Abstract: A computer-implemented method for generating anatomical data associated with a musculoskeletal joint, the method comprising: receiving as input variation data representing change with time of a musculoskeletal joint of interest caused by a condition; receiving as input patient data representing the musculoskeletal joint of interest of a patient at a current time; and processing the variation data and the patient data to generate said anatomical data, wherein said anatomical data comprises data indicating the musculoskeletal joint of interest of the patient at a predetermined time different to the current time.

Abstract: A computer-implemented method for generating anatomical data associated with a musculoskeletal joint, the method comprising: receiving as input variation data representing change with time of a musculoskeletal joint of interest caused by a condition; receiving as input patient data representing the musculoskeletal joint of interest of a patient at a current time; and processing the variation data and the patient data to generate said anatomical data, wherein said anatomical data comprises data indicating the musculoskeletal joint of interest of the patient at a predetermined time different to the current time.

Abstract: A computer-implemented method for identifying features in an image. The method comprises fitting a plurality of second models to the image, the plurality of second models together modelling a region of interest, wherein each part of the region of interest is modelled by at least two of the plurality of second models; and identifying the features in the image based upon the fit of the plurality of second models.

Abstract: A computer-implemented method for identifying features in an image. The method comprises fitting a plurality of second models to the image, the plurality of second models together modelling a region of interest, wherein each part of the region of interest is modelled by at least two of the plurality of second models; and identifying the features in the image based upon the fit of the plurality of second models.

Abstract: A computer-implemented method for identifying features in an image. The method comprises fitting a plurality of second models to the image, the plurality of second models together modelling a region of interest, wherein each part of the region of interest is modelled by at least two of the plurality of second models; and identifying the features in the image based upon the fit of the plurality of second models.

Abstract: A computer-implemented method of generating a model that models a class of objects. The method comprises, for each of a plurality of objects of the class of objects, receiving a first two-dimensional image of the object and first acquisition data, receiving a second two-dimensional image of the object and second acquisition data and receiving data indicating a plurality of points of interest within the object. The first and second two-dimensional images are combined based upon the first and second acquisition data to generate three-dimensional image data, the three-dimensional image data including data based upon the data indicating a plurality of points of interest and the generated three-dimensional image data for each of the objects of the class of objects is processed to generate the model.

Abstract: A computer-implemented method of generating a model that models a class of objects. The method comprises, for each of a plurality of objects of the class of objects, receiving a first two-dimensional image of the object and first acquisition data, receiving a second two-dimensional image of the object and second acquisition data and receiving data indicating a plurality of points of interest within the object. The first and second two-dimensional images are combined based upon the first and second acquisition data to generate three-dimensional image data, the three-dimensional image data including data based upon the data indicating a plurality of points of interest and the generated three-dimensional image data for each of the objects of the class of objects is processed to generate the model.

Abstract: A computer-implemented method for identifying features in an image. The method comprises fitting a plurality of second models to the image, the plurality of second models together modelling a region of interest, wherein each part of the region of interest is modelled by at least two of the plurality of second models; and identifying the features in the image based upon the fit of the plurality of second models.