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共 2036 条记录，以下是2001-2010 订阅

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An associative-processor-based mixed signal system for robust grayscale image recognition

An associative-processor-based mixed signal system for robus...

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IEEE international Symposium on Circuits and Systems (ISCAS)

作者： M. Yagi T. Shibata Department of Electronics Engineering School of Engineering University of Tokyo Tokyo Japan Department of Frontier Informatics School of Frontier Science University of Tokyo Tokyo Japan

An associative-processor-based VLSI system architecture has been developed for robust grayscale image recognition. The system receives a 64/spl times/64 pels block of a gray scale image, extracting a feature vector from the image and recognizing the image by template matching. An analog associative processor is adopted as the template matching core because it features compact implementation as well as fast processing due to its fully parallel architecture. For generating feature vectors, dedicated digital CMOS circuits have been developed because of their versatility in the algorithm. The analysis of medical X-ray pictures (Cephalometric landmark identification by expert dentists) was taken as an exercise for the system, and intensive computer simulations have been conducted to optimize the recognition performance of the system. Although the entire system has not yet been implemented on a single chip, all the key sub circuits in the system were fabricated as test circuits and their correct functioning has been experimentally demonstrated. It is also shown by experiment that very low power operation of the template matching core is possible by operating the analog circuitry in the subthreshold regime without degrading recognition performance.

关键词： Robustness Gray-scale image recognition Circuit testing Very large scale integration Feature extraction Parallel architectures CMOS digital integrated circuits Performance analysis biomedical imaging

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Today’s and tomorrow’s medical imaging 9th

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9th international Conference on Computer Analysis of images and Patterns, CAIP 2001

作者： Przelaskowski, Artur Institute of Radioelectronics Warsaw University of Technology Nowowiejska 15/19 Warszawa00-665 Poland

ISBN: (纸本)9783540425137

biomedical engineering in present form started its developing since the late 1960’s and includes engineering applications in physiology and medicine, such as Biomechanics, biomedical Instrumentation, Bioelectrical processes, Biocontrol systems, biomedical signal and image processing, Medical informatics and others. In last decades Medical Imaging (MI) started to play important role in innovatory solutions and applications of biomedical engineering. In our presentation current trends of medical imaging development are considered. We mean an interesting projects, the ideas currently developed in labs and many research centers. Underlying our research leaded in many areas of medical imaging, nuclear and medical engineering, in collaborations with several medical and biomedical centers and institutes of physics and nuclear science, we intended to present a quick review of the most hopeful research directions. -What is important, and worth of work with? -Is the medical imaging dynamically developing science of the useful applications, truly important in an information society development, able to cumulate the resources and interests of youth? Subjectively, we tried to find the answers considering the following topics: - functional imaging of organs and tissues: PET (brain), SPECT (circulatory system, organs), MRI (brain, circulatory system, organs), CT(circulatory system, organs);dynamic imaging of heart and blood vessels, blood supply of liver and kidneys, etc., 2-D and even 3-D perfusion maps, statistical flow models and objective computable parameters required to be standardized (EBCT, dynamic MRI, even US Power Doopler);- image detectors (PET, radiography, CT), detection systems (SPECT), detectors (scintillators), sensors with amorphous silicon and selenium in digital radiography, x-ray tubes with laser beam irradiation;- virtual endoscopy (bronchoscophy, gastroscophy);- telemedicine, means protocols, network switches, satellite connectors, and PACS, DICOM servers, i

关键词： image enhancement

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Design of complex-valued CNN filters for medical image enhancement

Design of complex-valued CNN filters for medical image enhan...

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Conference of the North American Fuzzy Information processing Society - NAFIPS

作者： K. Kondo M. Iguchi H. Ishigaki Y. Konishi K. Mabuchi Faculty of Engineering Himeji Institute of Technology Himeji Hyogo Japan Center for Collaborative Research University of Tokyo Meguro Tokyo Japan

In this paper, we present a new image enhancement technique, using cellular neural network (CNN) filters with complex weighting factors, that is applicable to medical images. Since CNN-type filters have only spatially local interconnections and the number of connections between neurons is relatively low, the required computation in the learning phase is a reasonable amount. However, the output/input behavior is restrictive. The proposed CNN filters are designed as complex-coefficient filters which can improve the output SNR and process the 2D analytic signals of input images. The filter parameters are determined by applying a complex domain backpropagation algorithm. Through several simulations, it is shown that the proposed filters are robust and noise-tolerant for medical images.

关键词： Cellular neural networks Filters biomedical imaging image enhancement Neurons signal design image analysis signal analysis signal processing Backpropagation algorithms

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Lossless medical image compression algorithm exploring three dimensional space

Lossless medical image compression algorithm exploring three...

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international Conference on signal processing Proceedings (ICSP)

作者： Wu Dajun Tan Eng Chong School of Applied Science Computer Engineering Nanyang Technological University Singapore

There has been a lot of research on lossless medical image compression in the 2D domain. As for volumetric data, a 3D image is firstly cut into slices and then compressed losslessly in 2D space. However, in this way, the information redundancy between neighboring slices is not exploited. This paper extends the segmentation-based lossless image coding (SLIC) algorithm to deal with image data from 2D to 3D. The results show that the new method not only encompasses all the SLIC functions, but also produces same results on 2D images and performs better on image volume data which has inherent 3D characteristics.

关键词： Space exploration biomedical imaging image coding Space technology Redundancy Magnetic resonance imaging image segmentation Pixel biomedical engineering Computed tomography

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Applications of statistical signal processing in image data compression

Applications of statistical signal processing in image data ...

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international Conference on signal processing Proceedings (ICSP)

作者： P. Stavroulakis C.P. Kakkavas H.G. Sandalidis Telecommunication Systems Institute of Crete Crete Greece Department of Electronic and Electrical Engineering University of Bradford Bradford Yorkshire UK

The study of image compression has been risen dramatically. Many new ideas have come out with impressive results. Since images can be regarded as two-dimensional signals with the independent variables being the coordinates of two-dimensional space, many digital compression techniques can be extended, for instance from one-dimensional signals. This paper presents the most used still and video image compression techniques.

关键词： signal processing Data compression image coding Application software Entropy Propagation losses biomedical imaging Law Legal factors Bit rate

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Uuinformation-theoretic reconstruction of moment-coded grey-scale images

Uuinformation-theoretic reconstruction of moment-coded grey-...

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international Conference on signal processing Proceedings (ICSP)

作者： R.C. Papademetriou D.A. Karras Department of Electrical & Electronic Engineering University of Portsmouth Portsmouth UK Department of Business Administration University of Piraeus Greece

The information-theoretic method of maximum entropy (ME) is applied to the problem of reconstructing a grey-scale image from a finite set of its geometric moments (GMs). Simulation results, using medical images, demonstrate the superiority of the ME method, with almost threefold compression ratios achieved, over the Legendre moments (LMs) approach.

关键词： image reconstruction Entropy biomedical imaging Medical simulation image coding image segmentation Statistics Pattern recognition Pattern matching image recognition

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The new method of reducing the NMR image's ringing artifacts by wavelet transform

The new method of reducing the NMR image's ringing artifacts...

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international Conference on signal processing Proceedings (ICSP)

作者： Jiang Mingyan Zhu Daming Lei Peng Computer Science Department ShanDong Univérsity Jinan China Electronic Engineering Department ShanDong Univérsity Jinan China

It is difficult to reduce an NMR image's ringing artifacts and obtain better images. This paper uses the method of dyadic wavelets and self-adaptive threshold to process the images that have the ringing artifacts. The test results prove that the method is effective and it can process the NMR image's ringing artifacts. Finally the paper discusses using the fuzzy method.

关键词： Nuclear magnetic resonance Wavelet transforms image reconstruction Filters biomedical imaging Frequency domain analysis Multi-layer neural network Computer science Testing Magnetic separation

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Extraction of blood vessel in CT angiography image aided by fuzzy logic

Extraction of blood vessel in CT angiography image aided by ...

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international Conference on signal processing Proceedings (ICSP)

作者： Changjiang Yan Shoji Hirano Yutaka Hata Department of Computer Engineering Himeji Institute of Technology Himeji Japan

To diagnose cerebral diseases, visual perception for the cerebrovascular system is essential. We propose a method for segmenting the cerebrovascular region from the computed tomography angiography (CTA) images. By segmenting it, we can generate the surface shade display, which is appropriate for evaluating the morphology. The proposed method first derives a rough image by combining a raw image and the difference image. The difference image is obtained by applying a Laplacian filter. For the rough image, the venae and arteries are segmented by fuzzy inference. The method then extracts the Willis ring contacting the blood vessels based on region growing techniques. The experimental result shows that our method can extract the blood vessels in CTA images with high accuracy.

关键词： Blood vessels biomedical imaging Computed tomography Angiography image segmentation Diseases Visual perception Rough surfaces Surface roughness Surface morphology

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Design of two-dimensional adaptive digital notch filters

Design of two-dimensional adaptive digital notch filters

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international Conference on signal processing Proceedings (ICSP)

作者： T. Hinamoto N. Ikeda S. Nishimura A. Doi Faculty of Engineering Hiroshima University Higashihiroshima Japan Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Japan Faculty of Engineering Hiroshima University HigashiHiroshima Japan

A method for realizing a two-dimensional (2-D) adaptive notch filter is proposed. The obtained 2-D structure contains a pair of one-dimensional (1-D) second-order IIR notch filters and a pair of 1-D first-order allpass filters. The method has been successfully applied to the removal of a sinusoidal interference superimposed on an image.

关键词： Adaptive filters Digital filters IIR filters Frequency response Lattices Electronic mail Interference Radar imaging Communication system control biomedical engineering

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A rule-based expert system for automatic segmentation of cerebral MRI images

A rule-based expert system for automatic segmentation of cer...

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international Conference on signal processing Proceedings (ICSP)

作者： Shanjun Zhang J. Maeda Department of Computer Science and Systems Engineering Muroran Institute of Technology Muroran Japan

The interior boundary of a medical image is fuzzy in nature. We propose a novel method to segment and classify the MR image of the head by fuzzy clustering and fuzzy reasoning. Traditional fuzzy clustering methods are basically statistical ones in which only intensity affinities of the image are reflected. Considering the characteristics of an MR image, we constructed a set of knowledge-based rules to set the fuzzy memberships of the pixels of the image by generally using the intensity similarities, positional relationships among multiple spectra MR images, shape features of the brain tissues and the mathematics morphological analogy of the brain tissues. Then a coarse-to-fine reasoning method is used to combine the fuzzy memberships of the pixels of the T1- and T2-channels of the image to segment the cerebral tissues into gray matter, white matter, and CSF. Experimental results showed the efficiency of the method.

关键词： Expert systems image segmentation Fuzzy reasoning Pixel Medical expert systems biomedical imaging Head Clustering methods Fuzzy sets Shape

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