Koninklijke Philips Corporation N.v.

Philips Intellectual Property & Standards Gmbh

Michael Kaus

Vladimir Pekar

Todd R McNutt

Juergen Weese

Daniel Bystrov

Jens Von Berg

Stewart Young

Heinrich Schulz

Thomas Netsch

Steven Lobregt

Torbjoern Vik

Jürgen Weese

Matthias Wolfgang Meyer

Michael Adam Meltsner

Ying Xiong

Laura A Dawson

Rafael Wiemker

David Anthony Jaffray

Sherif Makram-Ebeid

Jean-Michel Rouet

Olivier Gerard

Lothar Spies

Himanshu P Shukla

Ingwer Curt Carlsen

Maxim Fradkin

Holger Timinger

Thomas G Purdie

Ruediger Grewer

Christian Adrian Cocosco

R Keith Tipton

Todd Mcnutt

Sebastian Dries

Jeremy D P Hoisak

Celine Saint Olive

Anja Hennemuth

Todd R Mcnutt

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. The user iteratively adjusts the compensator model until the dose distribution is optimized, at which time the optimized compensator model is stored to memory and/or output to a machining device that constructs a compensator from the optimized model.

Interactive computer-aided editor for compensators used in radiotherapy treatment planning

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.

Deformable registration of images for image guided radiation therapy

When performing multimodal radiotherapy planning, an optimizer () concurrently optimizes a combined treatment plan that employs an intensity modulated radiotherapy (IMRT) device () and an intensity modulated proton therapy (IMPT) that respectively generate a photon beam and an ion beam for treating a volume of interest () in a patient (). A simulator () iteratively generates multiple variations of a simulation model () according to optimization parameters that are varied by the optimizer () until the simulation model () satisfies user-entered treatment objective criteria () (e.g., maximum dose, does placement, etc.)

Simultaneous multi-modality inverse optimization for radiotherapy treatment planning

An exemplary embodiment of the invention provides a method for producing a triangulation of a surface of a physical object the method comprising the steps of generating an intermediate mesh representation of the surface out of surface voxels () and detecting at least one T-junction in the intermediate mesh representation (). The method further comprising the steps of decomposing of the at least one T-junction into at least one triangle and at least one two-point-polygon (), and generating the triangulation of the surface out of the modelled intermediate mesh representation ().

Triangulation method of a surface of a physical object

An apparatus for delineating a structure of interest includes: a plane selection interface for selecting a contouring plane of selectable orientation in a three-dimensional image or map; a contouring interface for defining a contour in the selected contour plane; and a mesh constructor configured to construct a three-dimensional polygonal mesh delineating the structure of interest in the three-dimensional image or map. The mesh constructor positions constrained vertices on or near a plurality of non-coplanar delineation contours defined using the contouring interface.

Efficient user interaction with polygonal meshes for medical image segmentation

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.

Region-competitive deformable mesh adaptation

Quantification of metric or functional parameters often requires image segmentation. A crucial part of such method is the model of the surface characteristics of the object of interest (features), which drives the deformable surface towards the object boundary in the image. According to the present invention, sections of the mesh are assigned to different classes for different features. According to the present invention, the assignment of mesh sections to the classes is adapted by using actual feature information from the unseen image. Advantageously, this allows for an adaptation of the feature category to which the mesh section is assigned and thereby allows an improved segmentation of the object.

Image segmentation by assigning classes to adaptive mesh primitives

When modeling anatomical structures in a patient for diagnosis or therapeutic planning, an atlas () 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.

CT surrogate by auto-segmentation of magnetic resonance images

A method of data processing is provided for estimating a position of an object in an image from a position of a reference object in a reference image. The method includes learning the position of the reference object in the reference image and its relation to a set of reference landmarks in the reference image, accessing the image, accessing the relation between the position of the reference object and the set of the reference landmarks, identifying a set of landmarks in the image corresponding to the set of the reference landmarks, and applying the relation to the set of landmarks in the image for estimating the position of the object in the image.

Method, an apparatus and a computer program for data processing

When adapting models of anatomical structures in a patient for diagnosis or therapeutic planning, an atlas () 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 () of a patient. A user can click on an initially unapproved segmentationlandmark () on the patient image (), reposition the unapproved landmark, and approve the repositioned landmark. Remaining unapproved landmarks () are then repositioned as a function of the position of the approved landmark () using one or more interpolation techniques to adapt the model to the patient image on the fly.

Interactive image segmentation

An apparatus for delineating a structure of interest includes: a plane selection interface () for selecting a contouring plane of selectable orientation in a three-dimensional image or map (); a contouring interface () for defining a contour in the selected contour plane; and a mesh constructor () configured to construct a three-dimensional polygonal mesh () delineating the structure of interest in the three-dimensional image or map. The mesh constructor positions constrained vertices (, Vc) on or near a plurality of non-coplanar delineation contours (, Ccor, Cobl) defined using the contouring interface.

The invention relates to a method of measuring geometric variables of a three-dimensional structure contained in an object from at least on image representing the object, having the following steps:&#x2014;use of a deformable first model describing the structure, the shape of which model can be described by parameters,&#x2014;adjustment of the first model to the structure in the image,&#x2014;determination of the parameters at which the first model exhibits optimum conformity with the structure,&#x2014;use of a deformable second model describing the structure, which second model in shape corresponds to the first model, and which in addition contains at least one geometric variable,&#x2014;modification of the second model according to the parameters determined, and&#x2014;derivation of the geometric variable(s) from the modified second model.

Method of measuring geometric variables of a structure contained in an image

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

Data representation for rtp

A respiratory marker () includes an elongated detectable portion () that is operatively coupled with respiration of an imaging subject such that the elongated detectable portion moves with the respiration. The elongated detectable portion is arranged to intersect images acquired by an imaging scanner () at different times and at different positions along a scanner axis (), and is detectable as a marker feature in the images. A marker position finder () is configured to determine positions of the marker features in the images.

Retrospective sorting of 4D CT into breathing phases based on geometric analysis of imaging fiducials

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.

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Hamburg, Germany

Michael Kaus