Abstract: An image segmentation method segments a plurality of image features in an image. The plurality of image features are segmented non-simultaneously in succession. The segmenting of each image feature includes adapting an initial mesh to boundaries of the image feature. The segmenting of each image feature further includes preventing the adapted mesh from overlapping any previously adapted mesh.

Abstract: A system and method for determining at least one new treatment plan for at least one new patient, comprising: providing at least one representation of the at least one new patient's at least one organ at risk relative to at least one target; searching for at least one prior treatment plan for at least one prior patient with at least one similar representation; and reviewing the at least one prior treatment plan for the at least one prior patient in order to determine whether the at least one new treatment plan can be improved based on information in the at least one prior treatment plan.

Abstract: A system and method for determining at least one new treatment plan for at least one new patient, comprising: providing at least one representation of the at least one new patient's at least one organ at risk relative to at least one target; searching for at least one prior treatment plan for at least one prior patient with at least one similar representation; and reviewing the at least one prior treatment plan for the at least one prior patient in order to determine whether the at least one new treatment plan can be improved based on information in the at least one prior treatment plan.

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: An imaging system (10) includes imaging modalities such as a PET imaging system (12) and a CT scanner (14). The CT scanner (14) is used to produce a first image (62) which is used for primary contouring. The PET system (12) is used to provide a second image (56), which provides complementary information about the same or overlapping anatomical region. After first and second images (62, 56) are registered with one another the first and second images (62, 56) are concurrently segmented to outline a keyhole (76). The keyhole portion of the second image (56) is inserted into the keyhole (76) of the first image (62). The user can observe the composite image and deform a boundary (78) of the keyhole (76) by a mouse (52) to better focus on the region of interest within previously defined keyhole.

Abstract: A system for radiation therapy including a radiation planning system, wherein the radiation planning system comprises a parallel processor adapted to receive input information concerning a body having an intended radiation treatment region and to output information for providing radiation treatment to the intended radiation treatment region of the body, wherein the parallel processor is adapted to perform a plurality of reverse ray tracing calculations based on the input information concerning the body in determining the output information for providing radiation treatment, each of the plurality of reverse ray tracing calculations comprising: calculating a first physical property corresponding to a first sub-region of the intended radiation treatment region of the body that is intersected by a ray traced between a source position and the intended radiation treatment region; and calculating, subsequent to the first-mentioned calculating, a second physical property corresponding to a second sub-region of the in

Abstract: A scanner (18) acquires images of a subject. A 3D model (52) of an organ is selected from an organ model database (50) and dropped over an image of an actual organ. A best fitting means (62) globally scales, translates and/or rotates the model (52) to best fit the actual organ represented by the image. A user uses a mouse (38) to use a set of manual tools (68) to segment and manipulate the model (52)1:o match the image data. The set of tools (68) includes: a Gaussian tool (72) for deforming a surface portion of the model along a Gaussian curve, a spherical push tool (80) for deforming the surface portion along a spherical surface segment, and a pencil tool (90) for manually drawing a line to which the surface portion is redefined.

Abstract: An imaging system (10) includes imaging modalities such as a PET imaging system (12) and a CT scanner (14). The CT scanner (14) is used to produce a first image (62) which is used for primary contouring. The PET system (12) is used to provide a second image (56), which provides complementary information about the same or overlapping anatomical region. After first and second images (62, 56) are registered with one another the first and second images (62, 56) are concurrently segmented to outline a keyhole (76). The keyhole portion of the second image (56) is inserted into the keyhole (76) of the first image (62). The user can observe the composite image and deform a boundary (78) of the keyhole (76) by a mouse (52) to better focus on the region of interest within previously defined keyhole.

Abstract: A radiation treatment apparatus (10) includes a diagnostic imaging scanner (12) that acquires a diagnostic image of a subject. A contouring processor (54) computes a radiation treatment objective based thereon. A radiation delivery apparatus (60) delivers radiation to the subject. An inverse planning processor (80) computes radiation beamlet parameters conforming with the radiation treatment objective by: grouping the beamlet parameters; assigning a weight to each group (82, 84, 86); optimizing a first group (82) to produce an intermediate dosage objective corresponding to the treatment objective weighted by a weight of the first group (82); and optimizing successive groups (84) to produce with the previously optimized groups (82) an increasing intermediate dosage objective corresponding to the treatment objective weighted by the combined weights of the previous and current groups (82, 84).

Abstract: A radiation treatment apparatus (10) includes a diagnostic imaging scanner (12) that acquires a diagnostic image of a subject. A contouring processor (54) computes a radiation treatment objective based thereon. A radiation delivery apparatus (60) delivers radiation to the subject. An inverse planning processor (80) computes radiation beamlet parameters conforming with the radiation treatment objective by: grouping the beamlet parameters; assigning a weight to each group (82, 84, 86); optimizing a first group (82) to produce an intermediate dosage objective corresponding to the treatment objective weighted by a weight of the first group (82); and optimizing successive groups (84) to produce with the previously optimized groups (82) an increasing intermediate dosage objective corresponding to the treatment objective weighted by the combined weights of the previous and current groups (82, 84).

Abstract: A method of calibration and verification of radiotherapy systems deduced radiation beam fluence profiles from the radiation source from a complete model of an extended radiation phantom together with dose information from a portal imaging device. The improved beam fluence profile characterization made with an iterative modeling which includes scatter effects may be used to compute dose profiles in the extended phantom or a patient who has been previously characterized with a CT scan. Deviations from the expected beam fluence profile can be used to detect patient misregistration.

Abstract: A method of calibration and verification of radiotherapy systems deduced radiation beam fluence profiles from the radiation source from a complete model of an extended radiation phantom together with dose information from a portal imaging device. The improved beam fluence profile characterization made with an iterative modeling which includes scatter effects may be used to compute dose profiles in the extended phantom or a patient who has been previously characterized with a CT scan. Deviations from the expected beam fluence profile can be used to detect patient misregistration.

Abstract: A method of calibration and verification of radiotherapy systems deduced radiation beam fluence profiles from the radiation source from a complete model of an extended radiation phantom together with dose information from a portal imaging device. The improved beam fluence profile characterization made with an iterative modeling which includes scatter effects may be used to compute dose profiles in the extended phantom or a patient who has been previously characterized with a CT scan. Deviations from the expected beam fluence profile can be used to detect patient misregistration.