Abstract: A radiation therapy system includes a diagnostic image scanner (12) which acquires a multidimensional dataset of a subject that is reconstructed into at least one image representation of an object of interest. An image processing apparatus (72), of radiation therapy system, includes a segmentation unit (74) which identifies a surface contour of the object of interest, or other critical structures. A masking unit (82) determines a non-constant margin, based on the identified surface contour and appends the determined non-constant margin to the identified surface contour. The non-constant margin is based on at least one of anisotropic motion, surface morphology, positional uncertainty, proximity to other organs, and probability of dose distribution. A planning processor (70) generates a radiation therapy plan which limits the delivery of therapeutic radiation to anatomy associated with the surface contour and appended non-constant margin.

Abstract: A radiation therapy system includes a diagnostic image scanner (12) which acquires a multidimensional dataset of a subject that is reconstructed into at least one image representation of an object of interest. An image processing apparatus (72), of radiation therapy system, includes a segmentation unit (74) which identifies a surface contour of the object of interest, or other critical structures. A masking unit (82) determines a non-constant margin, based on the identified surface contour and appends the determined non-constant margin to the identified surface contour. The non-constant margin is based on at least one of anisotropic motion, surface morphology, positional uncertainty, proximity to other organs, and probability of dose distribution. A planning processor (70) generates a radiation therapy plan which limits the delivery of therapeutic radiation to anatomy associated with the surface contour and appended non-constant margin.

Abstract: In a radiation therapy method, one or more planning images are acquired (102) of a subject. Features of at least malignant tissue are contoured in the one or more planning images to produce one or more initial feature contours. One or more treatment images of the subject are acquired (114). The one or more initial feature contours are updated (122) based on the one or more treatment images. Radiation treatment parameters are optimized (126) based upon the updated one or more feature contours. Radiation treatment of the subject is performed (130) using the optimized parameters.

Abstract: A diagnostic imaging system (10) corrects metal artifact streaks (38) emanating from a metal object (36) in a tomographic image (T). A first processor (40) reduces streaks (38) caused by mild artifacts by applying an adaptive filter (82). The filter (82) is perpendicularly oriented toward the center of the metal object (36). The weight of the filter (82) is a function of the local structure tensor and the vector pointing to the metal object (36). If it is determined that the strong artifacts are present in the image, a second processor (48) applies a sinogram completed image algorithm to correct for severe artifacts in the image. The sinogram completed image and adaptively filtered image are fused to a final corrected image. In the fusion process, highly corrupted tomographic regions are replaced by the result of the sinogram completed image and the remainder is replaced by the adaptively filtered image.

Abstract: In a radiation therapy method, one or more planning images are acquired (102) of a subject. Features of at least malignant tissue are contoured in the one or more planning images to produce one or more initial feature contours. One or more treatment images of the subject are acquired (114). The one or more initial feature contours are updated (122) based on the one or more treatment images. Radiation treatment parameters are optimized (126) based upon the updated one or more feature contours. Radiation treatment of the subject is performed (130) using the optimized parameters.

Abstract: A radiation therapy planning procedure and device provides a model-based segmentation of co-registered anatomical and functional imaging information to provide a more precise radiation therapy plan. The biology-based segmentation models the imaging information to produce a parametric map, which is then clustered into regions of similar radiation sensitivity or other biological parameters relevant for treatment definition. Each clustered region is prescribed its own radiation prescription dose.

Abstract: A radiation therapy planning procedure and device provides a model-based segmentation of co-registered anatomical and functional imaging information to provide a more precise radiation therapy plan. The biology-based segmentation models the imaging information to produce a parametric map, which is then clustered into regions of similar radiation sensitivity or other biological parameters relevant for treatment definition. Each clustered region is prescribed its own radiation prescription dose.

Abstract: A diagnostic imaging system (10) corrects metal artifact streaks (38) emanating from a metal object (36) in a tomographic image (T). A first processor (40) reduces streaks (38) caused by mild artifacts by applying an adaptive filter (82). The filter (82) is perpendicularly oriented toward the center of the metal object (36). The weight of the filter (82) is a function of the local structure tensor and the vector pointing to the metal object (36). If it is determined that the strong artifacts are present in the image, a second processor (48) applies a sinogram completed image algorithm to correct for severe artifacts in the image. The sinogram completed image and adaptively filtered image are fused to a final corrected image. In the fusion process, highly corrupted tomographic regions are replaced by the result of the sinogram completed image and the remainder is replaced by the adaptively filtered image.