Abstract: A system and method for intra-operatively providing a surgeon with visual evaluations of possible surgical outcomes ahead of time, and generating simulated data, includes a medical imaging camera, a registration device for registering data to a physical space, and to the medical imaging camera, and a fusion mechanism for fusing the data and the images to generate simulated data, without correcting for distortion. The simulated data (e.g., such as augmented X-ray images) is natural and easy for a surgeon to interpret. In an exemplary implementation, the system preferably includes a data processor which receives a three-dimensional surgical plan or three-dimensional plan of therapy delivery, one or a plurality of two-dimensional intra-operative images, a three-dimensional model of pre-operative data, registration data, and image calibration data.

Abstract: A system and method for intra-operatively providing a surgeon with visual evaluations of possible surgical outcomes ahead of time, and generating simulated data, includes a medical imaging camera, a registration device for registering data to a physical space, and to the medical imaging camera, and a fusion mechanism for fusing the data and the images to generate simulated data, without correcting for distortion. The simulated data (e.g., such as augmented X-ray images) is natural and easy for a surgeon to interpret. In an exemplary implementation, the system preferably includes a data processor which receives a three-dimensional surgical plan or three-dimensional plan of therapy delivery, one or a plurality of two-dimensional intra-operative images, a three-dimensional model of pre-operative data, registration data, and image calibration data.

Abstract: A system and method for intra-operatively providing a surgeon with visual evaluations of possible surgical outcomes ahead of time, and generating simulated data, includes a medical imaging camera, a registration device for registering data to a physical space, and to the medical imaging camera, and a fusion mechanism for fusing the data and the images to generate simulated data. The simulated data (e.g., such as augmented X-ray images) is natural and easy for a surgeon to interpret. In an exemplary implementation, the system preferably includes a data processor which receives a three-dimensional surgical plan or three-dimensional plan of therapy delivery, one or a plurality of two-dimensional intra-operative images, a three-dimensional model of pre-operative data, registration data, and image calibration data.

Abstract: Noise-corrupted boundary information in tomographic images is restored using a data structure, called a “boundary envelope”. Both the restored boundary information and a measure of the precision of the restoration are described by the process. This data structure is used to describe the restored information in both qualitative and quantitative terms. The results of the boundary restoration process are described qualitatively by graphically displaying the boundary envelope together with the noisy CT image in such a way that allows a human observer to (a) see more details of the boundary than are visible in the CT image alone, and (b) to visually apprehend the precision with which the boundary has been restored. A boundary envelope describes a region in the image within which the boundary of a given noisy object is guaranteed to lie. The boundary envelope describes a set of limits on the object boundary, and limits on those properties of a noisy object that can be computed from boundary information.

Abstract: A system and method for intra-operatively providing a surgeon with visual evaluations of possible surgical outcomes ahead of time, and generating simulated data, includes a medical imaging camera, a registration device for registering data to a physical space, and to the medical imaging camera, and a fusion mechanism for fusing the data and the images to generate simulated data, without correcting for distortion. The simulated data (e.g., such as augmented X-ray images) is natural and easy for a surgeon to interpret. In an exemplary implementation, the system preferably includes a data processor which receives a three-dimensional surgical plan or three-dimensional plan of therapy delivery, one or a plurality of two-dimensional intra-operative images, a three-dimensional model of pre-operative data, registration data, and image calibration data.

Abstract: Noise-corrupted boundary information in tomographic images is restored using a data structure, called a “boundary envelope”. Both the restored boundary information and a measure of the precision of the restoration are described by the process. This data structure is used to describe the restored information in both qualitative and quantitative terms. The results of the boundary restoration process are described qualitatively by graphically displaying the boundary envelope together with the noisy CT image in such a way that allows a human observer to (a) see more details of the boundary than are visible in the CT image alone, and (b) to visually apprehend the precision with which the boundary has been restored. A boundary envelope describes a region in the image within which the boundary of a given noisy object is guaranteed to lie. The boundary envelope describes a set of limits on the object boundary, and limits on those properties of a noisy object that can be computed from boundary information.

Abstract: A computer system and method solve the problem of getting a useful three-dimensional representation of an object like the spine using a small amount of data. This is done by gathering three-dimensional data in the form of a set of 2D computer tomography (CT) slices of a patient's bones and a coaxial set of 2D CT scout images, which are digital two-dimensional X-ray images that can be produced by a CT scanner; extracting from each of these three-dimensional data sets a corresponding stack of 2D contours; and constructing a 3D geometric model of the object. The main features of spinal deformation are captured by integrating these two sets of three-dimensional data, and constructing from them a three-dimensional geometric model of the spine. Scouts are usually used to monitor CT scan acquisition. Here, they are also used as an essential source of data.

Abstract: A system and method extracts object boundaries in computed tomography images that have been corrupted by noise. The system and method find object boundaries in tomography images by finding edges in sinogram data, thereby providing a segmentation method that is insensitive to the image noise introduced by the process of image reconstruction from projections. The boundary-detection system uses projection data, and optionally tomographic image data, to detect the boundaries of objects in tomographic images. The system is of particular value for boundary-detection in images corrupted by reconstruction artifacts, such as CT scans of hospital patients who have implanted metal prostheses. The system is applicable to recovering the boundaries of convex objects, and the convex segments of the boundaries of concave objects (though not the complete boundaries of the concave objects themselves).

Abstract: A computer system and method solve the problem of getting a useful three-dimensional representation of an object like the spine using a small amount of data. This is done by gathering and combining three-dimensional data in the form of (a) a set of 2D computer tomography (CT) slices of a patient's bones with (b) a set of 2D CT scout images, which are digital two-dimensional X-ray images that can be produced by a CT scanner. The main features of spinal deformation are captured by integrating these two sets of three-dimensional data, and constructing from them a three-dimensional geometric model of the spinal. Scouts are usually used to monitor CT scan acquisition. Here, they are also used as an essential source of data.

Abstract: A system and method to improve the quality of noisy computer tomography (CT) images that have been generated by a CT scanner running on low-power. The image noise is reduced by restoring crucial quantitative image information. The system does not fail when applied to sparsely-sampled and/or low-resolution projection data and is clinically viable in that it is a method that can be embodied in a practical, real-world system that can be used routinely in remote sites with limited access to electric power, and relies only on data that are available from standard medical CT scanners.

Abstract: A computer system and method solve the problem of getting a useful three dimensional representation of an object like the spine using a small amount of data. This is done by gathering and combining three dimensional data in the form of computer tomography (CT) scans of a patient's bones with two dimensional data consisting of CT scout images (or scouts), which are digital two dimensional X-ray images that can be produced by a CT scanner. The main features of spinal deformation are captured by combining the two dimensional data from CT scouts and the three-dimensional information from the CT scans using simple modeling of vertebrae. Scouts are usually used to monitor CT scan acquisition. Here, they are also used as an essential source of data.

Abstract: A system and method reduce the noise, and hence improve the usefulness, of computer tomography (CT) images that have been corrupted by metal-induced reconstruction artifacts. Metal-induced reconstruction artifacts in CT images are reduced by restoring crucial quantitative image information. The system does not fail when applied to sparsely-sampled and/or low-resolution projection data and is clinically viable in that it is a method that can be embodied in a practical, real-world system that can be used routinely in hospitals and medical clinics, and relies only on data that are available from standard medical CT scanners.

Abstract: In an x-ray computed tomography imaging system, it is often useful to have access to the unreconstructed CT projection data, called sinogram data. Scout image data can be converted to a sinogram using a series of computer implemented algorithms, since the original sinogram data may be unavailable or in a proprietary format. Using this conversion, multiple scout images may be substituted for unavailable sinogram data.