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Liver Fibrosis Identification Based on Ultrasound images

Liver Fibrosis Identification Based on Ultrasound Images

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Guitao Cao Pengfei Shi Bing Hu Institute of Image Processing and Pattern recognition Shanghai Jiaotong University Shanghai China Department of Ultrasound in Medicine Shanghai Sixth Hospital Shanghai Jiaotong University Shanghai China

Diagnostic ultrasound is one of useful and noninvasive tools for clinical medicine. However, due to its qualitative, subjective and experience-based nature, ultrasound images can be influenced by image conditions such as scanning frequency and machine settings. In this paper, a novel method is proposed to extract the liver features using the joint features of fractal dimension and the entropies of texture edge co-occurrence matrix based on ultrasound images, which is not sensitive to changes in emission frequency and gain. Then, Fisher linear classifier and support vector machine are employed to test on a group of 99 liver fibrosis images from 18 patients, as well as other 273 healthy liver images from 18 specimens

关键词： Liver Ultrasonic imaging Frequency Biomedical imaging Medical diagnostic imaging Feature extraction Fractals Entropy Support vector machines Support vector machine classification

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Ultrasonic Liver Characterization Using Phase Congruency

Ultrasonic Liver Characterization Using Phase Congruency

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Feature extraction plays an important role in the whole process of liver characterization. Because the ultrasonic scanner in use can be adjusted by different clinicians to produce optimal images, the ultrasound images captured sometimes can be greatly influenced by machine settings and further impact the classification result. In this paper, some experiments are made to try to extract the liver features using the 2D phase congruency, which invariant to changes in intensity or contrast, to try to avoid those problems. The effectiveness of our method tested on three classes of liver images shows the potential for physicians to quantify liver status in clinical diagnosis

关键词： Ultrasonic imaging Feature extraction Attenuation Liver diseases Cells (biology) Biopsy Testing Clinical diagnosis Support vector machines Radiofrequency identification

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A DSP/FPGA - Based Parallel Architecture for Real-time image processing

A DSP/FPGA - Based Parallel Architecture for Real-time Image...

引用

World Congress on Intelligent Control and Automation (WCICA)

作者： Luxin Yan Tianxu Zhang Sheng Zhong Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

A DSP/FPGA-based parallel architecture oriented to real-time image processing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnection network and the specific data communication protocol are implemented, which interconnect 3 DSPs (TMS320C6414) effectively. The measured performances in the prototype with the proposed parallel architecture, including inter-DSP data communication performance and system computing capacity, show high data transfer bandwidth (up to 400 Mbytes/s) with low latency as well as high image processing performance, which achieve a good balance for parallel image processing

关键词： Digital signal processing Field programmable gate arrays Parallel architectures image processing Data communication Computer architecture Multiprocessor interconnection networks Protocols Performance evaluation Prototypes

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Dualband Infrared images Target Detection Algorithm Based on Multiscale Morphology

Dualband Infrared Images Target Detection Algorithm Based on...

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2006 8th International Conference on Signal processing

作者： Yuqiu Sun Jinwen Tian Jian Liu School of Information and Mathematics Yangtze University State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial IntelligenceHuazhong University of Science and Technology

According to the features of mid-wave and long-wave infrared images,they are decomposed into morphology pyramid respectively based on the new multiscale mathematical morphology filters proposed in the *** features such as local maximum gray level and average gradient strength of every image are extracted at each level of morphology *** dualband infrared images based on fusion rule put forward in the paper,and then reconstruct original image and detect target using contrast threshold *** experiment results show that dualband infrared images target detection algorithm based on multiscale morphology algorithm is better than use mid-wave or long-wave infrared images detect targets alone.

关键词： image Dualband Infrared images Target Detection Algorithm Based on Multiscale Morphology Target

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Active Feature Models

Active Feature Models

引用

International Conference on pattern recognition

作者： G. Langs P. Peloschek R. Donner M. Reiter H. Bischof Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group University of Technology Vienna Austria Department of Radiology Medical University of Vienna Austria

ISBN: (纸本)0769525210

In this paper active feature models are proposed. They utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. They are related to active appearance models, but instead of modelling the entire texture of an object they represent image texture by means of local descriptors. The approach has advantages with complex image data like anatomical structures that exhibit high texture variation with limited relevance for the recognition of the object location. Experimental results and the comparison to AAMs on different data sets indicate that active feature models can improve search speed and result accuracy, considerably

关键词： Shape Active appearance model Biomedical imaging image texture image edge detection image texture analysis Computer graphics pattern recognition image processing Radiology

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Computer Analysis Method for Clinical CT image

Computer Analysis Method for Clinical CT Image

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International Multi-Symposiums on Computer and Computational Sciences (IMSCCS)

作者： Weiguo Bian Shaojie Tang Huazi Xu The Second Affiliated Hospital Yuying Children''s Hospital of Wenzhou Medical College Wenzhou Zhejiang China Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an Shaanxi China

This paper describes a new computer analysis method for the judgment of vertebral canal stenosis of lumbar spin by X-ray CT images, where a large number of technologies on computer image analysis and digital image processing are utilized such as image segmentation, morphology, coordinates transform, Hough transform, histogram equalization of image gray level, etc. For the boundaries extraction of every defined region in lumbar spin, we propose a new and concise algorithm with radial or polar sampling on the binary CT images. Although adopting computer program to automatically process some routine manual works is still very primary at present research, we believe that it is an excellent orientation for the clinical aided diagnosis. An example of processing realistic CT images is used to validate the feasibility of the whole procedure

关键词： image analysis Computed tomography Irrigation Area measurement Software measurement Hospitals Inspection Humans Independent component analysis Orthopedic surgery

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Automatic Surveying of Cutaneous Hemangiomas

Automatic Surveying of Cutaneous Hemangiomas

引用

International Conference on pattern recognition

作者： S. Zambanini G. Langs R. Sablatnig P. Donath H. Maier Pattern Recognition and Image Processing Group University of Technology Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Austria Division of Special and Environmental Dermatologyy Medical University of Vienna Austria

This paper presents a method for the fully automatic surveying of cutaneous hemangiomas by means of a hemangioma segmentation and a ruler visible in the images. The algorithm computes the spatial resolution of an image. Hemangioma segmentation is accomplished by a single-layer perceptron classification by means of pixel color features. The algorithm was evaluated on a set of 120 images. It achieves satisfactory results on images with clearly visible, saturated hemangiomas

关键词： image segmentation Neoplasms pattern recognition Spatial resolution Lesions Area measurement Pixel image processing Computer graphics Biomedical imaging

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RBF Network image Representation with Application to CT image Reconstruction

RBF Network image Representation with Application to CT Imag...

引用

International Conference on Computational Intelligence and Security

作者： Ping Guo Ming Hu Yunde Jia Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science Beijing Institute of Technology Beijing China Beijing Normal University Beijing Beijing CN China

ISBN: (纸本)1424406048

Radial basis function (RBF) neural network can be used as a universal approximator. In this paper, we propose a novel method to apply RBF net to reconstruct 2-dimensional computerized tomography (CT) images from a small amount of projection data. In the method, the cross-sectional image is represented by a RBF network, the unknown cross-sectional image vector is replaced by the function of the network's weight vector. As proved by us, the line integral of the weight matrix can be calculated providing the projections of the CT image are known. The ART method can be employed to obtain the final reconstructed CT image. Experiments show that the proposed method can obtain the better reconstructed image than the filtered back projection (FBP), and it is also more efficient than ART method alone

关键词： Radial basis function networks image representation Computed tomography image reconstruction Subspace constraints Matrix converters Equations Application software Laboratories Neural networks

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3D TRUS image Segmentation in Prostate Brachytherapy

3D TRUS Image Segmentation in Prostate Brachytherapy

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Mingyue Ding L. Gardi Zhouping Wei A. Fenster Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China Imaging Research Laboratories Robarts Research Institute London ONT Canada

Brachytherapy is a minimally invasive interventional surgery used to treat prostate cancer. It is composed of three steps: dose pre-planning, implantation of radioactive seeds, and dose post-planning. In these procedures, it is crucial to determine the positions of needles and seeds, measure the volume of the prostate gland. Three-dimensional transrectal ultrasound (TRUS) imaging has been demonstrated to be a useful technique to perform such tasks. Compared to CT, MRI or X-ray imaging, US image suffers from low contrast, image speckle and shadows, making it challenging for segmentation of needles, the prostates and seeds in the 3D TRUS images. In this paper, we reviewed 3D TRUS image segmentation methods used in prostate brachytherapy including the segmentations of the needles, the prostate, as well as the seeds. Furthermore, some experimental results with agar phantom, turkey and chicken phantom, as well as the patient data are reported

关键词： image segmentation Brachytherapy Needles Minimally invasive surgery Ultrasonic imaging Imaging phantoms Oncological surgery Prostate cancer Position measurement Volume measurement

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Embedded Real-Time Ball Detection Unit for the YABIRO Biped Robot

Embedded Real-Time Ball Detection Unit for the YABIRO Biped ...

引用

Workshop on Intelligent Solutions in Embedded Systems

作者： Markus Bader Miguel Albero Robert Sablatnig Jose E. Simo Gines Benet Gregor Novak Francisco Blanes Institute of Computer Aided Automation Pattern Recognition and Image Processing Group University of Technology Vienna Austria Departamento de Informática de Sistemas y Computadores Universidad Politécnica de Valencia Spain

Estimation of objects in a 3D space is a fundamental problem in computer vision and robotics. This paper describes an algorithm and its implementation for a vision module as a sensor of a biped robot (YABIRO). The embedded vision sensor is able to estimate the position of objects like spheres in 3D space. Objects are defined with their size and color in a model. The vision sensor detects the positions or at least the directions to the objects and stores them in a history. The algorithm includes a new voting system for detected objects, based on how trustable the detection was, and a new edge filter to terminate edges on the circle border for the circle detection. The systems frame rate depends on the area of interest and lies between 5 Hz and 20 Hz. With a mechanical size of 36times32mm it is smaller than a matchbox

关键词： Object detection Robot sensing systems Robot vision systems Computer vision Space technology Detection algorithms Hardware Embedded computing image edge detection Cameras

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