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A REVIEW ON ARTERY WALL SEGMENTATION TECHNIQUES AND INTIMA-MEDIA THICKNESS MEASUREMENT FOR CAROTID ULTRASOUND IMAGES

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Journal of Innovative Optical Health Sciences 2012年第1期5卷 75-84页

作者： XIN YANG WANJI HE KAITONG LI JIAOYING JIN XUMING ZHANG MING YUCHI MINGYUE DING State Key Laboratory for Multi-Spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI)Huazhong University of Science and Technology Wuhan 430074HubeiChina Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074HubeiChina

Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and *** is important for the early stage diagnosis and monitoring medical intervention of the *** stenosis is a classical atherosclerotic lesion with vessel wall narrowing down and accumulating plaques *** carotid artery of intima-media thickness(IMT)is a key indicator to the *** the development of computer assisted diagnosis technology,the imaging techniques,segmentation algorithms,measurement methods,and evaluation tools have made considerable *** imaging,being real-time,economic,reliable,and safe,now seems to become a standard in vascular assessment methodology especially for the measurement of *** review firstly attempts to discuss the clinical relevance of measurements in clinical practice at first,and then followed by the challenges that one has to face when approaching the segmentation of ultrasound ***,the commonly used methods for the IMT segmentation and measurement are ***,discussion and evaluation of different segmentation techniques are *** overview of summary and future perspectives is given finally.

关键词： Ultrasound(US)images carotid artery intima-media thickness(IMT) atherosclerosis image segmentation computer assisted diagnosis(CAD)

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Machine learning techniques and chi-square feature selection for cancer classification using SAGE gene expression profiles

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PAKDD 2006 Workshop on Data Mining for Biomedical Applications, BioDM 2006

作者： Jin, Xin Xu, Anbang Bie, Rongrang Guo, Ping College of Information Science and Technology Beijing Normal University Beijing 100815 China Image Processing and Pattern Recognition Laboratory Beijing Normal University

ISBN: (纸本)3540331042

Recently developed Serial Analysis of Gene Expression (SAGE) technology enables us to simultaneously quantify the expression levels of tens of thousands of genes in a population of cells. SAGE is better than Microarray in that SAGE can monitor both known and unknown genes while Microarray can only measure known genes. SAGE gene expression profiling based cancer classification is a better choice since cancers may be due to some unknown genes. Whereas a wide range of methods has been applied to traditional Microarray based cancer classification, relatively few studies have been done on SAGE based cancer classification. In our study we evaluate popular machine learning methods (SVM, Naive Bayes, Nearest Neighbor, C4.5 and RIPPER) for classifying cancers based on SAGE data. In order to deal with the high dimensional problem, we propose to use Chi-square for tag/gene selection. Both binary classification and multicategory classification are investigated. The experiments are based on two human SAGE datasets: brain and breast. The results show that SVM and Naive Bayes are the top-performing SAGE classifiers and that Chi-square based gene selection can improve the performance of all the five classifiers investigated. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Biotechnology

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Formal Photograph Compression Algorithm Based on Object Segmentation

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International Journal of Automation and computing 2008年第3期5卷 276-283页

作者： Li Zhu Guo-You Wang Chen Wang Laboratory. for Biomedical Image Processing Institute for Pattern Recognition ＆ Artificial Intelligence Huazhong University of Science ＆ Technology Wuhan 430074 PRC School of Mechanical and Aeropace Engineering Nanyang Technological Vnlversity Sigapore 639798 Sigapore

Small storage space for photographs in formal documents is increasingly necessary in today＇s needs for huge amounts of data communication and storage. Traditional compression algorithms do not sufficiently utilize the distinctness of formal photographs. That is, the object is an image of the human head, and the background is in unicolor. Therefore, the compression is of low efficiency and the image after compression is still space-consuming. This paper presents an image compression algorithm based on object segmentation for practical high-efficiency applications. To achieve high coding efficiency, shape-adaptive discrete wavelet transforms are used to transformation arbitrarily shaped objects. The areas of the human head and its background are compressed separately to reduce the coding redundancy of the background. Two methods, lossless image contour coding based on differential chain, and modified set partitioning in hierarchical trees （SPIHT） algorithm of arbitrary shape, are discussed in detail. The results of experiments show that when bit per pixel （bpp）is equal to 0.078, peak signal-to-noise ratio （PSNR） of reconstructed photograph will exceed the standard of SPIHT by nearly 4dB.

关键词： Image compression object segmentation lossless image contour coding differential chain set partitioning in hierarchical trees (SPIHT) coding of arbitrarily shaped object.

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Adaptive synthetic aperture radar image enhancement

Adaptive synthetic aperture radar image enhancement

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MIPPR 2009 - Multispectral Image Acquisition and processing: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Cheng, Hua Tian, Jinwen Huazhong University of Science and Technology Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies China

ISBN: (纸本)9780819478054

An adaptive SAR image enhancement method is presented for reducing the speckle noise and increasing the contrast of synthetic aperture radar (SAR) images. First, a fuzzy logic based filter, employing fuzzy edge to weight the contributions of pixel values in filter window, is used to filter the speckles. Second, the original SAR image is decomposed into lowfrequency component and high-frequency component. The fuzzy filtered image is viewed as the low-frequency component, and the contrast limited adaptive histogram equalization algorithm is used to increase its contrast. The highfrequency component is obtained by subtracting the low-frequency component from the original image, and its gain is controlled by fuzzy structural which employed to express the degree of a pixel belonging to structures. After processed one after the other, the two components are added together to form the final enhanced SAR image. Experimental results show the excellent effect of the proposed method by visual observation and numerical measurement. Many fine structures and little speckle noise can be seen from the enhanced SAR images. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Image enhancement

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Imaging lidar based 3D terrain matching using feature vector

Imaging lidar based 3D terrain matching using feature vector

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MIPPR 2007: Multispectral Image processing

作者： Hua, Cheng Jinwen, Tian Jie, Ma Junbin, Gong Lin, Wu State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

ISBN: (纸本)9780819469519

A novel 3D terrain matching algorithm is presented in this paper. A terrain feature vector map (FVM), composed of local mean and local gradient, is employed to represent the terrain elevation map (TEM). Compared with traditional matching algorithm using the magnitude of gradient to match, the new algorithm uses each component of the gradient vector to match individually, and it is able to generate two interim matching positions. Different from traditional matching algorithms which usually estimate an optimum matching position under some criterions at the end, the new algorithm fused the two interim matching positions to generate a final matching position or refuse to position in order to increase the matching confidence, which is very important because it is hardly acceptable to employ a mismatched position to correct the error of Inertial Navigation System (INS). Due to the stability of terrain and the high-precision of lidar ranging, the mean of a sensed terrain elevation map (STEM) sized terrain is quite stable. So it is bestowed to accelerate the matching process and to reduce mismatches at different terrain heights. Compared with other mismatch-eliminated methods based on neural network (NN) or support vector machine (SVM), the new method do not need training samples and is more stable and robust. Experimental results show that the proposed algorithm is effective and robust.

关键词： pattern matching

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Change detection in remote sensing imagery based on multisimilarity measures fusion

Change detection in remote sensing imagery based on multisim...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Huang, Weilin Yang, Weidong National Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

Detecting regions of change in multitemporal remote-sensing images of the same scene taken at different times is of widespread interest in recent years. In this paper, we propose a new change detection method based on a fusion of multisimilarity measures. This fusion is performed in the framework of the Dempster-Shafer evidence theory, which allows you to combine evidence from different sources and arrive at a degree of belief (represented by a belief function) that takes into account all the available evidence. The proposed algorithm is applied to airport change evaluation based on two popular Gray-textural similarity measures: grayscale difference and grayscale ratio. Experimental results confirm the effectiveness of the proposed method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Uncertainty analysis

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Semi-supervised Kernel Minimum Squared Error based on manifold structure

Semi-supervised Kernel Minimum Squared Error based on manifo...

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10th International Symposium on Neural Networks, ISNN 2013

作者： Gan, Haitao Sang, Nong Chen, Xi Science and Technology on Multi-spectral Information Processing Laboratory Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology 430074 China

ISBN: (纸本)9783642390647

Kernel Minimum Squared Error (KMSE) has been receiving much attention in data mining and pattern recognition in recent years. Generally speaking, training a KMSE classifier, which is a kind of supervised learning, needs sufficient labeled examples. However, there are usually a large amount of unlabeled examples and few labeled examples in real world applications. In this paper, we introduce a semi-supervised KMSE algorithm, called Laplacian regularized KMSE (LapKMSE), which explicitly exploits the manifold structure. We construct a p nearest neighbor graph to model the manifold structure of labeled and unlabeled examples. Then, LapKMSE incorporates the structure information of labeled and unlabeled examples in the objective function of KMSE by adding a Laplacian regularized term. As a result, the labels of labeled and unlabeled examples vary smoothly along the geodesics on the manifold. Experimental results on several synthetic and real-world datasets illustrate the effectiveness of our algorithm. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Supervised learning

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Prototype-guided Unsupervised Domain Adaptation for Semantic Segmentation

Prototype-guided Unsupervised Domain Adaptation for Semantic...

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2023 IEEE International Conference on Control, Electronics and Computer Technology, ICCECT 2023

作者： Xia, Shaoqi Huang, Hua Li, Qishen He, Yifan Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition School of Information Engineering Jiangxi Nanchang China Nanchang Hangkong University School of Information Engineering Nanchang China Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition School of Software Nanchang China

ISBN: (纸本)9798350399028

Semantic segmentation is one of the most important research directions in the field of computer vision, and has a wide range of applications for autonomous driving, medical imaging, intelligent security, etc. Unsupervised domain adaptation is the mainstream research topic in recent years, which can use a large number of labeled source samples to complete the segmentation task in target domain without labeled target samples. In this paper, we propose a prototype-guided unsupervised domain adaptation for semantic segmentation based on ProDA model. Due to lacking of labeled target samples and the prior probability, a prototype distance loss based on target domain is proposed to optimize the distribution of features by measuring the distance between features and the updated prototype and designing an adaptive threshold strategy. Meanwhile, a smoothing loss is proposed to alleviate the impact of source samples on our model and improve the prediction performance of the network. By conducting experiments on the GTA5 to Cityscapes scenarios, the results show that compared with the original model, the loss optimization improves mIoU by1.52. © 2023 IEEE.

关键词： Semantic Segmentation

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3D model retrieval using density-based silhouette descriptor

3D model retrieval using density-based silhouette descriptor

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2nd International Conference on pattern recognition Applications and Methods, ICPRAM 2013

作者： Tang, Qi Yang, Xin Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

ISBN: (纸本)9789898565419

In this paper we present a new content-based retrieval descriptor, density-based silhouette descriptor (DBS). It characterizes a 3D object with multivariate probability functions of its 2D silhouette features. The new descriptor is computationally efficient and induces a permutation property that guarantees invariance at the matching stage. Also, it is insensitive to small shape perturbations and mesh resolution. The retrieval performance on several 3D databases shows that the DBS provides state-of-art discrimination over a broad and heterogeneous set of shape categories.

关键词： Probability density function

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Adaptive tracking method for ground target of FLIR imaging

Adaptive tracking method for ground target of FLIR imaging

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MIPPR 2009 - Automatic Target recognition and Image Analysis: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Li, Yun Zhang, Tianxu Zuo, Zhengrong Wan, Meijun State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478061

An adaptive tracking method for ground target in FLIR image including centric and eccentric tracking is presented in this paper. The eccentric tracking is adopted to assist ATR or manual target acquisition by stabilizing the light axis of the seeker. The tracking adaptability detection at the start of centric tracking avoids tracking bad locked point and decreases the shift, slide and jump in the subsequent tracking. Combination of periodic template-updating based on scale variance rate and interruptive template-updating based on supervision of tracking point enhances the adaptability of tracking template. Supervision, modification of current tracking point and the combination of direct and indirect tracking increase the stability of tracking system. The multi-scale and size-variable template is adopted to fit the variable target scale. The detection and adoption of occlusion mask increase the accuracy of the tracking system. The hardware system based on multi-DSP takes a real-time parallel processing. The trial results show that this method is efficient to reduce the possibility of shift, slide, and jump in ground target tracking comparing with the traditional correlation tracking method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Target tracking

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