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    • 43. 发明申请
    • AUTOMATIC POSE INITIALIZATION FOR ACCURATE 2-D/3-D REGISTRATION APPLIED TO ABDOMINAL AORTIC ANEURYSM ENDOVASCULAR REPAIR
    • 适用于ABDOMINAL AORTIC ANEURYSM ENDOVASCULAR REPAIR的精确二维/三维注册的自动位置初始化
    • US20130058555A1
    • 2013-03-07
    • US13473049
    • 2012-05-16
    • Shun MiaoJoseph LucasRui Liao
    • Shun MiaoJoseph LucasRui Liao
    • G06K9/00
    • G06K9/00214G06K9/6203
    • A method for automatically initializing pose for registration of 2D fluoroscopic abdominal aortic images with a 3D model of an abdominal aorta includes detecting a 2D iliac bifurcation and a 2D renal artery bifurcation from a sequence of 2D fluoroscopic abdominal aortic images, detecting a spinal centerline in a 2D fluoroscopic spine image, providing a 3D iliac bifurcation and a 3D renal artery bifurcation from a 3D image volume of the patient's abdomen, and a 3D spinal centerline from the 3D image volume of the patient's abdomen, and determining pose parameters {x, y, z, θ}, where (x, y) denotes the translation on a table plane, z denotes a depth of the table, and θ is a rotation about the z axis, by minimizing a cost function of the 2D and 3D iliac bifurcations, the 2D and 3D renal artery bifurcation, and the 2D and 3D spinal centerlines.
    • 用于自动初始化用于腹部主动脉3D模型的2D荧光透视腹主动脉图像配准的姿势的方法包括从2D荧光透视腹主动脉图像序列检测2D髂骨分叉和2D肾动脉分叉,检测脊髓中心线 2D透视脊柱图像,从患者腹部的3D图像体积提供3D髂骨分叉和3D肾动脉分叉,以及来自患者腹部的3D图像体积的3D脊柱中心线,以及确定姿势参数{x,y, z,&thetas;},其中(x,y)表示平面上的平移,z表示表的深度,&thetas; 通过最小化2D和3D髂骨分叉,2D和3D肾动脉分叉以及2D和3D脊髓中心线的成本函数,围绕z轴旋转。
    • 44. 发明申请
    • SYSTEM AND METHOD FOR 2-D/3-D REGISTRATION BETWEEN 3-D VOLUME AND 2-D ANGIOGRAPHY
    • 三维体积与二维图像之间二维/三维注册的系统与方法
    • US20120163686A1
    • 2012-06-28
    • US13222034
    • 2011-08-31
    • Rui LiaoShun Miao
    • Rui LiaoShun Miao
    • G06K9/00
    • G06T7/33G06T2207/10072G06T2207/10124G06T2207/20224G06T2207/30048
    • A method for registering a 2-D DSA image to a 3-D image volume includes calculating a coarse similarity measure between a 2-D DRR of an aorta and a cardiac DSA image, and a 2-D DRR of a coronary artery and the cardiac DSA image, for a plurality of poses over a range of 2-D translations. Several DRR-pose combinations with largest similarity measures are selected as refinement candidates. The similarity measure is calculated between the refinement candidate DRRs and the DSA, for a plurality of poses over a range of 3-D translations and in-plane rotations. One or more DRR-pose combinations with largest similarity measures are selected as final candidates. The similarity measure between the final candidate DRRs the DSA are calculated for a plurality of poses over a range of 3D translations and 3D rotations, and a DRR-pose combination with a largest similarity measure is selected as a final registration result.
    • 将2-D DSA图像记录到3-D图像体积的方法包括计算主动脉的2-D DRR与心脏DSA图像和冠状动脉的2-D DRR之间的粗略相似性度量, 心脏DSA图像,用于在2-D翻译的范围内的多个姿势。 选择具有最大相似性度量的几种DRR姿势组合作为细化候选。 对于在3D平移和平面内旋转的范围内的多个姿态,在细化候选DRR和DSA之间计算相似性度量。 选择具有最大相似性度量的一个或多个DRR姿势组合作为最终候选。 在3D平移和3D旋转的范围内针对多个姿态计算最终候选DRR之间的相似性度量,并且选择具有最大相似性度量的DRR姿势组合作为最终注册结果。