2011 IEEE International Symposium on IT in Medicine and Education最新文献_第8页

An improved prefixspan algorithm research for sequential pattern mining 序列模式挖掘中一种改进的前缀跨度算法研究

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6130794

Pei-yu Liu, W. Gong, Xian Jia

引用次数: 9

Hierarchy model of influencing factors of online shopping 网络购物影响因素的层次模型

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6130892

Li Guo

引用次数: 4

Computer major training model of engineering education based on CDIO 基于CDIO的工程教育计算机专业人才培养模式

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6132146

Lanlan Kang, Wenliang Cao

引用次数: 1

The reason and self-adjustment of college teachers' psychological pressure under the background of IT in education 教育信息化背景下高校教师心理压力的成因及自我调适

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6130830

Xiaoying Wang, Lijie Wang

引用次数: 3

Training investigation of hospital nurses on disaster nursing 医院护士灾害护理培训调查

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6132076

Zhang Mengna, Yuan Guilin, Cheng Su, Zeng Jingxiang, Zheng Yijin, Shi Chongqing

引用次数: 2

Web-based open environment for foreign language teaching 基于网络的开放式外语教学环境

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6130787

Yang Xu

引用次数: 1

Multi-stage comprehensive evaluation model on low-carbon ecological mining construction 低碳生态矿山建设多阶段综合评价模型

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6132171

Chunhua Xin, Jing Wu, Jinyu Zhao

引用次数: 1

Intelligent brain hemorrhage diagnosis system 智能脑出血诊断系统

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6132126

U. Balasooriya, M. Perera

{"title":"Intelligent brain hemorrhage diagnosis system","authors":"U. Balasooriya, M. Perera","doi":"10.1109/ITIME.2011.6132126","DOIUrl":"https://doi.org/10.1109/ITIME.2011.6132126","url":null,"abstract":"Diagnosing brain hemorrhage, which is a condition caused by a brain artery busting and causing bleeding is currently done by medical experts using a CT scan. Periodic examination of scans enable the accurate prediction of disease and the extraction of reliable and robust measurement for patients in order to describe the morphological changes in the brain as the recovery progresses. Prior attempts to use medical image processing techniques to extract relevant information from a CT scan has shortcoming due to the low accuracy level in the current methods and algorithms, coding complexity of the developed approaches, impracticability in the real environment, and lack of other enhancements which may make the system more interactive and useful. This research investigates the possibility of diagnosing brain hemorrhage using an image segmentation of CT scan images using watershed method, feeding of the appropriate inputs extracted from the brain CT image to an artificial neural network for classification. The output generated as the type of brain hemorrhages, can be used to verify expert diagnosis and also as learning tool for trainee radiologists to narrow down the errors in current methods.","PeriodicalId":170838,"journal":{"name":"2011 IEEE International Symposium on IT in Medicine and Education","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121904652","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

Inter-regional gray matter correlation changes in normal aging 正常衰老中区域间灰质相关性的变化

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6132033

Cuicui Pan, Shuyu Li, F. Pu, Haijun Niu, Deyu Li, Yubo Fan

{"title":"Inter-regional gray matter correlation changes in normal aging","authors":"Cuicui Pan, Shuyu Li, F. Pu, Haijun Niu, Deyu Li, Yubo Fan","doi":"10.1109/ITIME.2011.6132033","DOIUrl":"https://doi.org/10.1109/ITIME.2011.6132033","url":null,"abstract":"The human brain undergoes many age-related changes, such as the atrophy of brain volume, the thinner of cortical thickness, the loose of white matter and so on. Here we aimed to explore whether the covariance existed among the regional gray matter volume with aging. 169 brain magnetic resonance images (MRI) of healthy people (54 males and 115 females, 18 to 92 years) were selected from OASIS database. Firstly, we computed each regional gray matter volume using atlas-based registration method, and then we investigated the correlations with age between any two regions. We found that all 90 gray matter regions in whole brain decreased with age. In 4005 (90*89/2) pairs connections, 54 pairs were significantly (p<0.005) related with age. And in which, 24 pairs belonged to the regular connections between the left and right hemispheres. In other 30 pairs, 9 long-range connections between fronto-occipital, fronto-parietal and temporal-parietal regions were found to be impaired with age. We concluded that brain shrinkage was widespread and showed different rates in different regions. The volume of the frontal gyrus showed the fastest reduction. The covariations between inter-regional gray matter volumes may be related to various reduction rates of different regions.","PeriodicalId":170838,"journal":{"name":"2011 IEEE International Symposium on IT in Medicine and Education","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121573960","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

The data mining model of physical factors based on neural network and polymerization of association rules 基于神经网络和聚合关联规则的物理因素数据挖掘模型

2011 IEEE International Symposium on IT in Medicine and Education Pub Date : 2011-12-01 DOI: 10.1109/ITIME.2011.6132030

Qi-yu Jiang, Xiao-sheng Sun

引用次数: 0