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MCIF-Transformer Mask RCNN:Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

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computers, Materials & Continua 2024年第6期79卷 4371-4393页

作者： Huiling Lu Tao Zhou School of Medical Information&Engineering Ningxia Medical UniversityYinchuan750004China School of Computer Science and Engineering North Minzu UniversityYinchuan750021China Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission NorthMinzu UniversityYinchuan750021China

The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided ***,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are *** solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung *** pixel dependence relationship is established in local and non-local fields to improve the model perception ***,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained ***,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic ***,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image *** results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this *** method has positive significance for the detection of lung tumors.

关键词： PET/CT images instance segmentation mask RCNN interactive fusion transformer

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A fast pavement location approach for autonomous car navigation 19

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19th Iberoamerican Congress on Pattern Recognition, CIARP 2014

作者： Rateke, Thiago Justen, Karla A. Chiarella, Vito F. Linhares, Rodrigo T. F. Sobieranski, Antonio Carlos Comunello, Eros von Wangenheim, Aldo Federal University of Santa Catarina Brazil Laboratory of Image Processing and Computer Graphics National Brazilian Institute for Digital Convergence Brazil Federal University of Parana Department of Informatics Brazil

ISBN: (纸本)9783319125671

This paper describes a fast image segmentation approach designed for pavement detection in a moving camera. The method is based on a graph-oriented segmentation approach where gradient information is used temporally as a system of discontinuities to control merging between adjacent regions. The method presumes that the navigable path usually is located at specific positions on the scene, and a predefined set of seed points is used to locate the region of interest. The obtained results shown the proposed approach is able to accurately detect in an inexpensive computation manner the navigable path even in non-optimum scenarios such as miss-painted or unpaved dirt roads. Validation was conducted using a dataset with 701 samples of navigable paths, presenting a very high precision for real-time applications. © Springer International Publishing Switzerland 2014.

关键词： Pavements

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MSD-Net: Pneumonia Classification Model Based on Multi-Scale Directional Feature Enhancement

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computers, Materials & Continua 2024年第6期79卷 4863-4882页

作者： Tao Zhou Yujie Guo Caiyue Peng Yuxia Niu Yunfeng Pan Huiling Lu School of Computer Science and Engineering North Minzu UniversityYinchuan750021China School of Medical Information&Engineering Ningxia Medical UniversityYinchuan750004China Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission North Minzu UniversityYinchuan750021China

computer-aided diagnosis of pneumonia based on deep learning is a research ***,there are some problems that the features of different sizes and different directions are not sufficient when extracting the features in lung X-ray images.A pneumonia classification model based on multi-scale directional feature enhancement MSD-Net is proposed in this *** main innovations are as follows:Firstly,the Multi-scale Residual Feature Extraction Module(MRFEM)is designed to effectively extract multi-scale *** MRFEM uses dilated convolutions with different expansion rates to increase the receptive field and extract multi-scale features ***,the Multi-scale Directional Feature Perception Module(MDFPM)is designed,which uses a three-branch structure of different sizes convolution to transmit direction feature layer by layer,and focuses on the target region to enhance the feature ***,the Axial Compression Former Module(ACFM)is designed to perform global calculations to enhance the perception ability of global features in different *** verify the effectiveness of the MSD-Net,comparative experiments and ablation experiments are carried *** the COVID-19 RADIOGRAPHY DATABASE,the Accuracy,Recall,Precision,F1 Score,and Specificity of MSD-Net are 97.76%,95.57%,95.52%,95.52%,and 98.51%,*** the chest X-ray dataset,the Accuracy,Recall,Precision,F1 Score and Specificity of MSD-Net are 97.78%,95.22%,96.49%,95.58%,and 98.11%,*** model improves the accuracy of lung image recognition effectively and provides an important clinical reference to pneumonia computer-Aided Diagnosis.

关键词： Pneumonia X-ray image ResNet multi-scale feature direction feature transformer

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SYSTOLIC ARRAY FOR ALL-NEAREST-NEIGHBORS PROBLEM

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ELECTRONICS LETTERS 1987年第24期23卷 1259-1260页

作者： PETKOV, N International Basic Laboratory for Image Processing & Computer Graphics Central Institute for Cybernetics & Information Processes Berlin East Germany

The all-nearest-neighbours (ANN) problem is a fundamental problem in computational geometry. In the letter a new two-dimensional triangular systolic array with mesh-connected cells is proposed for the ANN problem. This array can process a queue of ANN problems at a throughput of one ANN problem per time period, with an efficiency of 100%.

关键词： computer architecture computational geometry throughput Other numerical methods ANN problem cellular arrays all-nearest-neighbours problem parallel architectures two-dimensional triangular systolic array efficiency mesh-connected cells

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TSM resilient audio watermarking using IMFs

TSM resilient audio watermarking using IMFs

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Canadian Conference on Electrical and computer Engineering (CCECE)

作者： Saif AlZahir Md Wahedul Islam Image Processing and Graphics Laboratory Computer Science Department UNBC BC Canada

With widespread of the Internet as well as the numerous applications that involve audio signals and systems, the issue of ownership proof become imperative. In this paper, we present an audio watermark scheme that is based on Empirical Mode Decomposition and Hilbert Huang Transform. The audio signal is decomposed into several mono-component signals or Intrinsic Mode Functions to serve as the addressee for watermark. The watermark is a pseudo random number which is added to the highest and lowest Intrinsic Mode Functions of the signal to generate what we call the modified IMFs which is in turn added to the remaining IMFs to produce the watermarked signal. Our experimental results show that the proposed method is robust against signal processing attacks such as MP3, time scale modification, resizing, and others. The obtained results meet the recommended imperceptibility signal to noise ratio.

关键词： Watermarking Robustness Signal to noise ratio Transforms Digital audio players Detectors

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Generic Visualization and Manipulation Framework for Three-Dimensional Medical Environments

Generic Visualization and Manipulation Framework for Three-D...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： B.S. Tani T. Nobrega T.R. dos Santos A. von Wangenheim Computer Graphics and Image Processing Laboratory Federal University of Santa Catarina Brazil

We present a visualization and manipulation framework for three-dimensional medical environments. The MVC architecture of the. framework allows the use of different API technologies such us OpenGL and DirectSD, different model representations, and controllers. This facilitates the implementation of medical applications offering resources commonly needed by such systems. Two case studies are shown as examples of such applications

关键词： Biomedical imaging Data visualization computer architecture Engines Medical control systems computer displays Medical services Biomedical equipment Application software Solid modeling

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Extraction of human body skeleton based on silhouette images

Extraction of human body skeleton based on silhouette images

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2nd International Workshop on Education Technology and computer Science, ETCS 2010

作者： Ding, Jianhao Wang, Yigang Yu, Lingyun State Key Laboratory of CAD and CG Zhejiang University Hangzhou China Institute of Computer Graphics and Image Processing Hangzhou Dianzi University Hangzhou China Department of Mathematics and Computing Science University of Groningen Netherlands

ISBN: (纸本)9780769539874

Skeleton extraction is essential for general shape representation. A typical skeletonization algorithm should obtain the ability to preserve original object's topological and hierarchical properties. However, most of current methods are high memory cost, computationally intensive, and also require complex data structures. In this paper, we propose an efficient and accurate skeletonization method for the skeleton feature points extracted from human body based on silhouette images. First, the gradient of distance transform is used to detect critical points inside the foreground. Then, we converge and simplify critical points in order to generate the most important and elegant skeleton feature points. Finally, we present an algorithm which connects the skeleton feature points and estimates the position of skeleton joints. © 2010 IEEE.

关键词： Extraction

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On Estimation Of 3D Hand Position Using Stereo Vision 19

On Estimation Of 3D Hand Position Using Stereo Vision

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19th International Conference on computers and Their Applications, CATA 2004

作者： Teruel, M.B. Kubushyna, O. El-Khater, R. Yfantis, E.A. Boyle, R. Computer Graphics and Image Processing Laboratory School of Computer Science University of Nevada Las Vegas Las VegasNV89154-4019 United States NASA Ames Research Center Moffett FieldCA94035-1000 United States

ISBN: (纸本)9781618395511

In this paper an approach for reconstructing the position of an object from a pair of stereo images that allows for a fast and effective hand tracking and 3D gesture reconstruction is presented. The algorithm will serve as a building block for more advanced tasks such as the reconstructing a complete 3D hand model from multiple views using feature extraction based on color and shape. Copyright © (2004) by the International Society for computers and Their Applications. All rights reserved.

关键词： Stereo image processing

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Keycap character detection model based on target classification 7

Keycap character detection model based on target classificat...

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2024 7th International Conference on Intelligent Manufacturing and Automation, IMA 2024

作者： Xiong, Taiping Zhu, Zhiguo Wang, Tinghao School of Computer and Information Security Guilin University of Electronic Technology Guangxi Guilin541004 China Key Laboratory of Image Graphics and Intelligent Processing in Guangxi Guilin University of Electronic Technology Guangxi Guilin541004 China

The production process of keycaps may result in surface character defects. The existing keycap character defect detection technology has low efficiency and accuracy, hindering the automation of keycap manufacturing. Addressing the challenge of extracting the entire keyboard from illuminated regions, this paper proposes a method using image feature points for template matching to extract the region of interest. Subsequently, leveraging prior knowledge, the paper addresses character segmentation and extraction on the keyboard. For character detection, the paper preprocesses images and classifies them by using an S-VGG network, yielding corresponding labels. © Published under licence by IOP Publishing Ltd.

关键词： Template matching

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Block-based normalized-cut algorithm for image segmentation

Block-based normalized-cut algorithm for image segmentation

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作者： Song, Haiyu Li, Xiongfei Wang, Pengjie Chen, Jingrun Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China Institute of Computer Graphics and Image Processing Dalian Nationalities University Dalian China State Key Laboratory of CAD and CG Zhejiang University Hangzhou China

ISBN: (纸本)9783642051722

Automatic image segmentation remains a challenging problem in the fields of computer vision, image analysis and understanding. A lot of algorithms and technologies have been proposed and developed for image segmentation, among which the N-cut has been a promising method and active research area due to better quality. But the N-cut can't process medium and large image dataset online due to incredible memory and time complexity. Moreover, the N-cut algorithm can't utilize texture information since its basic unit of clustering algorithm is pixel. To overcome the drawback and improve the description power, the paper proposes a block-based N-cut algorithm for image segmentation, whose basic unit of clustering is image block instead of individual pixel. Block-based algorithm not only decreases the time and storage complexity, but also improves the discrimination power of visual feature vector. The experiments demonstrate that proposed algorithm outperform the original N-cut algorithm in efficiency. Experiments show that the proposed block-based N-cut algorithm is more suitable for online processing large-scale data. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： image segmentation

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