Cloud-computer-aided diagnostic imaging decision support system

云计算机辅助影像诊断决策支持系统

基本信息

  • 批准号:
    8276007
  • 负责人:
  • 金额:
    $ 36.16万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2012
  • 资助国家:
    美国
  • 起止时间:
    2012-07-01 至 2016-04-30
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): High-performance cloud computing (HPCC) is an integration of high-performance computing (HPC) with cloud computing that provides an alternative informatics infrastructure to deliver the supercomputer power needed for developing and reading high quality, multidimensional diagnostic images on desktop or mobile devices. Such infrastructure would advance the use of high-throughput cancer screening like virtual colonoscopy (VC), also known as computed tomography colonography (CTC). The goals of this proposal are to develop and validate the clinical benefits of a mobile HPCC-Virtual Colonoscopy decision support system (HPCC-VC) that integrates novel high-performance electronic cleansing and computer-aided detection schemes. The combination of high performance electronic cleansing (hpEC) with high performance computer aided detection (hpCAD) will allow visualization of the entire mucosal surface of the colon without artifact. Specifically, we hypothesize that the mobile HPCC-VC system will improve the quality of electronic cleansing of non-cathartic CTC (ncCTC) images, will deliver images 100 times faster than conventional approaches, and will improve reader performance in the detection of colonic lesions in the images analyzed on mobile high-resolution display devices. To achieve these goals, an HPCC platform will be established by use of a CPU-cluster-based supercomputing and parallel image processing libraries. Then, an hpEC scheme will be developed that effectively removes the residual fecal materials in ncCTC images. In parallel, a high-resolution hpCAD scheme will be developed to support high-performance detection of colonic lesions in ncCTC. These schemes will be integrated into a mobile HPCC-VC system on the HPCC platform. Necessary preliminary studies in the development of computed EC and CAD schemes show promise; and the development and deployment of the HPCC platform will advance the quality, speed, and utility of high performance, multidimensional imaging for colon cancer screening. A comprehensive reader performance study will be conducted to determine the clinical application and benefit of images analyzed and delivered through an HPCC platform. Successful development of HPCC-VC will demonstrate the clinical benefit of the platform for improved diagnostic imaging and facilitation of accurate, high-throughput colon cancer screening that is highly acceptable to patients. In the longer term, broad adoption and use of the HPCC-VC system will facilitate early and accurate diagnoses, and thus reduce mortality from colon cancer. PUBLIC HEALTH RELEVANCE: Successful development of the HPCC-VC system will demonstrate the clinical benefit of HPCC platform for diagnostic imaging, and will provide a high-throughput colon cancer screening scheme for colorectal lesions that is highly acceptable to patients and highly accurate. Such a system will promote the early diagnosis of colon cancer, and ultimately reduce the mortality due to colon cancer.
描述(由申请人提供):高性能云计算(HPCC)是高性能计算(HPC)与云计算的集成,其提供替代信息学基础设施,以提供在台式或移动的设备上开发和阅读高质量多维诊断图像所需的超级计算机能力。这种基础设施将促进高通量癌症筛查的使用,如虚拟结肠镜检查(VC),也称为计算机断层扫描结肠成像(CTC)。本提案的目标是开发和验证移动的HPCC-虚拟结肠镜检查决策支持系统(HPCC-VC)的临床受益,该系统集成了新型高性能电子清洗和计算机辅助检测方案。高性能电子清洗(hpEC)与高性能计算机辅助检测(hpCAD)的组合将允许可视化结肠的整个粘膜表面,而不会出现伪影。具体而言,我们假设移动的HPCC-VC系统将提高非泻药CTC(ncCTC)图像的电子净化质量,将以比传统方法快100倍的速度提供图像,并将提高读片员在移动的高分辨率显示设备上分析的图像中检测结肠病变的性能。 为了实现这些目标,HPCC平台将使用基于CPU集群的超级计算和并行图像处理库。然后,将开发一种hpEC方案,有效地去除ncCTC图像中的残留粪便物质。同时,将开发高分辨率hpCAD方案,以支持ncCTC中结肠病变的高性能检测。这些方案将被集成到HPCC平台上的移动的HPCC-VC系统中。在开发计算EC和CAD方案方面的必要初步研究显示出希望; HPCC平台的开发和部署将提高结肠癌筛查的高性能多维成像的质量、速度和实用性。将进行一项全面的阅片人性能研究,以确定通过HPCC平台分析和交付的图像的临床应用和受益。 HPCC-VC的成功开发将证明该平台在改善诊断成像和促进患者高度可接受的准确、高通量结肠癌筛查方面的临床益处。从长远来看,广泛采用和使用HPCC-VC系统将有助于早期和准确的诊断,从而降低结肠癌的死亡率。 公共卫生关系:HPCC-VC系统的成功开发将证明HPCC平台用于诊断成像的临床益处,并将为患者提供高度可接受且高度准确的结直肠病变的高通量结肠癌筛查方案。该系统将促进结肠癌的早期诊断,并最终降低结肠癌的死亡率。

项目成果

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HIROYUKI YOSHIDA其他文献

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{{ truncateString('HIROYUKI YOSHIDA', 18)}}的其他基金

Survival prediction in patients with progressive fibrosing interstitial lung disease
进行性纤维化间质性肺病患者的生存预测
  • 批准号:
    10644030
  • 财政年份:
    2022
  • 资助金额:
    $ 36.16万
  • 项目类别:
Survival prediction in patients with progressive fibrosing interstitial lung disease
进行性纤维化间质性肺病患者的生存预测
  • 批准号:
    10503417
  • 财政年份:
    2022
  • 资助金额:
    $ 36.16万
  • 项目类别:
Deep radiomic decision support system for colorectal cancer
结直肠癌深度放射组学决策支持系统
  • 批准号:
    9764151
  • 财政年份:
    2017
  • 资助金额:
    $ 36.16万
  • 项目类别:
Spectral precision imaging for early diagnosis of colorectal lesions with CT colonography
CT结肠成像光谱精密成像用于结直肠病变的早期诊断
  • 批准号:
    10308462
  • 财政年份:
    2017
  • 资助金额:
    $ 36.16万
  • 项目类别:
Deep radiomic decision support system for colorectal cancer
结直肠癌深度放射组学决策支持系统
  • 批准号:
    9288493
  • 财政年份:
    2017
  • 资助金额:
    $ 36.16万
  • 项目类别:
Deep radiomic decision support system for colorectal cancer
结直肠癌深度放射组学决策支持系统
  • 批准号:
    9566185
  • 财政年份:
    2017
  • 资助金额:
    $ 36.16万
  • 项目类别:
Spectral precision imaging for early diagnosis of colorectal lesions with CT colonography
CT结肠成像光谱精密成像用于结直肠病变的早期诊断
  • 批准号:
    10054168
  • 财政年份:
    2017
  • 资助金额:
    $ 36.16万
  • 项目类别:
Dynamic-CT-based biomarker for predicting clinical outcome in CRC
基于动态 CT 的生物标志物用于预测 CRC 的临床结果
  • 批准号:
    8893927
  • 财政年份:
    2014
  • 资助金额:
    $ 36.16万
  • 项目类别:
Dynamic-CT-based biomarker for predicting clinical outcome in CRC
基于动态 CT 的生物标志物用于预测 CRC 的临床结果
  • 批准号:
    8757781
  • 财政年份:
    2014
  • 资助金额:
    $ 36.16万
  • 项目类别:
Cloud-computer-aided diagnostic imaging decision support system
云计算机辅助影像诊断决策支持系统
  • 批准号:
    8848046
  • 财政年份:
    2012
  • 资助金额:
    $ 36.16万
  • 项目类别:

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