2013 6th International Conference on Biomedical Engineering and Informatics最新文献_第9页

Global visual cognition based on visual imagery and its mental connectivity 基于视觉意象及其心理连通性的全局视觉认知

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6746910

S. Xiao, Xiaoxing Liu

引用次数: 0

A Kinect based gesture recognition algorithm using GMM and HMM 基于Kinect的基于GMM和HMM的手势识别算法

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6747040

Yang Song, Yu Gu, Peisen Wang, Yuanning Liu, A. Li

引用次数: 27

Automatic characterization of masses in mammograms 乳房x光检查中肿块的自动表征

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6746917

Jayasree Chakraborty, A. Midya, S. Mukhopadhyay, A. Sadhu

引用次数: 19

Generalized function projective synchronization of weighted cellular neural networks with multiple time-varying coupling delays 多时变耦合时滞加权细胞神经网络的广义函数投影同步

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6747042

Xiangqian Gao, Guoliang Cai, Shuiming Cai

引用次数: 2

Predictive model for minimal hepatic encephalopathy based on cerebral functional connectivity 基于脑功能连通性的最小肝性脑病预测模型

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6747000

Y. Jiao, G. Teng, Xunheng Wang

{"title":"Predictive model for minimal hepatic encephalopathy based on cerebral functional connectivity","authors":"Y. Jiao, G. Teng, Xunheng Wang","doi":"10.1109/BMEI.2013.6747000","DOIUrl":"https://doi.org/10.1109/BMEI.2013.6747000","url":null,"abstract":"Minimal hepatic encephalopathy (MHE) is a common neurocognitive complication of liver cirrhosis, which have few recognizable clinical symptoms. Previous functional magnetic resonance imaging (fMRI) studies have found that widespread cortical and subcortical functional connectivity (FC) changes were significantly in patients with MHE. The goals of this study were twofold: 1) to construct predictive models for MHE, based on brain regional functional connectivity, 2) and to test feature selection method on p-value ranker based kernel principle component analysis (kPCA). Our study included thirty-two cirrhotic patients with MHE and twenty age-, gender-, and eduction-matched healthy controls. Using 1.5T MR, we obtained resting-state fMRI for each subject. Functional connectivities between 116 pairs of brain regions in patients with MHE were compared with those in control participants. Then, p-value ranker based kPCA was applied in feature selection step to reduce the dimension of input data. The best parameters of feature selection were chose based on 10-fold cross-validation of vector machines (SVMs). Finally, We found FC-based diagnostic model was accurate in differing MHE from normal controls with 86.5% accuracy, 88% specifity and 85% sensitivity.","PeriodicalId":163211,"journal":{"name":"2013 6th International Conference on Biomedical Engineering and Informatics","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127304817","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: 0

Nonrigid registration for evaluating locoregional therapy of hepatocellular carcinoma 评价肝细胞癌局部治疗的非刚性登记

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6747052

Chunhua Dong, T. Seki, Ryosuke Inoguchi, Chen-Lun Lin, X. Han, Yenwei Chen

{"title":"Nonrigid registration for evaluating locoregional therapy of hepatocellular carcinoma","authors":"Chunhua Dong, T. Seki, Ryosuke Inoguchi, Chen-Lun Lin, X. Han, Yenwei Chen","doi":"10.1109/BMEI.2013.6747052","DOIUrl":"https://doi.org/10.1109/BMEI.2013.6747052","url":null,"abstract":"The assessment of the treated margin with locoregional therapy (LT), for hepatocellular carcinoma (HCC), is the common method for predicting HCC recurrence in most hospital. However, tumors sometimes cannot be removed clearly with LT in limited conditions. The therapeutic efficiency of HCC is often evaluated by comparing 2D fusion images of computed tomography (CT) or magnetic resonance imaging (MRI) between the preoperation and the postoperation. However, judgment about whether the tumors exist in the treated margin after LT by using 2D slices sometimes is difficult. It is desirable to develop a suitable image registration algorithm to automatically align the two volumes in order to transform the treated margin of the postoperative volume to the tumor of the preoperative volume to assess the therapeutic efficiency after treatment of HCC. With taking these into consideration, this paper proposed an automatic 3D fusion imaging approach for medical image by using the nonrigid registration method that aligning an ablative margin - that is the treated margin after LT, onto the locations of HCC. In our registration algorithm, a rigid global transformation combined with localized B-spline is used to estimate the significant nonrigid motions of the liver between before and after LT. Our proposed approach can ensure the feasibility, the accuracy and the efficacy to assess the treated margin for HCC. Furthermore, this method can be adapted to register multi-modality medical images. We demonstrate the effectiveness of our proposed method by comparing the difference criterions of fusion evaluation on medical images. The results clearly indicate that our method extremely useful in the evaluation of the treated margin, in addition, it remain the motion and local deformation of the volume.","PeriodicalId":163211,"journal":{"name":"2013 6th International Conference on Biomedical Engineering and Informatics","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130638630","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

Recognition of microRNA-binding sites in proteins from sequences using Laplacian Support Vector Machines with a hybrid feature 基于混合特征的拉普拉斯支持向量机识别蛋白质序列中的microrna结合位点

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6746990

Jiansheng Wu, Wei Han, Dong Hu, Xin Xu, Shancheng Yan, L. Tang

引用次数: 1

Sparse model in hierarchic spatial structure for food image recognition 层次空间结构中的稀疏模型用于食品图像识别

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6747060

R. Kusumoto, X. Han, Yenwei Chen

{"title":"Sparse model in hierarchic spatial structure for food image recognition","authors":"R. Kusumoto, X. Han, Yenwei Chen","doi":"10.1109/BMEI.2013.6747060","DOIUrl":"https://doi.org/10.1109/BMEI.2013.6747060","url":null,"abstract":"Recent year, with the increasing of unhealthy diets which will threaten people's life due to the various resulted risks such as heart stroke, liver trouble and so on, the remain for healthy life has attracted much attention and then how to manage the dietary life is becoming more and more important. In this research, we aim to construct a auto-recognition system of food images and keep the daily food-log records which will contribute to manage dietary life. With the easily available food images taken by mobile phone, it prospects to give the insight about the daily dietary of users with our constructed food recognition system. In order to achieve the acceptable recognition performance of the food images, we propose to apply a sparse model for coding a local descriptor extracted from the food images. Sparse coding: an extension of vector quantization for local descriptors, which is popularly used in Bag-of-Features (BoF) for image representation in generic object recognition, can represent the local descriptors more efficient, and then abtain more discriminant feature for food image representation. Moreover, in order to introduce spatial information, a hierarchic spatial structure is explored to extract the feature based sparse model. Experiments validate that the proposed strategy can greatly improve the recognition rates compared with the conventional BOF model on two databases: our constructed RFID and the public PFID.","PeriodicalId":163211,"journal":{"name":"2013 6th International Conference on Biomedical Engineering and Informatics","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132117247","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

A neural network technique for feature selection and identification of obstructive sleep apnea 阻塞性睡眠呼吸暂停特征选择与识别的神经网络技术

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6746930

A. Hossen

引用次数: 3

Teeth segmentation via semi-supervised learning 基于半监督学习的牙齿分割

2013 6th International Conference on Biomedical Engineering and Informatics Pub Date : 2013-12-01 DOI: 10.1109/BMEI.2013.6747003

Yonghui Gao, Xiaoxiao Li

引用次数: 2