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.
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:
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:
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:
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:
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:
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.