithm on a single fixed-point TMS320C6455 digital signal processor (DSP). Software pipelining and proper configuration of the data transfer enables a 2563 volume to be reconstructed in about 42 seconds from 360 projections with very good accuracy. This implementation reveals the potential of modern high-performance DSPs in accelerating image reconstruction, especially ...


Modified Fast Factorized Backprojection as Applied to X-Band Data for Curved Flight Paths

7th European Conference on Synthetic Aperture Radar, 2008

A Fast Factorized Backprojection scheme modified to X-band frequencies and applicable to small aperture beamwidths is presented to compute SAR images from real and synthetic airborne data sets. The numerical complexity and memory consumption of the algorithm is verified and compared to ordinary Backprojection. The modified Fast Factorized Backprojection scheme is investigated for exceedingly curved flight paths and compared to ...


Low bit-rate codec based on LAR method for video surveillance via Internet

2000 10th European Signal Processing Conference, 2000

This paper presents a full codec for a distributed video surveillance system. It is based on a new method called LAR, mixing both spatial and spectral approaches. The spatial coder provides a low resolution image but preserving objects boundaries, whereas the spectral coder can add the local texture information. The encoding scheme is progressive, providing large flexibility for rate/quality trade-off.


High Resolution Particle Detection via Spectral Estimation

SCC 2013; 9th International ITG Conference on Systems, Communication and Coding, 2013

Within this paper the problem of Particle Tracking Velocimetry (PTV) is considered. PTV investigates turbulences in fluids by tracking particles with high temporal and spatial resolution. Due to the acquisition with high speed cameras, high spatial resolution and, therefore, a huge amount of data for the captured pictures, the particle flow can only be observed within a very small period ...


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Educational Resources on Image reconstruction

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IEEE-USA E-Books

  • Comparison of two image reconstruction algorithms for microwave tomography

    Two image reconstruction algorithms for microwave tomography are compared and contrasted. One is a general, gradient-based minimization algorithm. The other is the chirp pulse microwave computed tomography (CP-MCT) method, which is a highly computationally efficient reconstruction method but also a method best suited for low contrasts. The results of the simulations show that when imaging high-contrast objects, such as a breast cancer tumor, reconstructions made are comparable to results from the minimization algorithm below a contrast of about 10%. The simulations, however, show that the reconstructions made by the CP-MCT method are very robust to noise. The reconstruction of the conductivity using the minimization algorithm, on the other hand, is very sensitive to the level of noise. In spite of a strong degradation in the conductivity reconstructions, the corresponding permittivity reconstructions do not show the same sensitivity to the noise level.

  • Optimized implementation of the FDK algorithm on one digital signal processor

    This paper presents an optimized implementation of the FDK algorithm on a single fixed-point TMS320C6455 digital signal processor (DSP). Software pipelining and proper configuration of the data transfer enables a 2563 volume to be reconstructed in about 42 seconds from 360 projections with very good accuracy. This implementation reveals the potential of modern high-performance DSPs in accelerating image reconstruction, especially when cost and power consumption are emphasized.

  • Modified Fast Factorized Backprojection as Applied to X-Band Data for Curved Flight Paths

    A Fast Factorized Backprojection scheme modified to X-band frequencies and applicable to small aperture beamwidths is presented to compute SAR images from real and synthetic airborne data sets. The numerical complexity and memory consumption of the algorithm is verified and compared to ordinary Backprojection. The modified Fast Factorized Backprojection scheme is investigated for exceedingly curved flight paths and compared to an omega-k algorithm in combination with a motion error correction. Excellent SAR image focusing results were found for the modified Fast Factorized Backprojection approach while keeping the numerical complexity to O(N2log(N)).

  • Low bit-rate codec based on LAR method for video surveillance via Internet

    This paper presents a full codec for a distributed video surveillance system. It is based on a new method called LAR, mixing both spatial and spectral approaches. The spatial coder provides a low resolution image but preserving objects boundaries, whereas the spectral coder can add the local texture information. The encoding scheme is progressive, providing large flexibility for rate/quality trade-off.

  • High Resolution Particle Detection via Spectral Estimation

    Within this paper the problem of Particle Tracking Velocimetry (PTV) is considered. PTV investigates turbulences in fluids by tracking particles with high temporal and spatial resolution. Due to the acquisition with high speed cameras, high spatial resolution and, therefore, a huge amount of data for the captured pictures, the particle flow can only be observed within a very small period of time. The proposed, new and practical system design allows a significant decrease of the spatial sampling rate for the pictures. This decreases the amount of data to be captured and, therefore, increases the possible time for observation. Designing a 2-stage sampling allows the use of conventional camera sensors as used up to now. Thus, it is directly applicable without a change of existing camera systems. From a signal processing point of view, this paper considers the problem of sampling a 2-D signal with Finite Rate of Innovation (FRI). Therefore, an appropriate solution for sampling and reconstruction of such signals is proposed. Furthermore, the performance for reconstruction of signal parameters under the influence of coloured noise is investigated as well as the accuracy of the estimates if no model knowledge is available.

  • Reconstruction methods of missing SAR data: Analysis in the frame of TanDEM-X synchronization link

    The reconstruction of corrupted or missing data is a conventional problem in image and audio processing, but has only raised moderate attention in the SAR community. In the frame of the TanDEM-X mission, the cooperative operation of the bistatic system requires the exchange of information between transmitter and receiver during the acquisition time in order to gather calibration and sync information. Therefore, the reception of SAR signal is periodically interrupted according to the synchronization link frequency and artifacts appear in the focused image. The data corruption is especially problematic when acquiring close to the Nyquist rate.

  • Correction to "Resampling and reconstruction with fractal interpolation functions"

    None

  • Comprehensive Use of Curvature for Robust and Accurate Online Surface Reconstruction

    Interactive real-time scene acquisition from hand-held depth cameras has recently developed much momentum, enabling applications in ad-hoc object acquisition, augmented reality and other fields. A key challenge to online reconstruction remains error accumulation in the reconstructed camera trajectory, due to drift-inducing instabilities in the range scan alignments of the underlying iterative-closest-point (ICP) algorithm. Various strategies have been proposed to mitigate that drift, including SIFT-based pre-alignment, color-based weighting of ICP pairs, stronger weighting of edge features, and so on. In our work, we focus on surface curvature as a feature that is detectable on range scans alone and hence does not depend on accurate multi- sensor alignment. In contrast to previous work that took curvature into consideration, however, we treat curvature as an independent quantity that we consistently incorporate into every stage of the real-time reconstruction pipeline, including densely curvature-weighted ICP, range image fusion, local surface reconstruction, and rendering. Using multiple benchmark sequences, and in direct comparison to other state-of-the-art online acquisition systems, we show that our approach significantly reduces drift, both when analyzing individual pipeline stages in isolation, as well as seen across the online reconstruction pipeline as a whole.

  • Unified image/bitstream analysis for the robust decoding of compressed video sequences for wireless networks

    This paper is concerned with the problem of error detection and correction of MPEG-4 video streams transmitted over lossy networks. The problem is first defined and some relevant detail of the MPEG-4 syntax is presented. The difficulties encountered in articulating this problem within a unified Bayesian framework are explored and two separate frameworks for dealing with error detection and error correction are then presented, along with some results. The paper concludes with some comments on the techniques used and pointers to future plans.

  • An algorithm for reconstructing positive images from noisy data

    In this paper we describe a novel method for finding non-negative solutions to linear inverse problems. Such problems include image reconstruction where one is required to deconvolve a known point spread function from the image to produce a clearer image. The method described here is related to the truncated singular function expansion for solving linear inverse problems. The method consists of choosing the non-negative solution with minimum 2-norm whose singular function expansion agrees with the truncated singular function expansion solution in its first N terms. The fact that only the first N singular function coefficients, which are easily derived from the data, are used gives the method robustness with respect to noise and the method is not computationally very demanding.



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