2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)最新文献_第9页

The Pareto rank algorithm for the division of the sub arrays for the phase array radar 相控阵雷达子阵划分的Pareto排序算法

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852847

Dan Wang, Hang Hu, Zhitao Yang

引用次数: 16

A precise time-integration for analysis of time-domain response to lossy transmission lines 用于分析有耗传输线时域响应的精确时间积分法

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852874

Xiaoke Chen, Jie Zeng, Jin-quan Zhao, Zhuo Wang, Huanrui Liu

{"title":"A precise time-integration for analysis of time-domain response to lossy transmission lines","authors":"Xiaoke Chen, Jie Zeng, Jin-quan Zhao, Zhuo Wang, Huanrui Liu","doi":"10.1109/CISP-BMEI.2016.7852874","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852874","url":null,"abstract":"The precise integration method is a semi analytical solution method of partial differential equation method. Based on the precise integration method, the lossy transmission line transient response analysis method is a time domain analysis method. The lossy transmission line transient response analysis method can easily deal with the transmission line problems, which is difficult for the nonzero initial value and nonlinear load frequency domain method to deal with, but it is still difficult to deal with the reactance load of transmission line. By separating and integrating the beginning and terminal conditions of the precise integration method, and introducing time domain adjoint model of the various kinds of load, this paper solves the problems of the load reactance of transmission line, also solves the transmission line problems of long time transition, short circuit and open circuit, which greatly improves the precise integration method for the analysis of the efficacy of transmission lines in time domain response. Finally, the correctness of the presented method is illustrated by the application examples, which provide a theoretical basis for the time domain analysis of the transient response of the transmission line.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"440 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116016223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Self-adapting threshold of pulmonary parenchyma 肺实质自适应阈值

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852941

Xin-Yue Li, Fan Xu, Xiao Hu, Shao-Hu Peng, H. Nam, Jin-Ming Zhao

{"title":"Self-adapting threshold of pulmonary parenchyma","authors":"Xin-Yue Li, Fan Xu, Xiao Hu, Shao-Hu Peng, H. Nam, Jin-Ming Zhao","doi":"10.1109/CISP-BMEI.2016.7852941","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852941","url":null,"abstract":"Segmentation for pulmonary parenchyma is a crucial step for computer aided diagnosis (CAD) systems. The accuracy of pulmonary parenchyma segmentation can have a great impact on further steps of CAD systems, such as pulmonary nodule detection and feature extraction. Before segmentation, preprocessing should be done to remove references outside the thorax. After preprocessing, pulmonary parenchyma area threshold will be employed to realize segmentation. However, current segmentation approaches are mainly based on a fixed area threshold, which confronts problem of mis-segmentation and high segmentation failure rate. This article proposed a novel self-adapting threshold segmentation approach, which realized fully automatic segmentation and held considerable accuracy rate. First, fitting of polynomials based on the least square law is constructed to fit curves of pulmonary parenchyma areas. Secondly, a golden standard is created to represent change trend of pulmonary parenchyma for all patients. Finally, the golden standard is adjusted accordingly to realize full adaption and automation of segmentation. Experimental results indicated that the proposed approach achieved excellent accuracy rate and precise segmentation.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115263226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A vascular bifurcations detection method based on Transfer Learning model 一种基于迁移学习模型的血管分叉检测方法

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852746

Xiaoming Liu, Jia Wang, Zhou Yang

引用次数: 1

An efficient all-frequency environment rendering method for mixed reality 一种高效的混合现实全频环境渲染方法

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852736

Fengquan Zhang, Yujie Zhao, Zhaowei Wang, T. Lei

引用次数: 1

Camera image quality assessment without reference information 没有参考信息的摄像机图像质量评估

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852793

Lijuan Tang, Hong Lu, Ke Gu, Kezheng Sun

引用次数: 1

Online dynamic magnetic resonance imaging based on radial sampling and GPU acceleration 基于径向采样和GPU加速的在线动态磁共振成像

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852777

Xu Wang, Zhaoyang Jin

{"title":"Online dynamic magnetic resonance imaging based on radial sampling and GPU acceleration","authors":"Xu Wang, Zhaoyang Jin","doi":"10.1109/CISP-BMEI.2016.7852777","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852777","url":null,"abstract":"In many fields of MRI (Magnetic Resonance Imaging), especially in DMRI (Dynamic MRI) domain, long acquisition time often limits its clinical applications. The new online MRI technique can obviously accelerate the imaging time for DMRI based on under-sampling acquisition and sparsity performance between neighbor frames. The data acquisition of previous online MRI schemes was based on the Cartesian coordinate. Non-Cartesian sampling, such as radial sampling, can obtain higher data acquisition speed than conventional Cartesian sampling. In order to further accelerate the imaging speed for online MRI, radial under-sampling instead of Cartesian under-sampling, was proposed to shorten the data acquisition time for DMRI. However the reconstruction of non-Cartesian data is complicated and time consumed, so GPU (Graphics Processing Unit) was used to shorten the reconstruction time. In this primary study, the full sampled cardiac dataset was used as a reference dataset, radial under-sampling with 25% and 10% k-space coverage was simulated for the online imaging scheme. The results show that radial under-sampling scheme obtained higher image quality than that of Cartesian acquisition scheme, with its imaging time still satisfying online reconstruction after applying GPU acceleration.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121448083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Thickness measurements of ten intra-retinal layers from optical coherent tomography images using a super-pixels and manifold ranking approach 使用超像素和流形排序方法测量光学相干断层扫描图像中的十个视网膜内层的厚度

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852930

Zhijun Gao, Wei Bu, Xiangqian Wu, Yalin Zheng

{"title":"Thickness measurements of ten intra-retinal layers from optical coherent tomography images using a super-pixels and manifold ranking approach","authors":"Zhijun Gao, Wei Bu, Xiangqian Wu, Yalin Zheng","doi":"10.1109/CISP-BMEI.2016.7852930","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852930","url":null,"abstract":"The purposes of this paper are to calculate exactly the mean thickness, plot the thickness maps, and depict the early treatment diabetic retinopathy study (ETDRS) charts for ten intra-retinal layers by spectral domain optical coherence tomography(OCT). Using our previously the reported segmented method with a simple linear iterative clustering (SLIC) super-pixels and manifold ranking (SLIC_MR), the ten intra-retinal layers were fast and exactly segmented in 3-D OCT dataset, includes 55 B-scan images from 11 different healthy adult subjects. By our definitions of the sensitivity and specificity, we compared the segmented results with the recent graph-based method for the main layers in dataset. The experimental results demonstrated that the SLIC_MR method outperformed the graph-based method. The thickness maps were plotted in the ten intra-retinal layers and the overall layer, the ETDRS charts were depicted in the 9 sectors of each intra-retinal layer and the overall layer, and the bar graph displayed the mean and standard deviation of macular thickness in 9 sectors for ten retinal layers and the overall layer. The mean thickness of the central foveal area displayed the minimum thickness in layers 1, 2, 3, 4, 5 and the overall, and the maximum thickness in the central foveal area of the 6th layer. Both layers 4 and 5 have the similar mean thickness in each sector.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124162549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An optimal sub array partitioning method based on directed graph path search 一种基于有向图路径搜索的最优子阵列划分方法

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852891

Lian-qing Yu, Huan Zhu, Si-ming Li, Yu-Hao Yang

引用次数: 1

A robust point detection algorithm based on wavelet transform for visual tracking 基于小波变换的鲁棒视觉跟踪点检测算法

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2016-10-01 DOI: 10.1109/CISP-BMEI.2016.7852672

Rongfeng Zhang, Huanhou Xiao, Ting Deng, Wei Qiu, Jinglun Shi

{"title":"A robust point detection algorithm based on wavelet transform for visual tracking","authors":"Rongfeng Zhang, Huanhou Xiao, Ting Deng, Wei Qiu, Jinglun Shi","doi":"10.1109/CISP-BMEI.2016.7852672","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852672","url":null,"abstract":"Visual tracking is one of the hot research topics in computer vision in recent years. It has been widely used in many vision applications, such as traffic surveillance, anti-terrorism. However, there are still challenges for visual tracking, like illumination change, object occlusion, appearance deformation, etc. This paper proposes a robust point detection algorithm based on wavelet transform for visual tracking. First, the input image patch that includes the tracking object is decomposed by wavelet transform with several levels and the wavelet coefficients are obtained. The wavelet coefficients are then analyzed and the points that hold the local maximal wavelet coefficients are determined as the robust points for tracking. Finally, the proposed method is integrated to the Tracking Learning Detection (TLD) framework, which not only improves the tracking precision, but also reduces the false detection. Experimental results showed that the new algorithm outperformed the TLD method with respect to the precision, recall, and f-measure.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124526258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1