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    • 9. 发明授权
    • Personalized prognosis modeling in medical treatment planning
    • 医疗策划中的个性化预后建模
    • US08579784B2
    • 2013-11-12
    • US12944288
    • 2010-11-11
    • Sriram KrishnanR. Bharat RaoChristopher Jude Amies
    • Sriram KrishnanR. Bharat RaoChristopher Jude Amies
    • A61N5/00
    • A61N5/103A61N2005/1041G06F19/00G06F19/3481G16H50/30G16H50/50
    • Automated treatment planning is provided with individual specific consideration. One or more prognosis models indicate survivability as a function of patient specific information for a given dose. By determining survivability for a plurality of doses, the biological model represented by survivability as a function of dose is determined from the specific patient. Similarly, the chances of complications or side effects are determined. The chance of survivability and chance of complication are used as or instead of the tumor control probability and normal tissue complications probability, respectively. The desired tumor dosage and tolerance dosage are selected as a function of the patient specific dose distributions. The selected dosages are input to an inverse treatment planning system for establishing radiation treatment parameters.
    • 提供自动化治疗计划,具体考虑。 一个或多个预后模型表明作为给定剂量的患者特异性信息的函数的存活率。 通过确定多个剂量的存活率,从特定患者确定作为剂量的函数的存活率所表示的生物学模型。 类似地,确定并发症或副作用的机会。 生存能力和并发症的机会分别被用作肿瘤控制概率和正常组织并发症概率。 选择所需的肿瘤剂量和耐受剂量作为患者具体剂量分布的函数。 选择的剂量被输入到用于建立放射治疗参数的反向治疗计划系统。
    • 10. 发明申请
    • Segmentation of Biological Image Data
    • 生物图像数据分割
    • US20110286654A1
    • 2011-11-24
    • US13109457
    • 2011-05-17
    • Sriram Krishnan
    • Sriram Krishnan
    • G06K9/00
    • G06K9/0014G06T7/12G06T7/155G06T2207/30024
    • Described herein are systems and methods for automated segmentation of image data. According to one aspect of the present technology, systems and methods are provided for detecting regions of interest within biological images. In particular, first and second images of first and second biological samples are received, wherein one or more routine stains have previously been applied to the first biological sample. A region of interest in the first image may be segmented to generate a boundary. The boundary may then be transferred to the second image to segment a corresponding region of interest in the second image.
    • 这里描述了用于图像数据的自动分割的系统和方法。 根据本技术的一个方面,提供了用于检测生物图像内的感兴趣区域的系统和方法。 特别地,接收第一和第二生物样品的第一和第二图像,其中一个或多个常规染料先前已经施加到第一生物样品。 可以对第一图像中的感兴趣区域进行分割以产生边界。 然后可以将边界传送到第二图像以分割第二图像中的对应的感兴趣区域。