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Summary Teleretinal programs have expanded in recent years, primarily to screen for diabetic retinopathy. Accurate and consistent assessment of the retinal vasculature, which often sustains damage as a result of cardiovascular disease, would advance teleretinal screening in terms of robustness and cost. Unfortunately, assessing changes to the retinal vasculature and quantifying abnormalities in retinal images has proven more difficult. Semi-automatic methods are reported to reduce grader variability, but they are time-consuming, requiring extensive reader interaction, thus limiting the overall effectiveness of a teleretinal screening program. VisionQuest Biomedical and its collaborator, the Retina Institute of South Texas (RIST), will demonstrate a software tool for comprehensive assessment of retinal vasculature (CARV) to aid readers in the quantitative characterization of vascular abnormalities and identification of those images with features indicative of potential sight-threatening or life-threatening conditions. CARV will provide the reader real-time artery to vein ratio (AVR) measurements, an accepted clinical value for determining risk of future stroke or hypertensive events, as well as measurements associated with branching patterns and tortuosity. It will also incorporate detection algorithms for features such as copper and silver wiring, AV nicking, and emboli. Our goal is to provide an aid to the retinal grader for detecting and quantifying common retinal vessel abnormalities with high agreement with the gold standard, a retinal specialist. In this Phase I we will also implement clinically accepted quantitative measurements for vasculature parameters. CARV, which can be integrated into a teleretinal system for diabetics, will allow graders to consistently identify signs of hypertensive retinopathy and CVD-related conditions and providers to exploit the full potential of teleretinal screening.
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Comprehensive automatic assessment of retinal vascular abnormalities for computer-assisted retinopathy grading.
计算机辅助视网膜病变分级的视网膜血管异常综合自动评估。
DOI: 10.1109/embc.2014.6945074
发表时间: 2014
期刊: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
影响因子: --
作者: [Joshi,Vinayak, Agurto,Carla, VanNess,Richard, Nemeth,Sheila, Soliz,Peter, Barriga,Simon]
通讯作者: Barriga,Simon
Automated system to improve compliance to diabetic retinopathy screening
  • 批准号:
    10697609
  • 项目类别:
  • 资助金额:
    $27.41万
  • 财政年份:
    2023
  • 负责人:
    Vinayak S Joshi
  • 依托单位:
Malarial retinopathy screening system for improved diagnosis of cerebral malaria
  • 批准号:
    10401912
  • 项目类别:
  • 资助金额:
    $99.29万
  • 财政年份:
    2021
  • 负责人:
    Vinayak S Joshi
  • 依托单位:
Malarial retinopathy screening system for improved diagnosis of cerebral malaria
  • 批准号:
    10253474
  • 项目类别:
  • 资助金额:
    $99.92万
  • 财政年份:
    2021
  • 负责人:
    Vinayak S Joshi
  • 依托单位:
Comprehensive Assessment of Retinal Vasculature (CARV)
  • 批准号:
    8905943
  • 项目类别:
  • 资助金额:
    $68.93万
  • 财政年份:
    2014
  • 负责人:
    Vinayak S Joshi
  • 依托单位:
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