Abstract: When constructing compensators for radiation therapy using ion or proton radiation beams, a computer-aided compensator editing method includes overlaying an initial 3D compensator model on an anatomical image of a target mass (e.g., a tumor) in a patient, along with radiation dose distribution information. A user manipulates pixels or voxels in the compensator model on a display, and a processor automatically adjusts the dose distribution according to the user edits.

Abstract: A method is arranged to segment a surface in a multi-dimensional dataset comprising a plurality of images. Data processing and data acquisition steps can be temporally or geographically distanced, so that the results of a suitable data segmentation are accessed. Next, suitable plurality of image features resembling possible spatial positions of the surface conceived to be segmented are selected and accessed. The features are subsequently matched for all image portions, whereby for each feature a matching error is assigned. A pre-defined selectivity factor is accessed defining a maximum allowable variable fraction of the features having largest matching errors which can be discarded. The segmentation of the sought surface is performed, whereby the discarded features are not taken into account for evaluating the quality of fit of a candidate deformation. The resulting surface is displayed on a suitable display means.

Abstract: A method for selecting vertices for performing deformable registration of imaged objects is provided. The selected vertices form corresponding pairs, each pair including a vertex from a first imaged object and a vertex from a second imaged object. The corresponding vertex pairs are sorted in order of distance between the vertices making up the corresponding vertex pair. The corresponding vertex pair with the greatest distance is given top priority. Corresponding vertex pairs that lie within a selected distance from the selected corresponding vertex pair are discarded. In this manner, the number of vertex pairs used for deformable registration of the imaged objects is reduced and therefore allows for processing times that are clinically acceptable.

Abstract: The present invention relates to the field of digital imaging, in particular to the field of estimating geometrical properties of an anatomical object. According to the present invention, geometrical properties are automatically measured and geometrical properties which have a definition based on sub-parts of the object are derived. To do this, additional geometrical information is integrated into a surface model. Geometrical properties are included into the surface model by identifying and labelling sub-parts of the surface model and fitting geometric primitives to these sub-parts. This advantageously allows to identify these sub-parts on an unseen object surface and to automatically extract relevant geometric properties.

Abstract: A therapy treatment response simulator includes a modeler (202) that generates a model of a structure of an object or subject based on information about the object or subject and a predictor (204) that generates a prediction indicative of how the structure is likely to respond to treatment based on the model and a therapy treatment plan. In another aspect, a system includes performing a patient state determining in silico simulation for a patient using a candidate set of parameters corresponding to another patient and producing a first signal indicative of a predicted state of the patient, and generating a second signal indicative of whether the candidate set of parameters are suitable for the patient based on a known state of the patient.

Abstract: When modeling anatomical structures in a patient for diagnosis or therapeutic planning, an atlas (26) of segmented co-registered CT and MRI anatomical structure reference images can be accessed, and an image of one or more such structures can be selected and overlaid with an MRI image of corresponding structure(s) in a clinical image of a patient. A user can click and drag landmarks or segment edges on the reference MRI image to deform the reference MRI image to align with the patient MRI image. Registration of a landmark in the patient MRI image to the reference MRI image also registers the patient MRI image landmark with a corresponding landmark in the co-registered reference CT image, and electron density information from the reference CT image landmark is automatically attributed to the corresponding registered patient MRI landmark.

Abstract: When adapting models of anatomical structures in a patient for diagnosis or therapeutic planning, an atlas (26) of predesigned anatomical structure models or image volumes can be accessed, and a segmentation of one or more such structures can be selected and overlaid on an a 3D image of corresponding structure(s) in a clinical image (52) of a patient. A user can click on an initially unapproved segmentation 5 landmark (72) on the patient image (52), reposition the unapproved landmark, and approve the repositioned landmark. Remaining unapproved landmarks (72) are then repositioned as a function of the position of the approved landmark (92) using one or more interpolation techniques to adapt the model to the patient image on the fly.

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: The invention relates to a method for data processing. At stage 3 the position of the reference object in the reference image and its relation to a set of reference landmarks in the reference image is established at step 6. In order to enable this, the reference imaging of learning examples may be performed at step 2 and each reference image may be analyzed at step 4, the results may be stored in a suitably arranged database. In order to process the image under consideration, the image is accessed at step 11, the suitable landmark corresponding to the reference landmark in the reference image is identified at step 13 and the spatial relationship established at step 6 is applied to the landmark thereby providing the initial position of the object in the actual image. In case when for the object an imaging volume is selected, the method 1 according to the invention follows to step 7, whereby the scanning 17 is performed within the boundaries given by the thus established scanning volume.

Abstract: A reconstruction processor (34) reconstructs acquired projection data (S) into an uncorrected reconstructed image (T). A classifying algorithm (66) classifies pixels of the uncorrected reconstructed image (T) at least into metal, bone, tissue, and air pixel classes. A clustering algorithm (60) iteratively assigns pixels to best fit classes. A pixel replacement algorithm (70) replaces metal class pixels of the uncorrected reconstructed image (T) with pixel values of the bone density class to generate a metal free image. A morphological algorithm (80) applies prior knowledge of the subject's anatomy to the metal free image to correct the shapes of the class regions to generate a model tomogram image. A forward projector (88) forward projects the model tomogram image to generate model projection data (Smodel). A corrupted rays identifying algorithm (100) identifies the rays in the original projection data (S) which lie through the regions containing metal objects.

Abstract: A method for selecting vertices for performing deformable registration of imaged objects is provided. The selected vertices form corresponding pairs, each pair including a vertex from a first imaged object and a vertex from a second imaged object. The corresponding vertex pairs are sorted in order of distance between the vertices making up the corresponding vertex pair. The corresponding vertex pair with the greatest distance is given top priority. Corresponding vertex pairs that lie within a selected distance from the selected corresponding vertex pair are discarded. In this manner, the number of vertex pairs used for deformable registration of the imaged objects is reduced and therefore allows for processing times that are clinically acceptable.

Abstract: A method and apparatus accounting for tumor motion during radiation therapy is provided. The method allows for radiation therapy treatments based on updated radiation therapy plans. For each fractionate radiation treatment that results in an updated radiation treatment, radiation treatment images are acquired, automatically segmented, and then subject to deformable registration to develop updated contours and an updated radiation therapy plan.

Abstract: A system and method for developing radiation therapy plans and a system and method for developing a radiation therapy plan to be used in a radiation therapy treatment is disclosed. A radiation therapy plan is developed using a registration of medical images. The registration is based on identifying landmarks located within inner body structures.

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: The method according to the invention is arranged to segment a surface in a multi-dimensional dataset comprising a plurality of images, which may be acquired using a suitable data-acquisition unit at a preparatory step 2. It is possible that data processing and data acquisition steps are temporally or geographically distanced, so that at step 4 the results of a suitable data segmentation step 6 are accessed, whereby said results comprise portions of the image which are subsequently used to segment the surface using the method of the invention. Next, at step 8 a suitable plurality of image features resembling possible spatial positions of the surface conceived to be segmented are selected and accessed. The features are subsequently matched for all image portions at step 10, whereby for each feature a matching error is assigned. At step 14 a pre-defined selectivity factor is accessed defining a maximum allowable variable fraction of the features having largest matching errors which can be discarded.

Abstract: The invention relates to a method of segmenting a three-dimensional structure from a three-dimensional, and in particular medical, data set while making allowance for user corrections. The method is performed with the help of a deformable three-dimensional model whose surface is formed by a network of nodes and mashes that connect these nodes. Once the model has been positioned at the point in the three-dimensional data set at which the structure to be segmented is situated and positions of nodes have, if necessary, been changed by known methods of segmentation, any desired nodes can be displaced manually. The nodes of the model are re-calculated by making weighted allowance for the nodes that have been displaced manually.

Abstract: A registration process that allows for assessment of deformation in the gastrointestinal region is provided. The registration process includes a classification process that classifies image data into the type of material imaged. The registration process further includes an automated segmentation process that allows for identification of the materials in the imaging region and allows for removal of objects, such as stool, from imaging data to allow for registration of images.

Abstract: The invention relates to a method for segmentation of a three-dimensional structure in a three-dimensional data set, especially a medical data set. The method uses a three-dimensional deformable model, wherein the surface of the model consists of a net of polygonal meshes. The meshes are split into groups, and a feature term is assigned to each group. After the model has been placed over the structure of interest, the deformable model is recalculated in consideration of the feature terms of each group.

Abstract: A reconstruction processor (34) reconstructs acquired projection data (S) into an uncorrected reconstructed image (T). A classifying algorithm (66) classifies pixels of the uncorrected reconstructed image (T) at least into metal, bone, tissue, and air pixel classes. A clustering algorithm (60) iteratively assigns pixels to best fit classes. A pixel replacement algorithm (70) replaces metal class pixels of the uncorrected reconstructed image (T) with pixel values of the bone density class to generate a metal free image. A morphological algorithm (80) applies prior knowledge of the subject's anatomy to the metal free image to correct the shapes of the class regions to generate a model tomogram image. A forward projector (88) forward projects the model tomogram image to generate model projection data (Smodel). A corrupted rays identifying algorithm (100) identifies the rays in the original projection data (S) which lie through the regions containing metal objects.

Abstract: A method and apparatus accounting for tumor motion during radiation therapy is provided. The method allows for radiation therapy treatments based on updated radiation therapy plans. For each fractionate radiation treatment that results in an updated radiation treatment, radiation treatment images are acquired, automatically segmented, and then subject to deformable registration to develop updated contours and an updated radiation therapy plan.