An object of the present invention is a process for representing views of an object. This object has to be discriminated in a digital volume. A digital volume results from the acquisition and storage of pieces of information concerning physical characteristics of internal parts of an examined body. The best known mode of acquisition of this information is the tomographic mode. This mode may be performed, especially in the medical field, by various means: nuclear magnetic resonance, tomodensitometry by X-rays, or tomography by gammagraphy or ultrasonic tomography. This acquisition mode may, of course, also be any mode, once it leads to a gathering of pieces of physical information that can be arranged virtually with respect to one another along three orthogonal axes of reference and are supposed to represent, in the virtual position that they occupy, the physical characteristics of corresponding parts in an examined body. Each volume element of this digital volume thus has at least two types of information. A first type concerns the coordinates of a corresponding place in the body (corresponding biuniquely to an address in a storage memory of a computer). The other type represents the value of the physical information which has been assigned to this place and which has been measured, for example by one of the above-mentioned techniques of tomography.
Techniques for the representation of views of objects to be discriminated in digital volumes are already known. There are chiefly two of them. A first technique, developed mainly by G. T. HERMAN and his team, comprises the sequence of the following operations. Taking a given digital volume, reformatted if necessary so that the resolution is identical in all three spatial dimensions, first of all a segmentation is done. The principle of the segmentation consists in comparing the values of the physical information loaded in each of the volume elements with a reference value and in selecting those of these volume elements for which the value of the physical information belongs, for example, to a value range located around this reference value. To simplify the matter, in tomodensitometry, it can be understood that a test on the density will enable differentiation, in the digital volume, of the volume elements corresponding to bones (high density) and the volume elements corresponding to soft tissue (low density). It is then possible to have a collection of addresses of memory cells that correspond to chosen volume elements and the set of which defines the object thus segmented.
The principle of the representation then consists in attributing a visible surface to each of the chosen volume elements (which, however, are located on the surface of the segmented object), computing an orientation of this surface (in estimating an orientation of the normal to it), and assessing the luminous contribution of this surface to an image of a view when this surface is exposed to a given illumination (namely, to an illumination coming, for example, from a precise point of the space external to the segmented object). The locations of the chosen volume elements, and hence of the corresponding visible surfaces being known, they can be attributed, in the image of the view to be represented, elements of the surface of this image for which the coordinates, in the image, depend on the point of view from which the segmented object is looked at. These surface elements are then assigned a luminosity representing the contributions of the visible surfaces to which they are assigned. The set of all the surface elements of the image constitutes the image of the view of the object.
This process has drawbacks; in particular, the shading is not satisfactory therein. For, the image obtained shows an effect of line artefacts or circle artefacts that seem to match the contours of the segmented object, in doing so irrespectively of the orientation of the illumination, and irrespectively of the viewpoint of observation of this object. These artefacts of contours are particularly discernible in the representation of surfaces with low relief. Although it is possible, at the extreme, to make do with them by mentally removing them during the examination of the view represented, it cannot be denied that these very same faults appear in the more uneven parts, with greater relief, of the views presented. For these parts, it then becomes impossible to distinguish the true representation from the artefact in the image.
This process further has another drawback which is related to the computation of the orientation of the visible surfaces. Briefly, the segmentation leads to assigning a piece of binary information, for example 1 and 0 respectively, to the volume elements chosen and to those that have been set aside. The orientation of the visible surface assigned to a chosen volume element is computed, in a standard way, by taking into account the distribution of the "ones" and "zeros", in the volume elements directly neighboring the chosen volume element. This leads, firstly, to a restricted number of possibilities of orientation of this surface (81 possible orientations if the 26 volume elements directly neighboring the chosen volume element are taken), above all if we take into account the fact that because of the observation viewpoint, this number of possibilities is divided by two. Secondly, this computation leads, in certain borderline cases, to showing a scintillation in the image. For, if the physical information tested for a set of adjacent volume elements is very close to the limit of the range of segmentation, some of these volume elements will be chosen, and others will not. The result thereof may be a crenelated outline of the segmented object at this position whereas its true shape may be smooth, but located, in terms of value of physical information, at a level that is a source of difficulty in view of the criterion chosen to do the segmentation. This crenelated profile causes the scintillation of the image.
Another process of representation, derived from techniques of image synthesis and computer-aided design, is aimed at achieving a segmentation in memory planes of the memory volume that corresponds to sections of the digital volume. For example, all the sections perpendicular to a given axis (an axis Z) are segmented. In all these sections, using correlation methods, it is possible to trace a "smoothened" contour of the section of the segmented object. Then, in a subsequent operation, the contours belonging to each of the adjacent sections are associated so as to determine facets of chosen dimensions which are generally triangular. A triangular facet is, for example, defined by three points, two of them belonging to a contour in one section, a third one belonging, in intermediate position, to a contour in an adjacent section. The position of each facet is known and, in the displayed image, a surface element of this image can be made to correspond to it. The luminous contributions for these facets are also computed, and the image of the view is then built. This technique suffers from the earlier drawbacks, albeit to a lesser degree. The artefacts of contours are all the same present when these contours are aligned along the axis to which the sections used are perpendicular. Furthermore, this other technique has a major drawback: it is unwieldy to implement by means of standard computers. It practically cannot be contemplated unless the number of the facets to be shown in the image is restricted to 5,000 to 10,000 facets. Now, for medical images, or more generally for images representing unknown objects that have to be recognized (and not symbolic objects that can be used in simulation), the number of facets to be represented is of the order of 500,000 to 1,000,000. The computation times relating to this technique are then no longer acceptable.