Abstract:
The invention relates to a system for assisting in evaluating a contour of an anatomic structure (22) with respect to a dose distribution corresponding to a treatment plan for a radiation therapy treatment of a patient. The system comprises an evaluation unit particularly configured to evaluate the dose distribution in varying distances from the contour of the anatomic structure (22) to determine at least one point where the evaluated dose distribution fulfills a predetermined condition, and to determine the distance between the at least one point and the contour and/or to visualize the at least one point to a user of the system.
Abstract:
The present invention relates to device and method for correction of a medical breast image. To provide for an improved correction, said device comprises a medical image input (31) for obtaining a medical breast image of subject's breast potentially showing artificial deformations of the breast, a scan image input (32) for obtaining a scan image of the same subject's breast showing the breast in a predetermined position of the subject and comprising surface information of the breast, a simulation unit (33) for generating a simulated medical breast image from the obtained medical breast image, said simulated medical breast image showing the breast in the same predetermined position of the subject as the scan image and representing the breast surface by a surface mesh, wherein said simulation unit (33) is configured to generate said simulated medical breast image based on a volumetric biomechanical model, and wherein material parameters of the biomechanical model are varied for aligning the biomechanical model with the breast surface extracted from the scan image, and a correction unit (34) for determining corrections for correcting the simulated medical breast image for said artificial deformations by use of the scan image by applying a surface matching between said surface mesh and said scan image and for applying the determined corrections to the obtained medical breast image to obtain a corrected medical breast image.
Abstract:
An image registration apparatus (118) includes an image quality driven image registration determiner (202) that determines an image quality driven image registration for a set of images to register based on a non-rigid registration (204), which includes an optimization of an image similarity term and a regularization term, and a registration steering factor, and a registration component (206) that registers the set of images using the image quality driven image registration. A method determining an image quality driven image registration for a set of images to register based on a non-rigid registration, which includes an optimization of an image similarity term and a regularization term, and a registration steering factor, and registering the set of images using the fidelity driven image registration, generating a set of registered images.
Abstract:
The invention relates to a method and an image processing device (50) for the registration of two images (I1, I2) that may for example be provided by a CT scanner (10) and/or an MRI scanner (20). According to one embodiment of the invention, the images are first globally registered (GR) with a given registration algorithm using a first parameter vector (p). A user may then select a region of interest ROI, and a plurality of local registrations (LR1, . . . LRs, . . . LRn) are calculated for this ROI using the same registration algorithm but different parameter vectors (p, p, . . . p). The results of the local registrations (LR1, . . . LRs, . . . LRn) are displayed and the user can select the best local registration(s). In a final step, the selected local registration(s) (LRs) and the global registration (GR) may be merged. Additionally or alternatively, a parameter vector for a local registration in the ROI may be determined by an automatic analysis of the ROI.
Abstract:
The present invention refers to providing a system that allows to very accurately determine the state of a disease, like COPD, in a patient. The system (100) comprises a unit (101) for providing images of the region of interest corresponding to different states of the region of interest, a unit (102) for elastically registering the images to each other resulting in an elastic registration output, a unit (103) for determining a specific tissue region in an image, a unit (104) for determining a specific elastic registration output for the specific tissue region based on the determined elastic registration output, and a unit (105) for determining an elastic indicator for the specific tissue type based on the specific elastic registration output. Thus, a state of a disease that influences the elastic properties of the specific tissue type can be determined very accurately.
Abstract:
A system and method are provided for guiding surgery using MR images and radioactive markers. The method comprises reconstructing the surface of an anatomical structure and a gamma probe orientated to optimize a radioactivity reading from a radioactive seed placed at a target location in the anatomic structure for each of one or more positions of the gamma probe. The position and orientation of the gamma probe is detected in each reconstructed surface to estimate a position of the radioactive seed relative to the reconstructed surface.
Abstract:
An object motion parameter determiner (122) includes a deformation vector field determiner (210) that determines deformation vector fields for a 4D image set, which includes three or more images corresponding to three or more different motion phases of motion of a moving object. The object motion parameter determiner further includes a volume curve determiner (212) that generates a volume curve for the voxel based on the deformation vector fields. The object motion parameter determiner further includes a model fitter (214) that fits a predetermined motion model to the volume curve. The object motion parameter determiner further includes a parameter determiner (218) that estimates at least one object motion parameter based on the fitted model.
Abstract:
The invention relates to a device for processing CT imaging data, comprising a processing unit, which is configured to receive a plurality of sets of CT imaging data recorded at different imaging positions and at different points in time. Furthermore, the processing device is configured to provide a plurality of auxiliary sets of CT imaging data, each auxiliary set of CT imaging data comprising processed image data allocated to spatial positions inside a respective spatial section of the object space, wherein a given one of the spatial sections contains those spatial positions which are covered by those sets of CT imaging data acquired at a respective one of the imaging positions, and to generate the processed image data for a given spatial position using those of the sets of CT imaging data acquired at the respective one of the imaging positions.
Abstract:
The invention relates to a system and a method for assisting in attenuation correction of gated PET data of a moving object (2). In the system, an evaluation unit (15) is configured to (i) receive a CT image of the object (2) and to segment the CT image into a plurality of CT sub-images, each CT sub-image correspond to an axial segment of an imaged volume, (ii) to determine for each CT sub-image a gate including PET data having a greatest correspondence with the CT sub-image, (iii) to construct, for each CT sub-image, a PET sub-image from the PET data included in the gate determined for the CT sub-image, the PET sub-image substantially corresponding to the same axial segment of the imaged volume as the CT sub-image, and (iv) to combine the PET sub-images to form a PET reference image of the object (2).
Abstract:
Systems and methods for iteratively computing an image registration or an image segmentation. The registration and segmentation computations are driven by an optimization function that includes a similarity measure component whose effect on the iterative computations is relatively mitigated based on a monitoring of volume changes o volume elements at image locations during the iterations. There is also a system and a related 5 method to quantify for a registration error. This includes applying a series of edge detectors to input images and combining related filter responses into a combined response. The series of filters are parameterized with a filter parameter. An extremal value of the combined response is then found and a filter parameter associated with said extremal value is then returned as output. This filter parameter relates to a registration error at a given image 10 location.