Image analysis – Pattern recognition – Feature extraction
Reexamination Certificate
1998-05-20
2002-08-06
Au, Amelia M. (Department: 2723)
Image analysis
Pattern recognition
Feature extraction
C382S205000
Reexamination Certificate
active
06430315
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention relates to an image processing method which includes the acquisition of an intensity image formed by a matrix of points having non-binary intensity values, representing filiform objects, which method also includes steps for the detection of filiform objects.
The invention is used for the manufacture of, for example, X-ray apparatus
2. Description of the Related Art
A method for the detection of edges is already known from the publication “IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, Vol. 14, No. 9, September 1992, Object Delineation in Noisy Images by a Modified Policy-Iteration method, by Adrie C. M. Dumay, Harielle N. A. J. Claessens et al., pp. 952-958”.
The cited publication describes an algorithm for the detection of contour lines of isolated objects in noisy images; it is a version of a method which is well known to those skill in the art as the dynamic programming method. The dynamic programming method can be applied in two circumstances: it is a method for searching the shortest path for linking group of points at minimum cost. It is necessary to supervise this method; therefore, it cannot be automated.
SUMMARY OF THE INVENTION
It is an object of the present invention to propose an image processing method as d fined above which can be applied in more circumstances than the known dynamic programming method: the calculation steps must be performed in an automatic fashion; the umber of steps must also be as small as possible; these steps must determine the shortest th for linking a group of points relating to an individual filiform object, at a cost which is as low as possible; the path chosen should include the largest possible number of points of e filiform object, and hence should be as long and as regular as possible in the image.
The condition that the path found should have the highest possible density of point relating to the filiform object is not known from the dynamic programming method.
According to the invention this problem is solved by an image processing method which includes the acquisition of an intensity image formed by a matrix of points having non-binary intensity values, representing filiform objects, which method also includes steps for the detection of filiform objects, which steps include:
automatic determination of a field of intensity vectors ({right arrow over (V)}), forming an image of states constituted by characteristics concerning magnitudes and angles [∥{right arrow over (V)}∥,&thgr;] of intensity vectors a the various points of the intensity image,
an operation for chaining the points of an individual filiform object by means of automatic filtering [Q(i)] of the image of the states, thus performing a selection of a dense and continuous field of intensity vectors corresponding to points of the filiform object.
This method offers the advantage that it applies to the processing of medical X-ray images which originally have a low contrast, for example arteriograms. In the case of pulmonary arteriogram this method enables, for example the automatic segmentation of arteries different diameters with respect to the background which contains a disturbing representation of ribs. In the case of a cerebral arteriogram this method enables, for example automatic segmentation of criss-crossing arteries. Generally speaking, this method offers the advantage hat it provides improved detection and reconstruction of edges or lines for numerous types of objects represented in images, irrespective of the origin of these images.
A medical imaging apparatus which includes means for carrying out this method comprises:
a system for the acquisition of data representing an image in the form of a two-dimension matrix of points which have non-binary intensity values and are denoted by their co-ordinate in the matrix,
an image processing system which includes a microprocessor which has access to the data representing the image and is provided with means for carrying out the steps of the method,
and a system for the display and/or storage of image data acquired and/or processed b the method.
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Sun, Ying, “Automated identification of vessel contours in coronary arteriograms by an adaptive tracking algorithm”, pp. 78-88, Mar. 1989.*
“Object Delineation in Noisy Imaged by a Modified Policy-Iteration Method”, by Adrie C.M. Dumay, Harielle N.A.J. Classens et al., in IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 952-958.
Au Amelia M.
Koninklijke Philips Electronics , N.V.
Miller Martin E
Vodopia John
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