U.S. Philips Corporation

Koninklijke Philips Corporation N.v.

Koninklijke Electronics N.v.

Sherif Makram-Ebeid

Olivier Gerard

Pierre Henri Lelong

Jean-Michel Rouet

Maxim Fradkin

Milena Planells-Rodriguez

Jens Von Berg

Vladimir Pekar

Michael Kaus

Peter Maria Johannes Rongen

Odile Bonnefous

Sylvain Devillers

Gerard M Martin

Pascal Allain

Oudom Somphone

Bert Leo Alfons Verdonck

Jacques Breitenstein

Camille Venger

Philippe Lacour

Bert L A Verdonck

Jean-Pierre Roux

Eric Cohen-Solal

A system for visualizing a myocardium represented by a cardiac image comprises a resampling means and a visualizing means. The resampling means resamples the intensity levels at sampling points on a plurality of curved surfaces, each curved surface enclosing at least part of a heart cavity and zero or more of the plurality of curved surfaces and being enclosed by the remaining curved surfaces of the plurality of curved surfaces, the plurality of curved surfaces together covering a hollow region in the cardiac image, the hollow region comprising the outer cavity walls of a group of at least one heart cavity. The visualizing means is arranged for visualizing at least part of at least one of the plurality of curved surfaces, using resampled intensity levels obtained from the resampling means. The group of at least one heart cavity may be the left atrium alone. It may also be the complete heart.

Cardiac image processing and analysis

Method of image processing, the method comprises providing a sequence () of images (F) which have contrast modulation () along said sequence (); providing a reference frequency (fm,) related to said contrast modulations () along said sequence (); and filtering said sequence of images depending on said reference frequency (fm,). According to an embodiment, a windowed harmonic filtering is applied to the sequence of input images to extract fundamental in-phase () and quadrature () components at a heart beat frequency (fm). The resultant time-signal phase is displayed () as image sequence.

Filtering of image sequences

A method and an apparatus for segmenting contours of objects in an image is disclosed. It particularly applies to the segmentation of body organs or parts depicted in medical images. An input image containing at least one object comprises pixel data sets of at least two dimensions. An edge-detected image is obtained from the input image. Markers are selected in the edge-detected image, and assigned respective fixed electrical potential values. An electrical potential map is generated as a solution to an electrostatic problem in a resistive medium having a resistivity dependent on the edge-detected image, with the markers defining electrodes at the respective fixed potential values. Object contours are estimated, for example by thresholding, from the generated potential map.

Conformal segmentation of organs in medical images

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 method for extracting geometrical data from a 2-D digital image of the spine, comprising steps for determining spine outlines, endplates and corners wherein:

Method and system for extracting spine geometrical data

The invention relates to an image processing method of extracting geometrical data of the spine, for extracting the left and right pedicle landmarks of each spine vertebra, comprising steps of: The invention also relates to a system, a medical apparatus and a program product for carrying out the method. Application: Medical Imaging x-ray Medical System and apparatus; Program Product for Medical Imaging.

Method and system for extracting spine frontal geometrical data including vertebra pedicle locations

A method of deriving geometrical data of a structure from an image of the structure comprises the selection of marker points in the image. A typical contour is associated with the marker points and the geometrical data is calculated from the typical contour. According to the invention, correctness values are associated with the marker points. The correctness values indicate the reliability of the correspondence of the marker points to typical (anatomical) features in the structure. Furthermore, a cost function is associated with a typical contour, which cost function is dependent on the correctness values of the marker points. The typical contour is arranged in such a manner that the cost function reaches an optimum value, such as a local maximum or minimum value. The method is particularly suitable for deriving geometrical data, such as angles and distances concerning the spinal column of a patient. Preferably, some clearly recognizable marker points are manually indicated and derived marker points are obtained by interpolation between the manually indicated marker points.

Deriving geometrical data of a structure from an image

A digital image (J.sub.o) processing method for automatic extraction of strip-shaped objects, includes a skeletonization operation with steps for forming smoothed images (J.sub.i) at several scales (.sigma..sub.i), and, in each smoothed image (J.sub.i), extracting boundaries of objects, extracting potential median pixels (.OMEGA..sub.iP) associated with the center (.OMEGA..sub.i) of a circle of radius (R.sub.i) proportional (k) to the scale (.sigma..sub.i), tangent to boundaries at a pair of distinct pixels (E.sub.1, E.sub.2), and associated with a measure of dependability regarding alignment of the center (.OMEGA..sub.i) and pixels of the pair, extracting median pixels .OMEGA..sub.iM, and constructing skeletons of objects by tracking in the digital image (J.sub.MED) formed by the extracted median pixels. The step of extracting median pixels .OMEGA..sub.im includes a first selection of potential median pixels of the same locations which have the maximum measure of dependability, and a second selection of remaining potential median pixels which locally have a maximum intensity in the direction of alignment .

Digital image processing method for automatic extraction of strip-shaped

A method of processing a digital image representing ribbon-shaped objects of non-uniform intensity contrasting with a background of lower intensity includes an automatic segmentation phase having one or more morphological opening operations effected, respectively, with one or more three-dimensional structuring elements. The latter have a two-dimensional base parallel to the image plane and have a non-binary intensity function in a third dimension. Preferably, the automatic segmentation phase is carried out by means of a set of two-dimensional spatial structuring elements with a third intensity dimension. The set contains N anisotropic structuring elements oriented from .pi./N to .pi./N and one isotropic structuring element.

Method and device for automatic segmentation of a digital image using a

A method for the temporal filtering of an image of a sequence of noisy digitized images includes the evaluation of an integration equation which produces the filtered intensity (P.sub.t.sup.C) of a given pixel �A.sub.t (x,y)! in the present image (J.sub.t.sup.P) by evaluating the sum of the noisy intensity (I.sub.t.sup.P) of the present (t) and the product of a gain factor (K.sub.t.sup.P) and the difference of said noisy intensity of the present (I.sub.t.sup.P) and the causal filtered intensity (P.sub.t-1.sup.C). According to this evaluation, the gain factor (K.sub.t.sup.C) is a function of the causal gain factor (K.sub.t-1.sup.C) and of a continuity coefficient (.alpha..sub.t.sup.C) which measures the probability of intensity continuity between the present noisy intensity (I.sub.t.sup.P) and the causal filtered intensity (P.sub.t-1.sup.C). A device for carrying out this method includes a sub-assembly whose input (100) receives the present noisy sample (I.sub.t.sup.P) and which includes a memory (10) which supplies a causal filtered intensity (P.sub.t-1.sup.C), a memory (17) which supplies a causal gain factor (K.sub.t-1.sup.C), and means for calculating the integration equation.

Method for the temporal filtering of the noise in an image of a sequence

A method of processing digital angiographic images which enables automatic detection of stenoses includes a tracking step for the identification of pixels or points situated on the central lines of vessels, and a step for the detection of stenoses by measurement of the intensity of pixels along the central lines of the vessels. The stenoses detection step includes a sub-step for deciding whether a pixel zone is a potential stenosis zone when the intensity of its pixels exhibits a local variation so as to assume an intermediate value between the intensity of the pixels to both sides of this zone and the intensity of the pixels of the image background, a sub-step for defining an icon around potential stenosis zones, and a sub-step for the extraction of the pixels of edges of the vessel segments in the icons.

Digital image processing method for automatic detection of stenoses

An image processing method for automatic detection of regions of a predetermined type of cancer in an intensity image of a part of a human or animal body, includes, for a number of points of a part of said image, the determination of a set (referred to as a vector) of components formed by characteristic values derived from the intensity distribution around each point in said part of the image, and the use of a classification system for determining the probability of the point associated with said vector belonging to a region of said part of the image which corresponds to the predetermined type of cancer or to another region. An image processing device for carrying out such a method is utilized in conjunction with a digital medical imaging system.

Image processing method and device for automatic detection of regions of

Digital image processing method for local determination of the center and the width of objects in the form of contrasting bands on a background. A digital image processing method, for representation of objects in the form of contrasting bands of substantially uniform intensity on a substantially uniform background, includes a step for the identification of pixels situated on the central lines of the objects, which step is referred to as a 'tracking' step. This method is characterized in that the step includes a first filtering operation which is executed by applying, to each image, a series of N lozenge-type-bidimensional, selective, recursive low-pass filters having respective ones of the principal directions angulary spaced apart 180.degree./N in order to determine the direction of each band-shaped object segment as that in which the response of one of the filters is maximum.

Digital image processing method for local determination of the center

The invention relates to a method of learning which is carried out in a neural network operating on the basis of the gradient back-propagation algorithm. In order to determine the new synaptic coefficients with a minimum learning period, the invention introduces parameters which privilege corrections based on the sign of the error at the start of learning and which gradually induce less coarse corrections. This can be complemented by other parameters which favor a layer-wise strategy, accelerating the learning in the input layers with respect to the output layers. It is also possible to add a strategy which acts on the entire neural network.

Growing community of inventors

Dampierre, France

Sherif Makram-Ebeid