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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 full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.
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.
All areas of ionizing radiation detection - detectors, signal processing, analysis of results, PET development, PET results, medical imaging using ionizing radiation
The Optical Fiber Communication Conference and Exhibition (OFC) is the largest global conference and exhibition for optical communications and networking professionals. For over 40 years, OFC has drawn attendees from all corners of the globe to meet and greet, teach and learn, make connections and move business forward.OFC attracts the biggest names in the field, offers key networking and partnering opportunities, and provides insights and inspiration on the major trends and technology advances affecting the industry. From technical presentations to the latest market trends and predictions, OFC is a one-stop-shop.
The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.
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.
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
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.
Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...
IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a strong combination of peer-reviewed feature articles and refereed departments, including news and product announcements. Special Applications sidebars relate research stories to commercial development. Cover stories focus on creative applications of the technology by an artist or ...
Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143), 2000
We studied image subtraction of temporally sequential chest images by rib image elimination. The image subtraction presents clinically useful information related to interval changes in chest images. Clinical chest images are not usually reproducible in terms of patient positioning, X-ray projection, inspiration, cardiac pulsation, etc. A proper image registration is needed prior to the subtraction. An image registration method by ...
2006 2nd International Conference on Information & Communication Technologies, 2006
Conventional surveillance system requires human power to monitor and thus not applicable for a long hour monitoring. An automated method is proposed here, an integration of a moving object detection and recognition. First, the moving object is detected and segmented by using selectiveness adaptive background subtraction technique followed by noise and shadow removal algorithm for removing disturbances. Then, standardize moment ...
2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2013
In the past a lot of work has been done to remove noise from speech. Most of the presented techniques were derived from Boll's spectral subtraction technique. Roughly speaking the spectral subtraction techniques consists of estimating the noise power during the periods when no speech is present and subtracting this estimate of the noise power from the signal when speech ...
2012 12th International Conference on Control, Automation and Systems, 2012
Recently, the death rate due to the liver cancer rises remarkably. To reduce the rate, the early detection of the disease is important. To detect diseases in early stage which are concern cancer, image diagnosis such as CT image is used in medical fields. On the other hand, the burden to a radiologist becomes increase. Therefore, the development of a ...
2006 International RF and Microwave Conference, 2006
A new detection scheme, namely AND subtraction technique is proposed and presented in this paper. The theory is being elaborated and experimental results have been done by comparing double-weight (DW) code against the existing code, Hadamard. In this paper we have proved that AND subtraction technique gives better bit error rates (BER) performance than complementary subtraction technique against the received ...
IMS 2011 Microapps - A Comparison of Noise Parameter Measurement Techniques
IMS 2011 Microapps - Techniques for Validating a Vector Network Analyzer Calibration When Using Microwave Probes
IMS 2012 Microapps - High-Power VNA Calibration Techniques Keith Anderson, Agilent
IMS 2012 Microapps - Generation and Analysis Techniques for Cost-efficient SATCOM Measurements Richard Overdorf, Agilent
IMS 2011 Microapps - IQ Mixer Measurements: Techniques for Complete Characterization of IQ Mixers Using a Multi-Port Vector Network Analyzer
IMS 2012 Microapps - Practical Techniques for Recognizing and Diagnosing Root Causes of Poor Waferlevel S-parameter Calibrations
IMS 2011 Microapps - Improved Microwave Device Characterization and Qualification Using Affordable Microwave Microprobing Techniques for High-Yield Production of Microwave Components
Charles A. Mistretta accepts the IEEE Medal for Innovations in Healthcare Technology - Honors Ceremony 2016
IMS 2011 Microapps - Improved Soldering Techniques for Cylindrical RF Connectors Using HIG Induction Technology
IMS Organizer: Richard Snyder, President Elect for MTT-S
State-of-the art techniques for advanced vehicle dynamics control & vehicle state estimation
Micro-Apps 2013: Alternative Methods and Optimization Techniques for Vector Modulation
MicroApps: New Technologies and Techniques for Wideband Analysis (Agilent Technologies)
IMS Organizers: Samir El-Ghazaly, President of MTT-S on Society Mission and Structure
IMS 2010 Special Features: Recognizing Chuck Swift's 52 Years of Service
IMS Honorary Session for Tatsuo Itoh: Jenshan Lin
ON-CHIP VOLTAGE AND TIMING DIAGNOSTIC CIRCUITS
Alan S. Willsky - IEEE Jack S. Kilby Signal Processing Medal, 2019 IEEE Honors Ceremony
Design of Monolithic Silicon-Based Envelope-Tracking Power Amplifiers for Broadband Wireless Applications
We studied image subtraction of temporally sequential chest images by rib image elimination. The image subtraction presents clinically useful information related to interval changes in chest images. Clinical chest images are not usually reproducible in terms of patient positioning, X-ray projection, inspiration, cardiac pulsation, etc. A proper image registration is needed prior to the subtraction. An image registration method by nonlinear warping was suggested [A. Kano et al., 1994]. In the method, template regions of interest and the corresponding search area regions of interest are selected in the lung areas on the two images. The method provides an improper image registration for some pairs of temporally sequential images. One of the reasons for the improper image registration is the difference between the shifts of lung and rib by inspiration. Some pairs of temporally sequential chest images show large difference of lung position in the pairs in spite of small difference of rib position in the pairs. In this case, the method does not provide a proper image registration. To get the proper image registration of the temporally sequential images with different position changes for the rib and lung, we eliminated rib images from the chest images assuming that the contribution of rib to the chest image is uniform. The nonlinear warping was then applied to the rib eliminating images leading to the properly registered images and enhanced interval changes.
Conventional surveillance system requires human power to monitor and thus not applicable for a long hour monitoring. An automated method is proposed here, an integration of a moving object detection and recognition. First, the moving object is detected and segmented by using selectiveness adaptive background subtraction technique followed by noise and shadow removal algorithm for removing disturbances. Then, standardize moment invariant is employed to extract the features for each moving blobs. To recognize these blobs, the calculated moment values are fed to a neural network module that is equipped with trained extracted moment values for human and vehicle silhouettes. The results of the experiments showed a satisfied performance with the proposed approach
In the past a lot of work has been done to remove noise from speech. Most of the presented techniques were derived from Boll's spectral subtraction technique. Roughly speaking the spectral subtraction techniques consists of estimating the noise power during the periods when no speech is present and subtracting this estimate of the noise power from the signal when speech is present. This spectral subtraction technique could be a very good in-band de- noising technique for communication signals measured by cognitive radios. However, there is one major drawback: one can never turn off the spectrum so that no communication signals are present. This paper presents an extended version of the spectral subtraction technique which does not require `speech free' periods, but can determine the noise power from the empty frequency bins in the spectrum. The presented method is based on an autoregressive (AR) model, which is linear in the parameters. Simulation results show that the presented technique is as performing as the original spectral subtraction techniques without the need to turn off the signals.
Recently, the death rate due to the liver cancer rises remarkably. To reduce the rate, the early detection of the disease is important. To detect diseases in early stage which are concern cancer, image diagnosis such as CT image is used in medical fields. On the other hand, the burden to a radiologist becomes increase. Therefore, the development of a system reducing the burden of the radiologist is important. In order to diagnose abnormalities based on medical imaging there are some reports. But, there is no report which is concern with detecting abnormality on liver disease based on temporal subtraction technique for abdominal CT image. As one of the methods to analyze abnormalities on visual screening, temporal subtraction technique is useful. This technique subtracts past image to current one. To obtain the good performance based temporal subtraction technique, image registration is most important task. In this paper, we propose a registration method for liver CT image using voxel matching techniques. We describe our registration method from two CT image which obtained deference time series and shows experimental results with discussion.
A new detection scheme, namely AND subtraction technique is proposed and presented in this paper. The theory is being elaborated and experimental results have been done by comparing double-weight (DW) code against the existing code, Hadamard. In this paper we have proved that AND subtraction technique gives better bit error rates (BER) performance than complementary subtraction technique against the received power level. The overall system cost and complexity can be reduced by using less number of filters in this technique. At the same time, the performance of the OCDMA system is improved significantly because with less number of filters in the decoder, the total power loss can be reduced and this can be clearly seen in the result
Simple and efficient numerical procedures for evaluating the gradient of Helmholtz-type potentials are presented. The convergence behavior of both normal and tangential components of the gradient is examined. It is also shown that the scheme for handling near-hypersingular integrals is effective for handling nearly singular potential integrals as well, so the same quadrature scheme may be used for both simultaneously.
A very simple alternative analytical approach to calculate the free space static potential integral associated to uniform source distributions over arbitrary oriented flat polygons is presented. The technique is based on a novel integral transformation and the resulting formula is equivalent to others existing in literature, being also suitable within a singularity subtraction framework. The numerical integration of the obtained analytical expression is performed by utilizing Generalized Cartesian product rules built on the double exponential formula. Therefore, the problems linked to the endpoint singularities in the derivative of the potential are eased. These techniques are used within a surface integral equation-Method of Moments framework.
Background subtraction is a key pre-processing step for several video automatic operations. Various techniques have been proposed to perform background subtraction automatically in complex environments. Visual background extractor (ViBe) is a popular background subtraction technique that can initialize its model in a single frame, adapt to the environment changes and achieve satisfactory subtraction results. In this paper, we propose to use ViBe with blind updating which can more quickly adapt to dynamic environment changes. We propose foreground model with adaptive updating strategy to assist the ViBe with blind updating to detect slow moving object without introducing the ghost phenomenon. Experimental results have verified the performance of the proposed technique.
The authors compare two subtraction-based techniques, dual window and convolution subtraction, to iterative reconstruction incorporating an accurate model of the scatter response. Two phantoms, consisting of a cylindrical attenuator with circular cross section and hot or cold rods, were used. Projection data were simulated using Monte Carlo techniques. They were reconstructed using the maximum-likelihood-expectation maximization (ML-EM) algorithm with a projector/backprojector that accurately models photon attenuation and the spatially variant geometric and scatter responses. In addition, the data were scatter-compensated using the subtraction techniques and then reconstructed using ML-EM with a projector/backprojector modeling only attenuation and collimator response. It was found that the images reconstructed with the accurate scatter model are superior in terms of mean square error, standard deviation, and signal-to-noise ratio to data reconstructed following scatter subtraction. The quantitative accuracy of the images reconstructed with subtraction techniques depends critically on the selection of subtraction parameters.<<ETX>>
A novel no-reference video quality assessment is proposed in this paper. The proposed metric is based on the combination of two-pass edge analysis and background subtraction. The two-pass edge analysis is a blur metric we proposed in our previous work, which has gain an efficient performance in image blur assessment and other image processing applications. We apply the two-pass edge analysis to the video quality assessment in order to calculate the quality of each frame in the video. On the other hand, considering that one will pay his most attention on the foreground of the video. So we also apply the background subtraction to get the foreground of the video and only use these foreground to calculate the video quality. Experiments in the last section shows that our proposed no-reference metric has a good performance in the test sequences.
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