2014 IEEE 27th International Symposium on Computer-Based Medical Systems最新文献_第6页

Mobili-T: A Mobile Swallowing-Therapy Device: An Interdisciplinary Solution for Patients with Chronic Dysphagia Mobili-T:移动吞咽治疗设备:慢性吞咽困难患者的跨学科解决方案

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.47

G. Constantinescu, Eleni Stroulia, J. Rieger

引用次数: 2

Computer Aided Medical Diagnosis Tool to Detect Normal/Abnormal Studies in Digital MR Brain Images 计算机辅助医学诊断工具检测数字MR脑图像的正常/异常研究

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.110

J. C. Gutiérrez-Cáceres, Christian E. Portugal-Zambrano, C. B. Castañón

{"title":"Computer Aided Medical Diagnosis Tool to Detect Normal/Abnormal Studies in Digital MR Brain Images","authors":"J. C. Gutiérrez-Cáceres, Christian E. Portugal-Zambrano, C. B. Castañón","doi":"10.1109/CBMS.2014.110","DOIUrl":"https://doi.org/10.1109/CBMS.2014.110","url":null,"abstract":"This work presents a model to support medical diagnosis through the classification of abnormality normality in medical brain images, in order to help to specialist as a previous step in the brain pathology diagnosis. Our proposal was incorporated into a content-based image retrieval system, thus we developed a useful tool for radiologists. The first step produces the features vector of MR image using Gabor Filter for the data train and test, then as second step features vector of training data are indexed into CBIR module. The third step makes the training of SVM and as four step the test dataset is classified with the SVM trained. Finally, the result of classification are presented with a set of similar images product of a KNN query. This model was implemented as a software tool with graphical interface. We obtained 94.12% of correct classification. Our medical image dataset is composed of 187 MRI images collected from a medical diagnosis company and selected by medical specialist. The result shows that the proposed model is robust and effective as a software tool to aid support to medical diagnostic.","PeriodicalId":398710,"journal":{"name":"2014 IEEE 27th International Symposium on Computer-Based Medical Systems","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130921306","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: 8

Linking Clinicians to Biomedical Researchers: An Application of the ISF Ontology at Stony Brook Medicine 将临床医生与生物医学研究人员联系起来:ISF本体在石溪医学院的应用

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.111

J. Hajagos, Viviktesh Agwan

引用次数: 1

Multidisciplinary Work Practices: A Comparison of Three Major European Hospitals 多学科工作实践:欧洲三大医院的比较

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.14

B. Kane, K. Groth

引用次数: 3

A Bibliometrics Review of CBMS Symposiums Papers from 1993 Till 2013 1993 - 2013年CBMS会议文献计量学综述

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.90

P. Kokol, M. Zorman, Bojan Žlahtič, Grega Zlahtic, H. Blazun

引用次数: 0

Discovering Differentially Expressed Genes in Yeast Stress Data 在酵母胁迫数据中发现差异表达基因

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.127

António Gonçalves, I. Ong, Jeffrey A. Lewis, V. S. Costa

引用次数: 0

MedInject: A General-Purpose Information Retrieval Framework Applied in a Medical Context 医学对象:应用于医学语境的通用信息检索框架

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.20

Luiz Olmes Carvalho, Enzo Seraphim, Thatyana F. P. Seraphim, A. Traina, C. Traina

{"title":"MedInject: A General-Purpose Information Retrieval Framework Applied in a Medical Context","authors":"Luiz Olmes Carvalho, Enzo Seraphim, Thatyana F. P. Seraphim, A. Traina, C. Traina","doi":"10.1109/CBMS.2014.20","DOIUrl":"https://doi.org/10.1109/CBMS.2014.20","url":null,"abstract":"The continuous improvement of medical software and instrumentation have contributed to generate large amounts of medical image data. Thus, plenty of Content-Based Image Retrieval systems have emerged in order to index and retrieve images according to similarity criteria. Some of those systems are applied in very specific domains, such as mammography, lung or spine exams. Others, however, are general-purpose applications that can be adopted in a medical environment. In such context, we realized those specific systems could benefit from the facilities brought by generic frameworks and propose our solution. This article presents a novel information retrieval core framework that performs both indexing and similarity search operations over medical image data sets. The framework follows a modular architecture based on Design Patterns and can be easily extended, allowing to other system developers to take advantages of its functions by using the provided interfaces. We performed extensive experiments evaluating several of its properties and target abstractions using medical real data, and show that it allows the implementation to achieve proper similarity retrieval and significant performance improvements in relation to the existing alternatives.","PeriodicalId":398710,"journal":{"name":"2014 IEEE 27th International Symposium on Computer-Based Medical Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134360811","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

Social-Spider Optimization-Based Artificial Neural Networks Training and Its Applications for Parkinson's Disease Identification 基于社会蜘蛛优化的人工神经网络训练及其在帕金森病识别中的应用

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.25

Luís A. M. Pereira, D. Rodrigues, Patricia B. Ribeiro, J. Papa, S. Weber

引用次数: 41

A Laboratory-Targeted, Data Management and Processing System for the Early Detection Research Network 面向实验室的早期检测研究网络数据管理与处理系统

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.139

R. Verma, Andrew F. Hart, C. Mattmann, D. Crichton, H. Kincaid, S. Kelly, M. Joyce, P. Zimdars, D. Tabb, Jay D. Holman, Matthew Chambers, K. Anton, M. Colbert, C. Patriotis, S. Srivastava

{"title":"A Laboratory-Targeted, Data Management and Processing System for the Early Detection Research Network","authors":"R. Verma, Andrew F. Hart, C. Mattmann, D. Crichton, H. Kincaid, S. Kelly, M. Joyce, P. Zimdars, D. Tabb, Jay D. Holman, Matthew Chambers, K. Anton, M. Colbert, C. Patriotis, S. Srivastava","doi":"10.1109/CBMS.2014.139","DOIUrl":"https://doi.org/10.1109/CBMS.2014.139","url":null,"abstract":"The National Institutes of Health (NIH), National Cancer Institute's Early Detection Research Network (EDRN) is a cross-institutional collaborative initiative seeking to accelerate the clinical application of cancer biomarker research. Over the past decade, it has been our role, as EDRN's Informatics Center (IC), to develop a comprehensive information services infrastructure as well as a set of software tools and services to support this overall initiative. We have recently developed a novel application called the Laboratory Catalog and Archive Service (LabCAS) whose focus is to extend EDRN IC data management and processing capabilities to EDRN laboratories. By leveraging the same technologies used to manage and process NASA Earth and Planetary data sets, we offer EDRN researchers an effective way of managing their laboratory data. More specifically, LabCAS enables EDRN researchers to reliably archive their experimental data, to optionally share these data in a controlled manner with other researchers, and to gain insight into these data through highly configurable data analysis pipelines tailored to the broad range of biomarker related experiments. This particular collaboration leverages expertise from NASA's Jet Propulsion Laboratory, Vanderbilt University Medical Center, and Dartmouth Medical School, as well as builds upon existing cross-governmental collaboration between NASA and the NIH.","PeriodicalId":398710,"journal":{"name":"2014 IEEE 27th International Symposium on Computer-Based Medical Systems","volume":"21 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116580781","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

Non-contact Sensation Screening of Diabetic Foot Using Low Cost Infrared Sensors 利用低成本红外传感器对糖尿病足进行非接触式感觉筛选

2014 IEEE 27th International Symposium on Computer-Based Medical Systems Pub Date : 2014-05-27 DOI: 10.1109/CBMS.2014.99

Greg Iven, V. Chekh, S. Luan, A. Mueen, P. Soliz, Wenyao Xu, M. Burge

引用次数: 13