Abstract: A method and system is disclosed for analyzing and evaluating image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. More than one projection may be combined to generate and create a selected view of the subject. The evaluation may be a location determination of a member positioned within the subject.

Abstract: Selected artifacts, which may be based on distortions or selected attenuation features, may be reduced or removed from a reconstructed image. Various artifacts may occur due to the presence of a metal object in a field of view. The metal object may be identified and removed from a data that is used to generate a reconstruction.

Abstract: Selected artifacts, which may be based on distortions or selected attenuation features, may be reduced or removed from a reconstructed image. Various artifacts may occur due to the presence of a metal object in a field of view. The metal object may be identified and removed from a data that is used to generate a reconstruction.

Abstract: A method and system is disclosed for analyzing image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. The image data may include selected overlap and be acquired with an imaging system that generates a plurality of perspectives for more than one location. An automatic system and method may then define or identify various features and/or allow for registration for alternative image data.

Abstract: A method and system is disclosed for analyzing image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. The image data may include selected overlap and be acquired with an imaging system that generates a plurality of perspectives for more than one location. An automatic system and method may then define or identify various features and/or allow for registration for alternative image data.

Abstract: A method and system is disclosed for analyzing image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. The image data may include selected overlap and be acquired with an imaging system that generates a plurality of perspectives for more than one location. An automatic system and method may then define or identify various features and/or allow for registration for alternative image data.

Abstract: A method and system is disclosed for analyzing image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. The image data may include selected overlap and be acquired with an imaging system that generates a plurality of perspectives for more than one location. An automatic system and method may then define or identify various features and/or allow for registration for alternative image data.

Abstract: An embodiment in accordance with the present invention provides a method for 3D-2D registration (for example, registration of a 3D CT image to a 2D radiograph) that permits deformable motion between structures defined in the 3D image based on a series of locally rigid transformations. This invention utilizes predefined annotations in 3D images (e.g., the location of anatomical features of interest) to perform multiple locally rigid registrations that yield improved accuracy in aligning structures that have undergone deformation between the acquisition of the 3D and 2D images (e.g., a preoperative CT compared to an intraoperative radiograph). The 3D image is divided into subregions that are masked according to the annotations, and the registration is computed simultaneously for each divided region by incorporating a volumetric masking method within the 3D-2D registration process.

Abstract: Some embodiments provide systems, assemblies, and methods of analyzing patient anatomy, including providing an analysis of a patient's spine, and also analyzing the biomechanical effects of implants. In some embodiments, the systems, assemblies, and/or methods can include obtaining initial patient data, acquiring spinal alignment and contour information, acquiring flexibility and/or biomechanical information, registering patient anatomical landmarks of interest relative to fiducial markers, analyzing databases of measurements and patient data to predict postoperative patient outcomes. Further, in some embodiments, the systems, assemblies, and/or methods can assess localized anatomical features of the patient, and obtain anatomical region data. In some embodiments, the systems, assemblies, and/or methods can also analyze the localized anatomy and therapeutic device location and contouring.

Abstract: An embodiment in accordance with the present invention provides a method for 3D-2D registration (for example, registration of a 3D CT image to a 2D radiograph) that permits deformable motion between structures defined in the 3D image based on a series of locally rigid transformations. This invention utilizes predefined annotations in 3D images (e.g., the location of anatomical features of interest) to perform multiple locally rigid registrations that yield improved accuracy in aligning structures that have undergone deformation between the acquisition of the 3D and 2D images (e.g., a preoperative CT compared to an intraoperative radiograph). The 3D image is divided into subregions that are masked according to the annotations, and the registration is computed simultaneously for each divided region by incorporating a volumetric masking method within the 3D-2D registration process.

Abstract: Selected artifacts, which may be based on distortions or selected attenuation features, may be reduced or removed from a reconstructed image. Various artifacts may occur due to the presence of a metal object in a field of view. The metal object may be identified and removed from a data that is used to generate a reconstruction.

Abstract: Selected artifacts, which may be based on distortions or selected attenuation features, may be reduced or removed from a reconstructed image. Various artifacts may occur due to the presence of a metal object in a field of view. The metal object may be identified and removed from a data that is used to generate a reconstruction.

Abstract: Some embodiments provide systems, assemblies, and methods of analyzing patient anatomy, including providing an analysis of a patient's spine, and also analyzing the biomechanical effects of implants. In some embodiments, the systems, assemblies, and/or methods can include obtaining initial patient data, acquiring spinal alignment and contour information, acquiring flexibility and/or biomechanical information, registering patient anatomical landmarks of interest relative to fiducial markers, analyzing databases of measurements and patient data to predict postoperative patient outcomes. Further, in some embodiments, the systems, assemblies, and/or methods can assess localized anatomical features of the patient, and obtain anatomical region data. In some embodiments, the systems, assemblies, and/or methods can also analyze the localized anatomy and therapeutic device location and contouring.

Abstract: A method and system is disclosed for analyzing and evaluating image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. More than one projection may be combined to generate and create a selected view of the subject. The evaluation may be a location determination of a member positioned within the subject.

Abstract: An embodiment in accordance with the present invention provides a method for 3D-2D registration (for example, registration of a 3D CT image to a 2D radiograph) that permits deformable motion between structures defined in the 3D image based on a series of locally rigid transformations. This invention utilizes predefined annotations in 3D images (e.g., the location of anatomical features of interest) to perform multiple locally rigid registrations that yield improved accuracy in aligning structures that have undergone deformation between the acquisition of the 3D and 2D images (e.g., a preoperative CT compared to an intraoperative radiograph). The 3D image is divided into subregions that are masked according to the annotations, and the registration is computed simultaneously for each divided region by incorporating a volumetric masking method within the 3D-2D registration process.

Abstract: The present invention is directed to a method for enabling volumetric image reconstruction from unknown projection geometry of tomographic imaging systems, including CT, cone-beam CT (CBCT), and tomosynthesis systems. The invention enables image reconstruction in cases where it was not previously possible (e.g., custom-designed trajectories on robotic C-arms, or systems using uncalibrated geometries), and more broadly offers improved image quality (e.g., improved spatial resolution and reduced streak artifact) and robustness to patient motion (e.g., inherent compensation for rigid motion) in a manner that does not alter the patient setup or imaging workflow. The method provides a means for accurately estimating the complete geometric description of each projection acquired during a scan by simulating various poses of the x-ray source and detector to determine their unique, scan-specific positions relative to the patient, which is often unknown or inexactly known (e.g.

Abstract: Selected artifacts, which may be based on distortions or selected attenuation features, may be reduced or removed from a reconstructed image. Various artifacts may occur due to the presence of a metal object in a field of view. The metal object may be identified and removed from a data that is used to generate a reconstruction.

Abstract: An embodiment in accordance with the present invention provides a technique for localizing structures of interest in projection images (e.g., x-ray projection radiographs or fluoroscopy) based on structures defined in a preoperative 3D image (e.g., MR or CT). Applications include, but are not limited to, spinal interventions. The present invention achieves 3D-2D image registration (and particularly allowing use with a preoperative MR image) by segmenting the structures of interest in the preoperative 3D image and generating a simulated projection of the segmented structures to be aligned with the 2D projection image. Other applications include various clinical scenarios involving 3D-2D image registration, such as image-guided cranial neurosurgery, orthopedic surgery, biopsy, and radiation therapy.

Abstract: An embodiment in accordance with the present invention provides a method for 3D-2D registration (for example, registration of a 3D CT image to a 2D radiograph) that permits deformable motion between structures defined in the 3D image based on a series of locally rigid transformations. This invention utilizes predefined annotations in 3D images (e.g., the location of anatomical features of interest) to perform multiple locally rigid registrations that yield improved accuracy in aligning structures that have undergone deformation between the acquisition of the 3D and 2D images (e.g., a preoperative CT compared to an intraoperative radiograph). The 3D image is divided into subregions that are masked according to the annotations, and the registration is computed simultaneously for each divided region by incorporating a volumetric masking method within the 3D-2D registration process.

Abstract: The present invention is directed to a method for enabling volumetric image reconstruction from unknown projection geometry of tomographic imaging systems, including CT, cone-beam CT (CBCT), and tomosynthesis systems. The invention enables image reconstruction in cases where it was not previously possible (e.g., custom-designed trajectories on robotic C-arms, or systems using uncalibrated geometries), and more broadly offers improved image quality (e.g., improved spatial resolution and reduced streak artifact) and robustness to patient motion (e.g., inherent compensation for rigid motion) in a manner that does not alter the patient setup or imaging workflow. The method provides a means for accurately estimating the complete geometric description of each projection acquired during a scan by simulating various poses of the x-ray source and detector to determine their unique, scan-specific positions relative to the patient, which is often unknown or inexactly known (e.g.