GIDAC:生物图像注释和临床数据整合的原型

P. Vizza, P. Guzzi, P. Veltri, G. Cascini, R. Curia, Loredana Sisca
{"title":"GIDAC:生物图像注释和临床数据整合的原型","authors":"P. Vizza, P. Guzzi, P. Veltri, G. Cascini, R. Curia, Loredana Sisca","doi":"10.1109/BIBM.2016.7822663","DOIUrl":null,"url":null,"abstract":"The analysis of bioimages and their correlated clinical patient information allows to investigate specific diseases and define the corresponding medical protocols. To perform a correct diagnosis and apply a precise therapy, bioimages must be collected and studied together with others relevant data as well as laboratory results, medical annotations and patient history. Today, the management of these data is performed by single systems inside hospital departments that often do not provide dedicated data integration platforms among different departments as well as different health structures to exchange of relevant clinical information. Also, images cannot be annotated or enriched by physicians to trace temporal studies for patients or even among patients with similar diseases. In this contribution, we report the results of a research project called GIDAC (standing for Gestione Integrata DAti Clinici) that aims to define a general purpose framework for the bioimages management and annotations as well as clinical data view and integration in a simple-to-use information system. The proposed framework does not substitute any existing clinical information system but is able in gathering and integrating data by using a XML-based module. The novelty also consists in allowing annotations on DICOM images by means of simple user-interface to take trace of changes intra images as well as comparisons among patients. This system supports oncologists in the management of DICOM images from different devices (e.g., ecograph or PACS) to extract relevant information necessary to query (annotate) images and study similar clinical cases.","PeriodicalId":345384,"journal":{"name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"GIDAC: A prototype for bioimages annotation and clinical data integration\",\"authors\":\"P. Vizza, P. Guzzi, P. Veltri, G. Cascini, R. Curia, Loredana Sisca\",\"doi\":\"10.1109/BIBM.2016.7822663\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The analysis of bioimages and their correlated clinical patient information allows to investigate specific diseases and define the corresponding medical protocols. To perform a correct diagnosis and apply a precise therapy, bioimages must be collected and studied together with others relevant data as well as laboratory results, medical annotations and patient history. Today, the management of these data is performed by single systems inside hospital departments that often do not provide dedicated data integration platforms among different departments as well as different health structures to exchange of relevant clinical information. Also, images cannot be annotated or enriched by physicians to trace temporal studies for patients or even among patients with similar diseases. In this contribution, we report the results of a research project called GIDAC (standing for Gestione Integrata DAti Clinici) that aims to define a general purpose framework for the bioimages management and annotations as well as clinical data view and integration in a simple-to-use information system. The proposed framework does not substitute any existing clinical information system but is able in gathering and integrating data by using a XML-based module. The novelty also consists in allowing annotations on DICOM images by means of simple user-interface to take trace of changes intra images as well as comparisons among patients. This system supports oncologists in the management of DICOM images from different devices (e.g., ecograph or PACS) to extract relevant information necessary to query (annotate) images and study similar clinical cases.\",\"PeriodicalId\":345384,\"journal\":{\"name\":\"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2016.7822663\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2016.7822663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

摘要

生物图像及其相关临床患者信息的分析允许调查特定疾病并确定相应的医疗方案。为了进行正确的诊断和应用精确的治疗,必须收集生物图像并与其他相关数据以及实验室结果、医学注释和患者病史一起研究。目前,这些数据的管理是由医院部门内部的单一系统完成的,这些系统往往没有在不同部门和不同医疗机构之间提供专用的数据集成平台来交换相关的临床信息。此外,医生无法对图像进行注释或丰富,以追踪患者甚至患有类似疾病的患者的时间研究。在这篇文章中,我们报告了一个名为GIDAC (Gestione Integrata DAti Clinici)的研究项目的结果,该项目旨在定义一个通用框架,用于生物图像管理和注释,以及临床数据视图和集成在一个简单易用的信息系统中。该框架不替代任何现有的临床信息系统,而是能够使用基于xml的模块收集和集成数据。其新颖之处还在于允许通过简单的用户界面对DICOM图像进行注释,以跟踪图像内的变化以及患者之间的比较。该系统支持肿瘤学家管理来自不同设备(如ecograph或PACS)的DICOM图像,以提取查询(注释)图像和研究类似临床病例所需的相关信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GIDAC: A prototype for bioimages annotation and clinical data integration
The analysis of bioimages and their correlated clinical patient information allows to investigate specific diseases and define the corresponding medical protocols. To perform a correct diagnosis and apply a precise therapy, bioimages must be collected and studied together with others relevant data as well as laboratory results, medical annotations and patient history. Today, the management of these data is performed by single systems inside hospital departments that often do not provide dedicated data integration platforms among different departments as well as different health structures to exchange of relevant clinical information. Also, images cannot be annotated or enriched by physicians to trace temporal studies for patients or even among patients with similar diseases. In this contribution, we report the results of a research project called GIDAC (standing for Gestione Integrata DAti Clinici) that aims to define a general purpose framework for the bioimages management and annotations as well as clinical data view and integration in a simple-to-use information system. The proposed framework does not substitute any existing clinical information system but is able in gathering and integrating data by using a XML-based module. The novelty also consists in allowing annotations on DICOM images by means of simple user-interface to take trace of changes intra images as well as comparisons among patients. This system supports oncologists in the management of DICOM images from different devices (e.g., ecograph or PACS) to extract relevant information necessary to query (annotate) images and study similar clinical cases.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信