Koninklijke Philips Corporation N.v.

Koninklijke Electronics N.v.

Maxim Fradkin

Jean-Michel Rouet

Shérif Makram-Ebeid

Sherif Makram-Ebeid

Franck Laffargue

Francois Guy Gerard Marie Vignon

Jens Von Berg

Vladimir Pekar

Michael Kaus

Grzegorz Andrzej Toporek

Kunal Vaidya

Olivier Gerard

Benoit Jean-Dominique Bertrand Maurice Mory

Benoit Mory

Sibo Li

Emmanuel Mocé Serge Attia

Benoit Jean-dominique Bertrand Maurice Mory

Cybele Ciofolo

Vipul Shrihari Pai Raikar

In some examples, two dimensional (2D) datasets, such as images, may be transformed into three dimensional (3D) datasets (e.g., volumes). The values and material properties of voxels of the 3D dataset may be based, at least in part, on values of pixels in the 2D dataset. A 3D scene of the 3D dataset may be rendered from a plane parallel to a plane of the 2D dataset to generate a 'top-down' render that may look like a 2D image. In some examples, additional coloring may be added to the rendered 2D image based on intensity or other properties of the 2D dataset.

Rendering of two dimensional data sets

An end effector state estimation system for use in minimally invasive surgery (MIS) applications performs sensing and prediction algorithms to determine and visualize the state of an implantable therapeutic device during deployment. The end effector state estimation system includes a flexible elongate member, a therapeutic device coupled to a distal portion of the flexible elongate member, a sensor that measures at least one parameter related to the deployment state of the therapeutic device, and a processor. The processor receives image data from an imaging system representative of the therapeutic device positioned within the body cavity of the patient and the at least one parameter from the sensor, determines the deployment state of the therapeutic device based on the image data and the at least one parameter, outputs a graphical representation of the deployment state of the therapeutic device.

Medical imaging systems, devices, and methods for visualizing a deployment state of an intracorporeal therapeutic device

An image processing method, comprising acquiring an image of a 3-D tubular object of interest to segment; computing a 3-D path that corresponds to the centerline of the tubular object and defining segments on said 3-D path; creating an initial straight deformable cylindrical mesh model, of any kind of mesh, with a length defined along its longitudinal axis equal to the length of the 3-D path; dividing this initial mesh model into segments of length related to the different segments of the 3-D path; computing, for each segment of the mesh, a rigid-body transformation that transforms the initial direction of the mesh into the direction of the related segment of the 3-D path, and applying this transformation to the vertices of the mesh corresponding to that segment. The method comprises avoiding self-intersections in the bent regions of the tubular deformable mesh model and sharp radius changes from one segment of the mesh model to the other, by adapting or modulating the radius of the cylindrical deformable mesh model according to the local curvature of the 3-D path, sample distance of the path points and a predefined input radius.

Image processing method for automatic adaptation of 3-D deformable model onto a substantially tubular surface of a 3-D object

The invention relates to a system () for delineating an anatomical structure in an image computed from a slice of image data, the system () comprising a partition unit () for partitioning the image into a plurality of image portions, each image portion depicting a portion of the anatomical structure, and an adaptation unit () for adapting a template to the image based on a criterion function, the criterion function being a function of template parameters and of image values and their relative positions in the image, and on a criterion to be satisfied by a computed value of the criterion function, wherein the criterion function is defined on the basis of the plurality of image portions. Having a criterion function defined on the basis of the plurality of image portions allows computing optimal contributions to the criterion function value within each portion of the image. This is proven to be particularly useful for extracting myocardial contours in a slice of the LEMR short-axis volume image data in the presence of scar tissues. The invention allows optimizing the treatment of portions of the image comprising scar tissue in the myocardium.

Automatic 3-D segmentation of the short-axis late-enhancement cardiac MRI

The invention relates to a system () for delineating endocardial and epicardial contours of the heart in an image computed from long-axis image data, using a template defining curves for delineating the endocardial and epicardial contours in the image, the system () comprising a template-positioning unit () for positioning the template on the basis of short-axis image data, a scar map initialization unit () for initializing a scar map for use in adapting the template to the image, based on a prior segmentation of the endocardial and epicardial surfaces on the basis of the short-axis image data, and an adaptation unit () for adapting the template to the image, using a criterion function, the criterion function comprising terms describing the attraction of the template to image features and terms describing internal interactions within the template, and wherein at least one term of the criterion function is defined on the basis of the scar map. Identifying image pixels comprised in the scar map improves the definition of the criterion function by including at least one and possibly a plurality of criterion function terms defined on the basis of the scar map. Including criterion function terms defined on the basis of the scar map for adapting the template (i.e. a deformable model) for defining the endocardial and epicardial contours to the long-axis image data helps avoiding exclusion of the scar tissue from the delineated myocardial tissue and thus improves the delineation of the endocardial and epicardial contours of the heart.

Segmentation of the long-axis late-enhancement cardiac MRI

An image processing system having means of automatic adaptation of 3-D surface Model to image features, for Model-based image segmentation, comprising: dynamic adaptation means for adapting the Model resolution to image features including locally setting higher resolution when reliable image features are found and setting lower resolution in the opposite case. This system comprises estimation means for estimating a feature confidence parameter for each image feature. The model resolution is locally adapted according to said parameter. The feature confidence parameter depends on the feature distance and on the estimation of quality of this feature including estimation of noise. The large distances and the noisy, although close features are penalized. The resolution of the Model is decreased in absence of confidence and is gradually increased with the rise of feature confidence.

Image processing system for automatic adaptation of a 3-D mesh model onto a 3-D surface of an object

An image processing system, for processing a 3-D image of a 3-D substantially tubular structure (AAA), formed of a lumen (LUM) limited by a wall (), comprising processing means () for segmenting the 3-D external or internal surface of the structure; estimating a local parameter such as the local wall thickness (T) or diameters; and display means () for displaying the 3-D surface of segmentation with zones colorized according to a color code, so that to indicate the local parameter values in said zones. The system may comprise processing means to generate () a 3-D virtual cylinder and projecting () the color-coded 3-D segmentation surface onto the 3-D virtual cylinder surface colorized according to the same color-code; and projecting the 3-D virtual cylinder surface onto a 2-D color-coded map; and display means for displaying the 2-D color-coded map with colorized zones indicating the local parameter values (T) in said zones ().

Image processing system for displaying information relating to parameters of a 3-D tubular object

An image processing system comprising 3D image data processing means of automatic mapping a 3-D Surface Model onto the surface of an object of interest in a 3-D image, for estimating a model-based 3-D segmentation surface, comprising visualizing means and further comprising means of interactive adaptation of the segmentation surface to the actual surface of the object of interest including means of interactive selection of a 2D data plane (DP) that intersects the 3-D segmentation surface along a 2-D Model Curve (MC), said Data Plane having a user-selected orientation with respect to said surface, which is appropriate for the user to visualize a 2-D portion called Aberrant Curve (AC) of said Model Curve to be modified; means of interactive definition of a Guiding Curve (GC) in the 2-D Data Plane; means of interactive adaptation of said Aberrant Curve (AC) to said Guiding Curve (GC); and means of further automatically adapting the 3D segmentation surface within a neighborhood of the interactively adapted Aberrant Curve. The surface Model is favorably a Mesh Model.

Three-dimensional segmentation using deformable surfaces

The invention relates to an image processing method for displaying a processed image of a three dimensional (3-D) object using a two-dimensional display means and for interacting with the surface of the displayed 3-D object comprising the construction and display of at least two coupled views of the surface of the 3-D object, including a global 3-D view and a connected local 2-D view of the surface of said object on which local interactions are made. This method further comprises interactive navigation on the object surface in one of the two views and processing data in said view with automatic updating of corresponding data in the other coupled view. Application: Medical Imaging.

Image processing method for interacting with a 3-D surface represented in a 3-D image

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.

Method of segmenting a three-dimensional structure

A medical viewing system having means, for analysing and visualising medical image data corresponding to folded surfaces, comprises means of segmentation of the image data to identify the object surface, means for approximating the object surface by a reference surface, and means for detecting folded portions of the object surface including means for determining points of the reference surface at which a normal to a zone forming a patch on the reference surface intersects with the object surface. If there are more than one point of intersection, then that patch corresponds to a folded portion of the object surface. Fold-portion patches are assigned a code such that, on display or printing of an image (RP) corresponding to the reference surface, the fold-portions will be flagged (for example by coloured or patterned regions (HP). Other fold-attribute data can also be determined, coded and displayed: for example, the number and location of intersections between the first surface and the normal to the fold-portion patch, the distance to the first intersection, the distance between the second and third intersections, etc.

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Paris, France

Maxim Fradkin