Abstract: Embodiments develop a predictive dose-volume relationships for a radiation therapy treatment is provided. A system includes a memory area for storing data corresponding to a plurality of patients, wherein the data comprises a three-dimensional representation of the planning target volume and one or more organs-at-risk. The data further comprises an amount of radiation delivered to the planning target volume and the one or more organs-at-risk. The system further includes one or more processors programmed to access, from the memory area, the data and to develop a model that predicts dose-volume relationships using the three-dimensional representations of the planning target volume and the one or more organs-at-risk. The model is being derived from correlations between dose-volume relationships and calculated minimum distance vectors between discrete volume elements of the one or more organs-at-risk and a boundary surface of the planning target volume.

Abstract: Embodiments develop a predictive dose-volume relationships for a radiation therapy treatment is provided. A system includes a memory area for storing data corresponding to a plurality of patients, wherein the data comprises a three-dimensional representation of the planning target volume and one or more organs-at-risk. The data further comprises an amount of radiation delivered to the planning target volume and the one or more organs-at-risk. The system further includes one or more processors programmed to access, from the memory area, the data and to develop a model that predicts dose-volume relationships using the three-dimensional representations of the planning target volume and the one or more organs-at-risk. The model is being derived from correlations between dose-volume relationships and calculated minimum distance vectors between discrete volume elements of the one or more organs-at-risk and a boundary surface of the planning target volume.

Abstract: Embodiments develop a predictive dose-volume relationships for a radiation therapy treatment is provided. A system includes a memory area for storing data corresponding to a plurality of patients, wherein the data comprises a three-dimensional representation of the planning target volume and one or more organs-at-risk. The data further comprises an amount of radiation delivered to the planning target volume and the one or more organs-at-risk. The system further includes one or more processors programmed to access, from the memory area, the data and to develop a model that predicts dose-volume relationships using the three-dimensional representations of the planning target volume and the one or more organs-at-risk. The model is being derived from correlations between dose-volume relationships and calculated minimum distance vectors between discrete volume elements of the one or more organs-at-risk and a boundary surface of the planning target volume.

Abstract: Embodiments develop a predictive dose-volume relationships for a radiation therapy treatment is provided. A system includes a memory area for storing data corresponding to a plurality of patients, wherein the data comprises a three-dimensional representation of the planning target volume and one or more organs-at-risk. The data further comprises an amount of radiation delivered to the planning target volume and the one or more organs-at-risk. The system further includes one or more processors programmed to access, from the memory area, the data and to develop a model that predicts dose-volume relationships using the three-dimensional representations of the planning target volume and the one or more organs-at-risk. The model is being derived from correlations between dose-volume relationships and calculated minimum distance vectors between discrete volume elements of the one or more organs-at-risk and a boundary surface of the planning target volume.

Abstract: A technique is disclosed for generating a new contour and/or a 3D surface from contour data using a surface displacement field. The technique is preferably applied to un-contoured target images within a 4D image sequence for which contour data is desired. The technique can be initialized with contour data related to a reference image that has already been contoured, e.g. by a doctor who manually enters contour information into a computer. Image registration (calculation of correspondence between the reference image and target image) can be performed simultaneously with segmentation (identifying regions of interest in the target image). This allows one to make use of segmentation information in a reference image to improve the accuracy of contouring within the target image.

Abstract: A system for distributing images creates a self-sufficient, self-consistent medical imaging and other medical information transfer file that contains image files and corresponding data sets that are bundled with an image viewer application. The medical image and data transfer file is prepared using object serialization and contains a deserialization application. The transfer file is created at an origination location and transmitted to a destination device as a packaged file over a computer network. The destination device receives the packaged file from the origination location and executes the viewer application with the image files and the data sets by opening the packaged file alone, without the need to run any other imaging/viewer application at the destination device. The viewer application has image viewing panes, an annotation tool, and image manipulation tools.

Abstract: A technique is disclosed for generating a new contour and/or a 3D surface from contour data using a surface displacement field. The technique is preferably applied to un-contoured target images within a 4D image sequence for which contour data is desired. The technique can be initialized with contour data related to a reference image that has already been contoured, e.g. by a doctor who manually enters contour information into a computer. Image registration (calculation of correspondence between the reference image and target image) can be performed simultaneously with segmentation (identifying regions of interest in the target image). This allows one to make use of segmentation information in a reference image to improve the accuracy of contouring within the target image.