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SBIR Phase I: An Integrated Search, Analytics, and Imaging (SAI) Platform for Clinical Decision Support and Mobile Health

SBIR Phase I: An Integrated Search, Analytics, and Imaging (SAI) Platform for Clinical Decision Support and Mobile Health
SBIR 第一阶段:用于临床决策支持和移动医疗的集成搜索、分析和成像 (SAI) 平台
批准号:
1345927
负责人:
Roger Chylla
金额:
$15.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-01-01 至 2014-12-31

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中文摘要
翻译
这个小型企业创新研究(SBIR)第一阶段项目计划开发并向医疗保健企业提供新一代成像、分析和搜索解决方案,该解决方案不仅可以满足当前多企业医疗图像查看的需求,还可以满足与临床决策支持和移动医疗相关的新兴需求。该项目针对的是大数据之一。医疗成像问题,即在医疗保健企业内的任何位置提供对从功能强大的个人计算机到移动设备的各种设备的大型研究、高级成像工具和基于图像的分析的访问。该项目更广泛的影响/商业潜力是将使用定量成像生物标记物的新研究转化为实际的临床实践。医学成像通常用于癌症筛查、治疗计划和监测,但对这些图像的纯粹定性解释得出的结果并不总是确定的。最近的进展表明,从医学图像(放射组学)中高通量地提取和分析先进的定量成像特征。可用于在某些情况下提高癌症筛查的准确性和置信度。该项目的目标是将这些分析整合到一个商业可用的系统中,用于医学图像的显示和分发,这是广泛临床采用所必需的。这些进展将使医疗保健提供者能够降低与不必要的后续检查相关的成本,并通过识别更有可能对治疗产生抗药性的肿瘤来改善患者的预后,并使用医学成像更有效和准确地监测治疗反应。
英文摘要
This Small Business Innovation Research (SBIR) Phase I Project proposes to develop and deliver to health care enterprises a next generation imaging, analytics, and search solution that meets not only the current needs of multi-enterprise medical image viewing, but satisfies emerging demands related to clinical decision support and mobile health. The project addresses one of the ?Big Data? problems of medical imaging, i.e. providing access anywhere within the healthcare enterprise to large studies, advanced imaging tools, and image-based analytics across a spectrum of devices from powerful personal computers to mobile devices. The broader impact/commercial potential of this project is to translate novel research using quantitative imaging biomarkers into actual clinical practice. Medical imaging is commonly used for cancer screening, treatment planning, and monitoring but the results that come from purely qualitative interpretations of these images are not always definitive. Recent progress has shown that high-throughput extraction and analysis of advanced quantitative imaging features from medical images (?radiomics?) can be used to increase the accuracy and confidence of cancer screening in certain cases. The goals of this project are to incorporate these analytics into a commercially available system for medical image display and distribution which is necessary for widespread clinical adoption. These advances will enable health care providers to lower costs associated with unnecessary follow up exams as well as to improve patient outcomes through identification of tumors that are more likely to be resistant to treatment and to more efficiently and accurately monitor the response to treatment using medical imaging.
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