Abstract: A computer based method of obtaining a 3D image of a part of a patient's body is disclosed, based on a fraction image having a limited field-of-view and extending the field of view with information from an image of the patient's outline, obtained from a surface scan of the patient. Anatomical data from the planning image are preferably used to fill in the outline image, by means of a contour-guided deformable registration between the planning image and contour.

Abstract: An approximate image of a patient can be provided by the following method: Obtaining a model of the contour of a patient's body or a part of the patient's body, based on a surface scan of the patient Setting at least one interior density or image intensity value for at least a part of the interior of the contour to provide an approximation of the density of the patient's interior Setting an exterior density or image intensity value for the region outside of the contour, Creating an approximate image based on the model of the contour, and the density or image intensity values. The interior density or intensity may be set to a uniform image intensity value for the whole image or one or more regions, such as organs or bone, may be distinguished by different density of image intensity values.

Abstract: A computer based method of obtaining a 3D image of a part of a patient's body is disclosed, based on a fraction image having a limited field-of-view and extending the field of view with information from an image of the patient's outline, obtained from a surface scan of the patient. Anatomical data from the planning image are preferably used to fill in the outline image, by means of a contour-guided deformable registration between the planning image and contour.

Abstract: A method for generating data representing the volume of part of a body, the method comprising generating a point distribution model “PDM” based on an input dataset comprising data representing at least one surface of part of a body, the PDM defining a surface model dataset based on an average dataset and one or more weight-eigenvector pairs, generating a first surface model dataset based on the PDM by modifying at least one weight of the one or more weight-eigenvector pairs, wherein the first surface model dataset is different from the average dataset, and generating an output volume dataset based on the first surface model dataset and a first reference dataset, the first reference dataset comprising data representing the volume of a corresponding part of a body, the output volume dataset comprising data representing a deformed volume of the corresponding part of the body.

Abstract: An anatomic structure of interest is contoured in 3D source data by selecting a first subset of data in a first image slice, which has a first orientation in the source data. A first set of instructions identifies a first edge (E1) of the anatomic structure of interest in the first image slice. Then, a second subset of data is selected in a second image slice, which has a second orientation in the source data. A second set of instructions identifies a second edge (E2) of the anatomic structure of interest in the second image slice. A three-dimensional shell (3DS) is calculated based on the first and second edges (E1; E2) and the source data (SD). The three-dimensional shell (3DS) represents an approximation of a delimiting surface that separates the anatomic structure of interest from adjoining tissues in the 3D source data.

Abstract: An anatomic structure of interest is contoured in 3D source data by selecting a first subset of data in a first image slice, which has a first orientation in the source data. A first set of instructions identifies a first edge (E1) of the anatomic structure of interest in the first image slice. Then, a second subset of data is selected in a second image slice, which has a second orientation in the source data. A second set of instructions identifies a second edge (E2) of the anatomic structure of interest in the second image slice. A three-dimensional shell (3DS) is calculated based on the first and second edges (E1; E2) and the source data (SD). The three-dimensional shell (3DS) represents an approximation of a delimiting surface that separates the anatomic structure of interest from adjoining tissues in the 3D source data.

Abstract: A data processing unit receives a reference image (IMG13D) of a deformable physical entity, a target image (IMG23D) of said physical entity, and a first region of interest (ROI13D) defining a first volume in the reference image (IMG13D) representing a reference image element. The reference image (IMG13D), the target image (IMG23D) and the first region of interest (ROI13D) all contain 3D datasets. In response to user commands (c1; c2), the data processing unit defines a first contour (C12D) in a first plane through the target image (IMG23D), which is presented to a user via a display unit together with graphic data reflecting the reference image (IMG13D), the target image (IMG23D) and the first region of interest (ROI13D). The first contour (C12D) is aligned with at least a portion of a first border (IEB1) of a target image element (IE3D) in the target image (IMG23D). The target image element (IE3D) corresponds to the reference image element in the reference image (IMG13D).

Abstract: An anatomic structure of interest is contoured in 3D source data by selecting a first subset of data in a first image slice at a first axial position (z1). A first set of instructions identifies a first edge (E1) of the anatomic structure of interest in the first image slice. Then, a second subset of data is selected in a second image slice at a second axial position (z2); and a second set of instructions identifies a second edge (E2) of the anatomic structure of interest in the second image slice. A three-dimensional shell (3DS) is calculated based on the first and second edges (E1; E2) and the source data (SD). The three-dimensional shell (3DS) represents an approximation of a delimiting surface that separates the anatomic structure of interest from adjoining tissues in the 3D source data.

Abstract: An anatomic structure of interest is contoured in 3D source data by selecting a first subset of data in a first image slice at a first axial position (z1). A first set of instructions identifies a first edge (E1) of the anatomic structure of interest in the first image slice. Then, a second subset of data is selected in a second image slice at a second axial position (z2); and a second set of instructions identifies a second edge (E2) of the anatomic structure of interest in the second image slice. A three-dimensional shell (3DS) is calculated based on the first and second edges (E1; E2) and the source data (SD). The three-dimensional shell (3DS) represents an approximation of a delimiting surface that separates the anatomic structure of interest from adjoining tissues in the 3D source data.

Abstract: A data processing unit receives a reference image (IMG13D) of a deformable physical entity, a target image (IMG23D) of said physical entity, and a first region of interest (ROI13D) defining a first volume in the reference image (IMG13D) representing a reference image element. The reference image (IMG13D), the target image (IMG23D) and the first region of interest (ROI13D) all contain 3D datasets. In response to user commands (c1; c2), the data processing unit defines a first contour (C12D) in a first plane through the target image (IMG23D), which is presented to a user via a display unit together with graphic data reflecting the reference image (IMG13D), the target image (IMG23D) and the first region of interest (ROI13D). The first contour (C12D) is aligned with at least a portion of a first border (IEB1) of a target image element (IE3D) in the target image (IMG23D). The target image element (IE3D) corresponds to the reference image element in the reference image (IMG13D).

Abstract: A method for atlas-based segmentation is provided where a patient image is rigidly registered with each of a plurality of atlas images. Based on the rigid registration results, which indicate a degree of similarity for each atlas, an atlas image is selected for deformable registration where the rigid registration result is used as initialization. Regions of interest are segmented in the patient image using the results of the deformable registration.

Abstract: A method for atlas-based segmentation is provided where a patient image is rigidly registered with each of a plurality of atlas images. Based on the rigid registration results, which indicate a degree of similarity for each atlas, an atlas image is selected for deformable registration where the rigid registration result is used as initialization. Regions of interest are segmented in the patient image using the results of the deformable registration.