Classifications

• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
  • A61B6/48—Diagnostic techniques
  • A61B6/481—Diagnostic techniques involving the use of contrast agents
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
  • A61B6/50—Clinical applications
  • A61B6/504—Clinical applications involving diagnosis of blood vessels, e.g. by angiography
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T7/00—Image analysis
  • G06T7/50—Depth or shape recovery
  • G06T7/55—Depth or shape recovery from multiple images
  • G06T7/593—Depth or shape recovery from multiple images from stereo images
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/10—Image acquisition modality
  • G06T2207/10116—X-ray image
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/30—Subject of image; Context of image processing
  • G06T2207/30004—Biomedical image processing
  • G06T2207/30101—Blood vessel; Artery; Vein; Vascular
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2211/00—Image generation
  • G06T2211/40—Computed tomography
  • G06T2211/404—Angiography

Definitions

• the present invention relates to a three-dimensional (3D) tree reconstruction method by labeling. It is mainly intended for use in the medical field, where the trees studied are angiographic trees.
• the three-dimensional reconstruction makes it possible, by subsequent information processing on the reconstructed object, to present this object according to any modes: straight cuts, oblique cuts, or even 3D visualization.
• the 3D visualization of 3D objects is also known.
• the invention is essentially concerned with the acquisition of geometric information representative of a 3D tree structure, this information being subsequently used in visualization methods for visualizing this tree structure.
• the particularity of the method of the invention is that it allows the reconstruction of trees from two two-dimensional digital images in projection of the object to be reconstructed.
• the field of application of the invention is in particular the study of the vascular network (arterial and venous) of any region of the human body having a tree structure (heart, brain, femoral artery, carotid, ).
• the mode of acquisition of projected images is independent of the method.
• the invention is described in a radiology application, it can be transposed if the projection images are obtained by NMR, by ultrasonic insonification .... Digital radiology or analog X-ray (angiographic technique) currently allows obtaining images well suited to the implementation of the invention.
• the method of the invention is also applicable to any 3D wire structure other than medical.
• the current angiographic reconstruction techniques are partly techniques derived from the computed tomography experiment called scanner.
• the corresponding acquisitions are complicated, on the one hand, by the desire to eliminate from the acquired images the contributions of all that does not represent the angiographic network, on the other hand by the fact that the flow of blood in the vessels is a variable phenomenon over time (it therefore requires synchronization), and finally that the acquisition must be a three-dimensional acquisition.
• injections of products increasing the contrast in the capillaries are used in a known manner. It should be noted, however, that these injections cannot be repeated as often as desired without trauma to the patient.
• the synchronization phenomenon can have the result of increasing the duration of the acquisitions while at the same time being a technique contrary to precautions aiming not to inject contrast product too often into the vessels of a patient.
• three-dimensional reconstruction requires, with scanner methods, the repetition of these experiments.
• One solution to this problem would be to use multirange ultra-detectors in scanners.
• this technique is essentially linked to the systematic use of so-called conical projections because the source X-ray remains punctual.
• the algorithms for reconstructing section images from conical projections do not then allow the desired precision to be achieved to allow the reconstructions.
• a scanner has been designed capable of acquiring the images of four sections at the same time.
• a digital volume is a collection of information, relating to a measured property, and virtually arranged in a volume at 3D addresses corresponding to the locations of the object from which the information originates.
• This system also makes it possible to view all of the structures exhibiting attenuation by X-rays.
• the drawbacks of this system are twofold. Firstly, they are technical: the cost of the material is incompatible with industrial distribution. On the other hand the definition of the images is not sufficient for the detection of fine structures. If a resolution adapted to these fine structures is desired, the number of data to be acquired and processed in a time compatible with medical exploitation requires a substantial increase in the power of the machines.
• the problem is theoretical: the X-ray beam used is a divergent beam.
• the "parallel section" approximation used for the reconstruction is therefore rough, the taking into account of the conical geometry in the reconstruction algorithms prohibits decomposing the problem into a superposition of two-dimensional reconstructions.
• This technique consists of an algorithmic approach by searching for homologous points.
• This method consists in determining, on projection images, homologous points.
• Homologous points are points of the images of each projection which are associated and which correspond to the same point in the 3D space of the tree structure to be reconstructed.
• the algorithmic method makes it possible to calculate the 3D coordinates of the point of the object knowing the acquired images and the geometry of the acquisition system.
• the methodology used in this case is as follows. We seek, with a first algorithm, on a first image in projection, a characteristic point. This characteristic point is located on the path of a particular X-ray. The path of this X-ray is called "straight 3D". The method consists in projecting this 3D line on the second image in projection using the second projection orientation. The homologous point of the chosen characteristic point must be sought in the second projected image: it must be on this 3D line projected so-called epipolar.
• the automatic localization of the characteristic points requires an effective segmentation of the angiographies.
• the precision required in determining a homologous point in stereoscopic condition so that the estimation of the X, Y, Z coordinates of the corresponding points in the object is acceptable, is less than the pixel.
• This constraint can be relaxed if the angle between the shots can be increased, between the directions of projection. This can be obtained by using views whose projection orientations are deviated by an angle close to 90 e .
• three projection images are acquired according to orientations included at an angle of 90 °.
• the object of the invention is to remedy the drawbacks cited by proposing a three-dimensional tree reconstruction method in which only two pieces of equipment can be used and where the absence of the third is compensated for by a priori knowledge of the tree to rebuild.
• the two X-ray tube-camera equipment in a radiological application, are preferably oriented substantially at 90 ° from one another so as to improve the accuracy of the calculation of the point of intersection of the lines corresponding to the homologous points.
• the model in contrast to models already known for typical tree structures, is not a purely topographic model but it is an essentially structural model.
• topographic model we mean a model in which each part of the object is essentially determined by its coordinates as well as by its dimensions.
• structural model we essentially designate a set of information in which each segment of the tree structure is associated with a label representing the number of a bifurcation from which it originates, or of an upstream segment to which it is connected, as well as an orientation relative to a reference. In a way, the structural model is qualitative when the topographic model is quantitative.
• the invention therefore relates to a three-dimensional tree reconstruction method characterized in that: - at least a first image and a second two-dimensional image of a tree to be reconstructed are acquired, these images being obtained by projection of this tree structure in two different orientations, these images being made up of contiguous segments,
• a structural model is developed a priori of the tree structure to be represented, a first segment of the tree structure is reconstructed, - this first segment is assigned a label characteristic of a corresponding segment in the model,
• FIG. 3 a radiology machine usable for implementing the method of the invention
• FIG. 7 the model which is drawn therefrom according to the teaching of the invention.
• Figure 9 the complementary mode in case of failure to use the general mode.
• FIG. 1 represents the general mode of association of two homologous points.
• An object to reconstruct 1 was subjected, in a radiological application, to two X-ray illuminations.
• a first illumination the source was placed at a point 2 and the first projected image was formed on a plane 3 perpendicular to the central ray emitted by the source and placed on the other side of the object 1.
• the second illumination the source was placed at 4 and the second image was projected on a plane 5.
• the structure 1 is shown in double lines. It presents in a simplified manner a foot 6 whose image is projected respectively at 7 and 8 on the planes 3 and 5.
• a coupled luminance intensifier screen At the place of the plans 3 and 5 we have in fact placed a coupled luminance intensifier screen to a camera.
• the cameras associated with the luminance intensifying screens carry out a horizontal scan, oriented along 3 and X5 in each of the two images.
• this particular case is actually the least frequent, and we will often have to search for the counterpart of a particular point 9 which will be the image of a point 10 of the tree structure 1.
• To search for the counterpart of this point we use the fact that the X-ray which ended at point 9 on screen 3 was carried by a line called 3D passing through this point 9 and by the origin 2 of the emission X.
• This projection 11 is called the epipolar line of point 9. It is noted that this epipolar line is at an angle with respect to the axes X5 and Y5 of the plane 5.
• the epipolar line normally includes the point 12 homologous point 9. These two points 12 and 9 are representative, both of them, of point 10 of the tree structure 1.
• point 9 in the plane 3 is located on a segment, and if it is not at the intersection of two segments, there is only one candidate point in the plane 5 for which the equation is verified. Similarly if point 9 happens to be the image of a bifurcation such as for example the bifurcation 13 of the tree 1.
• This another type of ambiguity results from the wide angle presented by the projections 3 and 5 relative to each other.
• this ambiguity was resolved by using another projection, for example on a plane 23 making a relatively small angle with one of the two projections.
• the projections of points 14 to 16 on plane 23 are arranged in the same order as they had on plane 3.
• a small angle of disorientation of the projections makes it possible to keep the concept of arrangement between the points.
• a slight error 24 in assessing the coordinates of the image of a point on a projection sounds like a large error 25 in the position of the point to be reconstructed.
• We will show in the rest of this description how the use of a structural model makes it possible to resolve these ambiguities.
• FIG. 3 represents a radiology machine usable for implementing the method of the invention.
• a patient 26 is subjected to X-ray radiation emitted by a generator 27 in the direction of a luminance amplifier 28 placed on the other side of this patient relative to the generator 27.
• a device 29 for injecting a contrast product is shown schematically to show that the device is intended to acquire angiography images. There are two ways to do this. Or, as shown, the patient is subjected to two successive, synchronized irradiations, having meanwhile moved in correspondence the X-ray tube 27 and the screen 28 on a hoop 30 by means of a motor 31 so as to acquire images whose projection orientation is significantly different. Preferably chooses orientation differences of the order of 90 °.
• a computer 32 makes it possible to manage the acquisition of the images, the synchronization, the injection of the contrast product, as well as a segmentation processing aimed at skeletonizing, in each acquired image, the tree structure.
• FIG. 4a and 4b show in the video-line signal of this camera, the shape of the corresponding gray level signal NG.
• the subtraction operation aims to eliminate the continuous component 33 representative of the bottom, so as to leave only signals such as 34 representative of the vessels alone.
• the projected image is then, in the memory of the computer 32, a collection of addresses X3 and Y 3 with which gray levels are associated (Y3 marks the scanned line) corresponding to the peaks 34 of the detected signals.
• a skeletonization phase rather than being interested in detected points in each image, we are interested in straight segments to which belong these different points.
• each segment is given an attribute. This multidimensional attribute indicates the segment number, the coordinates of its extreme points, the average gray level of the segment, the direction of this segment, and the numbers, numbers, directions, and gray levels of the predecessor and successor segments of this segment.
• This skeletonization operation is known, it has been described in previously published works. In particular it is described in the thesis of Mrs. CHRISTINE TOUMOULIN, defended on November 24, 1987, UNIVERSITE DE RENNES.
• FIG. 5 shows, in terms of segments, the ambiguities resulting from the use of projections forming between them a large angle and not allowing the certain determination of two homologous points in these two projection planes. It was shown, at a bifurcation 38, the birth of two segments 39 and 40 of the object to be reconstructed. The segments 39 and 40 project respectively into 41 and 42 and 43 and 44 on the previous planes 3 and 5. If we draw both dihedrons passing through the sources 2 and 4 of projection and through the segments 39 and 40, one realizes that these dihedrons intersect at the location of the object to be reconstructed according to two other fictitious other segments 45 and 46. Obviously, the segments 45 and 46 are also "solution" for the projection into image segments 41 and 42 and 43 and 44.
• the normal anatomical model is therefore compared to the couple of segments 39 and 40 on the one hand, and to the couple of segments 45 and 46 on the other. Qualitatively it becomes possible to eliminate from these couples the candidate couple who does not meet the model.
• couples are each assigned a label in turn, and it is checked that the label assigned corresponds to their actual appearance.
• FIG. 6 represents, in the case of the left ventricle, in perspective, the representation of the inter-ventricular-anterior arteries IVA and circumflex CX connected in a common trunk to the artery aorta AA by a bifurcation point 47.
• IVA artery and CX artery are supposed to be on the surface of an elipsoid 48.
• This topographic representation is unfortunately not well adapted to the disparities presented by the different individuals and makes impossible the elaboration of simple criteria allowing an automatic reconstruction of the 3D tree. Reconstruction techniques using such a topographic model necessarily require that reconstruction to a large extent be manual. In the invention, on the contrary, everything can be automatic.
• FIG. 7 shows in comparison, for the same structure, the contribution of the invention.
• the IVA artery was generally situated in an interventricular IV plane while the circumflex artery was located in an AV atrioventricular plane.
• directions 49 to 54 said respectively year forward, back, up, down, right, and left.
• the AA aorta artery has a much higher gray level, due to its size, than all of the other vessels. It is therefore possible to be automatically placed on a segment belonging in each image in projection to this aortic artery. For this purpose, the segment for which the gray level is the highest is chosen from all the segments.
• Figure 8a shows the uelettized images obtained respectively in the previous plans 3 and 5.
• P ⁇ , I P2, j be the projections in planes 3 and 5 of the most contrasting starting point in each of the images. It is assumed that these two points are homologous to each other and represents a point Pn of the structure to be reconstructed.
• the point P ⁇ , j belongs to a first element of line D ⁇ f j going from P l , j to P ⁇ , j + ⁇ of the root segment of the tree. It is the same for? 2, j and D 2, j- Normally, we look for the homolog of the point P ⁇ , j + l , belonging to the image in the plane 3, this homolog being located in the image in the plan 5.
• Di j is contained in a plane J ⁇ T. defined by on the one hand and source 2 on the other.
• D2, j is contained in a plane ⁇ 2 defined by D2, j and l at source 4.
• the support of the vector 55 sought is the line of intersection of the two planes ⁇ . ⁇ and 7T 2 .
• the two main branches CX and IVA coming from the common trunk AA, characterize the planes.
• the CX forms an arc defining a plane substantially orthogonal to the plane containing the IVA.
• the two starting segments in each plane correspond one to the CX the other to the IVA. They are broken down into elements on the right. We are interested in the first element on the right of each of the segments.
• the procedure for calculating the 3D vectors corresponding to each is in principle identical to that described above in the case of a single 3D vector.
• the new problem is, according to FIG. 5, that there is ambiguity as to the ownership of the segments. We then build the 4 3D vectors of which only two are solutions.
• the criterion for choosing the acceptable solution is based on the assumptions linked to the model. According to these hypotheses, one of the branches, the IVA in this case, has good continuity with the common core. In contrast, the tree structure of the vascular network means that the second branch, the CX in this case, is distant from a direction parallel to that of the common trunk. It is therefore possible to eliminate the couple of reconstructed 3D vector which would not additionally have a label behind it (for 1 * IVA), and on the other hand (for the CX).
• the monitoring of the first segment of the CX is identical to the monitoring carried out for the common core.
• the CX plan is re-estimated at each end of the CX segment. A re-estimation of this plan can be made after detection of a first connection point on the CX.
• This branching point can be the bifurcation corresponding to the first lateral branch or to a crossing with a vessel.
• the condition for launching the plan reestimation calculation is that the curvature observed on all the points of the CX exceeds a certain threshold.
• the analysis of the first bifurcation is identical to the case of initialization. We are looking for matching and labeling in relation to the known model. We will use the criteria evaluated on the standard anatomical model according to which the first bifurcation encountered on the CX corresponds to the birth of a branch lateral and in pursuit of the CX. The starting segment of the CX is in continuity with the finishing segment of this same CX and the starting segment of the lateral branch is behind the segments of the CX. We automatically determine which segment belongs to the CX and which segment belongs to the lateral artery.
• the information concerning the lateral branch is memorized for a later resumption as soon as one arrives at the end of the CX.
• the end of the CX is detected by identification of a point without successor in at least one of the planes of the image.
• the IVA branch is reconstructed in the same way (with possible reestimation of the IVA plan at each stage). Then the branches left waiting are also reconstructed, for example the lateral branch detected during the course of the CX.
• the implementation of the method of the invention requires the acquisition, if possible, of two images simultaneously. Different sources of errors exist such as. the calibration of the radiology system or the sampling of the images and the uncertainties of the segmentation drawn from the skeletonization. The fact of working from images of angles of view very different gives access to greater reconstruction accuracy. The speed of the procedure is due to the very structured description of the data and the strong participation of the symbolic model. The method is applicable to any other arboreal vascular structure, as soon as the corresponding anatomical 3D model is acquired and is integrated into the system.
• this rapid method can allow the study of the vascular network in movement from images acquired in two incidences and at different phases of cardiac movement.
• the reconstruction of the tree structure of the image takes the same order of time as the skeletonization: it is of the order of 3 seconds.
• an interactive generator of wire reconstruction is available as software.
• An example is the INTERACTIVE GENERATOR OF 3D VASCULAR STRUCTURES software available at the University of RENNES, Laboratory of Signals and Images in Medicine, Faculty of Sciences, Campus de Beaulieu, 35042 RENNES CEDEX.

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• 1988
  • 1988-09-13 FR FR8811917A patent/FR2636451A1/fr active Granted
• 1989
  • 1989-09-07 WO PCT/FR1989/000449 patent/WO1990003010A1/fr not_active Application Discontinuation
  • 1989-09-07 EP EP89910105A patent/EP0434720A1/de not_active Withdrawn
  • 1989-09-07 US US07/659,406 patent/US5175773A/en not_active Expired - Lifetime

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