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    • 9. 发明申请
    • ACCURATE PELVIC FRACTURE DETECTION FOR X-RAY AND CT IMAGES
    • X射线和CT图像的精确检测
    • WO2010117575A3
    • 2011-01-13
    • PCT/US2010027601
    • 2010-03-17
    • UNIV VIRGINIA COMMONWEALTHNAJARIAN KAYVANVASILACHE SIMINASMITH REBECCAWARD KEVIN R
    • NAJARIAN KAYVANVASILACHE SIMINASMITH REBECCAWARD KEVIN R
    • A61B6/00
    • G06T7/0012A61B6/032A61B6/505A61B6/5217A61B6/5235G06T7/11G06T2207/10081G06T2207/10116G06T2207/20212G06T2207/30008
    • Accurate pelvic fracture detection is accomplished with automated X-ray and Computed Tomography (CT) Images for diagnosis and recommended therapy. The system combines computational methods to process images from two different modalities, using Active Shape Model (ASM), spline interpolation, active contours, and wavelet transform. By processing both X-ray and CT Images, features which may be visible under one modality and not under the other are extracted and validates and confirms in format ion visible in both. The X-ray component uses hierarchical approach based on directed Hough Transform to detect pelvic structures, removing the need for manual initialization. The X-ray component uses cubic spline interpolation to regulate ASM deformation during X-ray image segmentation. Key regions of the pelvis are first segmented and identified, allowing detection methods to be specialized to each structure using anatomical knowledge. The CT processing component is able to distinguish bone from other non-bone objects with similar visual characteristics, such a blood and contrast fluid, permitting detection and quantification of soft tissue hemorrhage. The CT processing component draws attention to slices where irregularities are detected, reducing the time to fully examine a pelvic CT scan. The quantitative measurement of bone displacement and hemorrhage area are used as input for a trauma decision-support system, along with physiological signals, injury details and demographic information.
    • 使用自动化X射线和计算机断层扫描(CT)图像进行准确的骨盆骨折检测,用于诊断和推荐治疗。 该系统结合计算方法来处理来自两种不同模态的图像,使用主动形状模型(ASM),样条插值,主动轮廓和小波变换。 通过处理X射线和CT图像,可以在一种模式下而不是在另一种模式下可见的特征被提取并且以两种格式离子可见的方式进行验证和确认。 X射线组件使用基于定向霍夫变换的分层方法来检测骨盆结构,消除手动初始化的需要。 X射线成分使用三次样条插值来调节X射线图像分割过程中的ASM变形。 骨盆的关键区域首先被分割和识别,从而允许使用解剖学知识来检测各种结构的检测方法。 CT处理组件能够将具有类似视觉特征的骨骼与其他具有类似视觉特征的非骨骼物体(如血液和造影剂)区分开,从而允许检测和定量软组织出血。 CT处理组件提请注意检测不规则的切片,减少完全检查盆腔CT扫描的时间。 骨移位和出血面积的定量测量用作创伤决策支持系统的输入,以及生理信号,损伤细节和人口统计信息。