Koninklijke Philips Corporation N.v.

Shérif Makram-Ebeid

Jean-Michel Rouet

Maxim Fradkin

Raoul Florent

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

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

Image processing system for generating a multidimensional adaptive oriented filter to be applied to the point intensities of a d-dimensional image, comprising analyzing means with means (, fi) to estimate at each image point a probability measure (Fi) of the presence of a type of feature of interest and a weighting control model () issuing a weighting control vector (, VC) constructed from said probability measure, for the user to control synthesized adaptive kernels at each image point; and synthesizing means for generating the filter kernels at each image point adapted to the type of the features of interest, whose filtering strength is controlled by the weighting control vector. The system may comprise a selection unit () for the user to select synthesizing means for generating 'pre-mixing filtering means' comprising combining means (, XH) dependent on the type of the image features having inputs for the weighting control vector (, VC) and the image data [I(x)] and having an aspect for weighted adaptive kernels (, H) adapted to the type of the image features to produce the filtered image signal [H(x)], and/or 'post-mixing filtering means' comprising both isotropic and anisotropic filtering means [, gi)] applied independently of the type of the image features, whose outputs (Gi) are combined at each image point and adapted using the weighting control vector (, VC) to produce the filtered image signal [G(x)].

Image viewing system and method for generating filters for filtering image features according to their type

An image processing system, for correlating shapes in multi-dimensional images including image data processor for estimating a similarity measure including estimating two image signals representing shapes defined in respective windows in two multi-dimensional images using a Hermite Transform applied to both the image signals for performing an evaluation of two first sets of scalar valued Hermite coefficients from which a combination yields a transformed set of scalar valued Hermite coefficients {K}. The inverse Hermite Transform is applied to the transformed set of scalar valued Hermite coefficients to achieve the computation of a windowed correlation function. The maximum of the windowed correlation function is estimated as the wanted similarity measure to correlate the shapes. The correlated shapes and/or processed images are displayed.

Image processing system and medical examination apparatus for correlating features in medical images

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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Dampierre, France

Shérif Makram-Ebeid