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公开(公告)号：US20200051258A1
公开(公告)日：2020-02-13
申请号：US13398999
申请日：2012-02-17
申请人： Shun Miao , Rui Liao , Marcus Pfister
发明人： Shun Miao , Rui Liao , Marcus Pfister
摘要： A method for performing 2D/3D registration includes acquiring a 3D image. A pre-contrast 2D image is acquired. A sequence of post-contrast 2D images is acquired. A 2D image is acquired from a second view. The first view pre-contrast 2D image is subtracted from each of the first view post-contrast 2D images to produce a set of subtraction images. An MO image is generated from the subtraction images. A 2D/3D registration result is generated by optimizing a measure of similarity between a first synthetic 2D image and the MO image and a measure of similarity between a second synthetic image and the intra-operative 2D image from the second view by iteratively adjusting an approximation of the pose of the patient in the synthetic images and iterating the synthetic images using the adjusted approximation of the pose.
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2.发明申请AUTOMATIC POSE INITIALIZATION FOR ACCURATE 2-D/3-D REGISTRATION APPLIED TO ABDOMINAL AORTIC ANEURYSM ENDOVASCULAR REPAIR 有权适用于ABDOMINAL AORTIC ANEURYSM ENDOVASCULAR REPAIR的精确二维/三维注册的自动位置初始化公开(公告)号：US20130058555A1
公开(公告)日：2013-03-07
申请号：US13473049
申请日：2012-05-16
申请人： Shun Miao , Joseph Lucas , Rui Liao
发明人： Shun Miao , Joseph Lucas , Rui Liao
IPC分类号： G06K9/00
CPC分类号： G06K9/00214 , G06K9/6203
摘要： 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.
摘要翻译： 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。
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3.发明申请SYSTEM AND METHOD FOR 2-D/3-D REGISTRATION BETWEEN 3-D VOLUME AND 2-D ANGIOGRAPHY 有权三维体积与二维图像之间二维/三维注册的系统与方法公开(公告)号：US20120163686A1
公开(公告)日：2012-06-28
申请号：US13222034
申请日：2011-08-31
IPC分类号： G06K9/00
CPC分类号： G06T7/33 , G06T2207/10072 , G06T2207/10124 , G06T2207/20224 , G06T2207/30048
摘要： 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.
摘要翻译： 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。
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公开(公告)号：US08879815B2
公开(公告)日：2014-11-04
申请号：US13591752
申请日：2012-08-22
申请人： Shun Miao , Christophe Chefd'hotel , Rui Liao
发明人： Shun Miao , Christophe Chefd'hotel , Rui Liao
CPC分类号： G06T7/344 , G06T2207/10081 , G06T2207/10121
摘要： A method for automatic initialization of 2D to 3D image registration includes acquiring a 3D model. A plurality of shape descriptor features is calculated from the acquired 3D model representing a plurality of poses of the 3D model. A 2D image is acquired. The plurality of shape descriptors is matched to the acquired 2D model. An optimum pose of the 3D model is determined based on the matching of the plurality of shape descriptors to the acquired 2D model. An initial registration is generated, in an image processing system, between the 3D model and the 2D image based on the determined optimum pose.
摘要翻译： 用于2D到3D图像配准的自动初始化的方法包括获取3D模型。 从所获取的3D模型中计算出多个形状描述符特征，该3D模型表示3D模型的多个姿态。 获取2D图像。 多个形状描述符与获取的2D模型相匹配。 基于多个形状描述符与所获取的2D模型的匹配来确定3D模型的最佳姿态。 在图像处理系统中，基于确定的最佳姿态在3D模型和2D图像之间生成初始注册。
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5.发明授权System and method for 2-D/3-D registration between 3-D volume and 2-D angiography 有权3-D体积和2维血管造影术之间2-D / 3-D配准的系统和方法公开(公告)号：US08620050B2
公开(公告)日：2013-12-31
申请号：US13222034
申请日：2011-08-31
IPC分类号： G06K9/00
CPC分类号： G06T7/33 , G06T2207/10072 , G06T2207/10124 , G06T2207/20224 , G06T2207/30048
摘要： 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.
摘要翻译： 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。
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公开(公告)号：US20130051647A1
公开(公告)日：2013-02-28
申请号：US13591752
申请日：2012-08-22
申请人： Shun Miao , Christophe Chefd'hotel , Rui Liao
发明人： Shun Miao , Christophe Chefd'hotel , Rui Liao
IPC分类号： G06K9/62
CPC分类号： G06T7/344 , G06T2207/10081 , G06T2207/10121
摘要： A method for automatic initialization of 2D to 3D image registration includes acquiring a 3D model. A plurality of shape descriptor features is calculated from the acquired 3D model representing a plurality of poses of the 3D model. A 2D image is acquired. The plurality of shape descriptors is matched to the acquired 2D model. An optimum pose of the 3D model is determined based on the matching of the plurality of shape descriptors to the acquired 2D model. An initial registration is generated, in an image processing system, between the 3D model and the 2D image based on the determined optimum pose.
摘要翻译： 用于2D到3D图像配准的自动初始化的方法包括获取3D模型。 从所获取的3D模型中计算出多个形状描述符特征，该3D模型表示3D模型的多个姿态。 获取2D图像。 多个形状描述符与获取的2D模型相匹配。 基于多个形状描述符与所获取的2D模型的匹配来确定3D模型的最佳姿态。 在图像处理系统中，基于确定的最佳姿态在3D模型和2D图像之间生成初始注册。
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7.发明授权Automatic pose initialization for accurate 2-D/3-D registration applied to abdominal aortic aneurysm endovascular repair 有权自动姿态初始化用于准确的2-D / 3-D记录应用于腹主动脉瘤血管内修复公开(公告)号：US08588501B2
公开(公告)日：2013-11-19
申请号：US13473049
申请日：2012-05-16
申请人： Shun Miao , Joseph Lucas , Rui Liao
发明人： Shun Miao , Joseph Lucas , Rui Liao
IPC分类号： G06K9/00
CPC分类号： G06K9/00214 , G06K9/6203
摘要： 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.
摘要翻译： 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，theta}，其中（x，y）表示平台上的平移，z表示桌子的深度，θ是围绕z轴的旋转，通过最小化2D和3D髂骨分叉的成本函数， 2D和3D肾动脉分叉，以及2D和3D脊髓中心线。
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