EP1861734A2 - Correction de non-linearites d'un systeme d'imagerie par une connaissance a priori en radiographie - Google Patents

Correction de non-linearites d'un systeme d'imagerie par une connaissance a priori en radiographie

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Publication number
EP1861734A2
EP1861734A2 EP06722577A EP06722577A EP1861734A2 EP 1861734 A2 EP1861734 A2 EP 1861734A2 EP 06722577 A EP06722577 A EP 06722577A EP 06722577 A EP06722577 A EP 06722577A EP 1861734 A2 EP1861734 A2 EP 1861734A2
Authority
EP
European Patent Office
Prior art keywords
reconstruction
correction
data
registration
specimen
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP06722577A
Other languages
German (de)
English (en)
Inventor
Stefan Kasperl
Ingo Bauscher
Matthias Franz
Stefan Schroepfer
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV
Original Assignee
Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV filed Critical Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV
Publication of EP1861734A2 publication Critical patent/EP1861734A2/fr
Withdrawn legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
    • G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
    • G01T1/29—Measurement performed on radiation beams, e.g. position or section of the beam; Measurement of spatial distribution of radiation
    • G01T1/2914—Measurement of spatial distribution of radiation
    • G01T1/2985—In depth localisation, e.g. using positron emitters; Tomographic imaging (longitudinal and transverse section imaging; apparatus for radiation diagnosis sequentially in different planes, steroscopic radiation diagnosis)

Definitions

  • the technical field of application of the invention is an industrial quality control of specimens with regard to quantitative statements, e.g. Surveying tasks.
  • CT computed tomography
  • various physical effects cause artifacts in the reconstructed tomograms, which reduce image quality.
  • CT reconstructions must be as free of artifacts as possible, cf. WO-A 2003/062856 (Fraunhofer).
  • Previous correction methods for example for beam hardening or scattered beam correction according to the above WO-A, considerably reduce the artifacts and the image quality thus achieved already enables meaningful dimensional stability analyzes.
  • these methods work iteratively and require the presence of the complete projection data.
  • An initial CT reconstruction initially provides artifact-laden 3D voxel data from the candidate.
  • Postprocessing image processing steps determine therefrom correction parameters for an improved second CT reconstruction. If necessary, it will go through another iteration.
  • the input data required for the correction methods can no longer be correctly determined from the test sample itself.
  • the object of the invention is to provide a method for the on-line correction of non-linearities of the imaging system during data acquisition in industrial computed tomography (CT).
  • CT computed tomography
  • Claim 1 or claim 10 alternatively claim 20 solve this task, with the aid of target data of the specimen.
  • the X-ray tubes used in CT emit polychromatic radiation.
  • the interaction of X-radiation when passing through matter is e.g. energy-dependent.
  • Real system characteristics therefore have a nonlinear course caused by effects such as beam hardening, stray radiation and detector nonlinearities. This causes artifacts in the reconstructed layers, such as stripes, blurred edges, barrel distortions and cupping effects, which degrade image quality and make it difficult or even prevent surveying tasks.
  • the method claimed here corrects nonlinearities of the imaging system in computed tomography already during the data acquisition (claim 1) or calculates parameters used at least before the end of the data acquisition (acquisition process or "data acquisition 11" ).
  • the advantage over the prior art is that the claimed method manages with a single CT reconstruction. Time-consuming iterative post-processing steps (IAR) are eliminated.
  • the correction methods can resort to better input data, resulting in better quality CT reconstructions.
  • the procedure uses the target data of the DUT and provides input data for CT reconstruction correction methods.
  • correction The correction parameters are determined during data acquisition. A correction is made; either here or later.
  • initialization is meant a rough screened registration of the device under test.
  • a rough screening is therefore a registry whose accuracy
  • singular pairs of points are searched, with a singular point is one that is measurably highlighted by its environment.
  • Singular points can be ones that have a maximum or a minimum, both two-dimensional and one-dimensional. Measurable is the singular point emphasizing its environment.
  • Other possibilities of singular points to be understood are those that are edge points of the object shadow or intersections of edges.
  • a point of a digital model of a test specimen (usually a CAD model) is projected on the detector.
  • the singular point of the model and the singular point of the figure form a pair of points called "feature point”.
  • feature points can also be extracted. This extraction of the singular points mentioned (in terms of the most unique feature points possible) is carried out with search algorithms from the measurements.
  • the search algorithms are adapted to the simulated projection of the digital model.
  • the position can be registered at the beginning of the CT scan. This registration is made from a projection. Possible algorithms that can be used to perform this registration are the SoftPOSIT process, cf. DeMenthon et al., SoftPOSIT, Simultaneous Pose and Correspondence Determination, International Journal of Computer Vision, 59 (3), 2004, pages 259 to 284. This ability to register the start position is relatively insensitive to mismatched feature points when using the well-known SoftPOSIT process (couples), if they do not get too much.
  • the procedure for intensity-based registrations is to determine the similarity between the reference image and the template image. Similarities are obtained with statistical methods, all pixel information serves as the basis, cf. Penney et al., "A Comparison of Similarity Measurements for Use in 2-D-3-D Medical Image Registration," IEEE Transactions on Medical Imaging, 17 (4), 1998, pages 586 to 595. Intensity-based 2D or 3D registration algorithms optimize, starting from a sufficiently good starting value, the similarity of reference and transformed template, cf. Pluim, IEEE Transactions on Medical Imaging, 22 (8), 2003, pages 986 to 1004.
  • the CT model as target data of the test object and the a-priori knowledge used thereby can be used on several projections in different positions of the test object. Each layer is characterized by a different angle of rotation which the specimen assumes relative to a rotation axis.
  • the registration as a 2D registration or 3D registration takes place alternatively and prompted by the application.
  • From a 2D fan-beam CT can be easily generalized to a 3D cone-beam CT.
  • the manner of the detector which is designed either as a line detector in a 2D-CT or as an area detector in a 3D-CT, is tracked in each case. In both cases, attenuated intensities are imaged on the detector by the object and by the radiation with the measuring radiation from the punctiform source, in each case as a projection in each case at a rotation angle of the test object.
  • the ideal case is a perfectly adjusted CT imaging system.
  • the position of the axis of rotation needs to be known, around which the test object is rotated in angular increments.
  • the registration on some projections makes it possible to use the CT on remaining projections in such a way that the position of the test object can be calculated for further projections.
  • a simulation in the form of a virtual CT can be done on the basis of the above knowledge. It provides the required input data for correction procedures during the reconstruction. A correction, at least a provision of correction parameters, takes place during the data acquisition.
  • radiated lengths are associated with arbitrary detector locations (pixels) for each assumed incremental rotational position of the test object. Each irradiated length and an associated measured intensity at the detector are combined into pairs of values. In order to determine the correction data during the data acquisition, data from all projections is not necessary.
  • Some projections are sufficient, for example a representative selection that covers an angle range of less than 360 °, in particular clearly below it.
  • the determination of the correction data can already be started when this representative selection of projections has been recorded. So at least part of the calculation of the correction parameters and the further recording process run in parallel.
  • the calculation of the correction parameters can be completed or completed essentially with the end of the acquisition process, that is also those projections that are not required for the representative selection.
  • the reconstruction can take place in the temporal range after / at the conclusion of the recording, thus allowing a lesser delay until the result is available.
  • FIG. 1 is a schematic side view of an imaging system with a symbolization of a radiographic image, caused by a radiation source Q, measuring beams q, a test object 10 and a detector 31.
  • FIG. 1a is a plan view of the arrangement of FIG. 1, showing the turntable with its axis 100; the two edge points of the test object form the boundary rays of the fan of the measuring beams q, representing an intensity distribution at the detector 31; Layer represents, but can also image in three-dimensional CT a volume of the specimen in the form of a planar x / y extent, wherein the detector 31 is formed correspondingly flat.
  • FIG. 2 illustrates the stepwise change of the angular position of the
  • Figure 3 illustrates not to scale, but symbolically and for clarity greatly increases the registration of a specimen 11, which is shown in solid in its actual position 11 and is shown in its inaccurate coarse determination position with 11 'by dashed lines.
  • the difference angle as a registration error is denoted by ⁇ .
  • the beam source Q is much farther away from the device under test than represented by the symbolic distance z1, and the device under test 11 is further away from the detector than symbolically shows the distance z2.
  • FIG. 3 a is the intensity profile or the associated intensity profile in the x-direction (from top to bottom in FIG. 3) with respect to a point-shaped radiation source having a fan-shaped beam as measuring beams.
  • Significant feature points whose position is designated by xa, xe and xf, and which belong to the edge points 11a, 11e and 11f of the test object 11 from FIG. 3, become apparent therefrom.
  • Figure 4 illustrates a flow chart for the implementation of
  • the side view of Figure 1 shows a test piece 10 in an L-shape (in side view) and a radiation source Q, which can emit X-rays or neutron beams. These rays are denoted by q, either cone-shaped or fan-shaped for a 2D or a 3D tomography.
  • the axis 100 is the axis of rotation of a plate 20, which drives a shaft 21 via a drive 22 with a gear, which is rotationally rigidly coupled to the turntable 20.
  • the rotation is characterized by ⁇ (omega), the shaft 21 is rotatably mounted on a base surface 25.
  • the axis 100 is perpendicular to the radiation axis emanating from the source Q, penetrates the device under test 10 and extends to a screen 31, which is used as a detector.
  • an intensity distribution I is shown which has a two-dimensional shape in the case of a three-dimensional tomography with a weakened intensity course corresponding to the shape, shape and the material of the test object 10, as l (x, y).
  • l (x, y) In the case of a layer transmission and a fan-shaped steel q, only one height direction is to be measured, for example, which has an intensity distribution l (y).
  • FIG. 1a (without the test object 10) with a turntable 20 which is rotatable about the axis 100.
  • the marginal rays of the radiation source Q are shown, which just touch the turntable, the central beam axis as well as the intensity distribution l (x) in the horizontal direction on the detector 31st
  • a driving beam q1 is shown, which would irradiate the test piece 10 when placed on the turntable 20 and is located within the two object shadow lines (boundary beams).
  • the turntable 20 is gradually rotated by the drive 22 by angular increments ⁇ , as Figure 2 shows clearly.
  • Each time interval T1, T2 or T3, an angle increment is valid for a transmission of radiation from the radiation source Q.
  • the angle increments are each symbolized as equalized as 20a, 20b and 20c.
  • Figure 3 illustrates symbolically, but not to scale, the specimen here in a similar shape and designated as specimen 11 in the coarse registration.
  • An orientation of the test piece 11 is roughly determined in a first, rapid registration.
  • the specimen is in the position shown in solid lines with corner points 11a, 11e and 11f and is irradiated by the radiation source Q with the example. Fan beam q.
  • the beam axis is perpendicular to the detector plane 31, in a surface detector, in a line detector is only a dependence of x.
  • the position of the test object 11 is determined precisely via feature point pairs.
  • Other possibilities which will be described separately, are statistical methods which also achieve a positioning of the test piece that is more accurate than the first rough (fast) registration which identifies the coarse layer 11 'of the test piece.
  • an angular error ⁇ shown between the actual ply 11 and the registered ply 11 '.
  • the angle error ⁇ is above one degree.
  • a translational error may also occur which lies in the range above 1 mm to 2 mm (or is dimensioned on the test object as at least 1% of its largest, in particular typical length).
  • the distances z1, z2 are not to scale, but to understand symbolically.
  • FIG. 3a An intensity distribution is shown in Figure 3a, which results in a fan-shaped beam q.
  • the course of the fan-shaped beams from top to bottom, starting from the corner point 11a to the corner point 11f (respective boundary beam) shows the profile of Figure 3a corresponding to the increasing or decreasing thickness of the radiation-absorbing specimen 11.
  • the curve of the intensity l (x ) shows some singular points at the positions xa, xe and xf which correspond to the vertices 11a, 11e and 11f of the position of the specimen.
  • the function profile of FIG. 3a shifts in the x direction by a small amount.
  • Each singular point forms a pair of points with a corresponding model point in a digital model, usually on a CAD model of the test object.
  • Several such pairs of points can each achieve a more accurate registration of the candidate in a projection.
  • the measurements of the singular points on the detector can be understood as an extraction, in any case they lead to the positioning of the specimen beyond the coarse registration more accurate.
  • statistical Methods are used, as explained above.
  • the similarity between the reference image and the template image plays a role here, cf. Penney in IEEE Transactions as mentioned above. These statistical methods are intensity-based and allow more accurate registration.
  • the position of the test piece 11 relative to the axis of rotation possibly can be calculated with translational error for at least one further projection.
  • Influence of the target data of the test specimen from the digital model allows the said improvement of the coarse positioning of the specimen.
  • at least one further projection of the test object can be calculated. This can be done relative to the axis of rotation and / or with a translational displacement.
  • a virtual CT can be made with the help of the acquired knowledge.
  • This is a simulated CT that provides input data for a reconstruction reconstruction procedure. This is only possible when the rough registration was made.
  • Use of the correction data resulting from the simulation can either begin during the data acquisition process or only after completion of this data acquisition in the temporal area of the end of the acquisition process.
  • the necessary correction data which has already been determined during the data acquisition, are available at the end of the acquisition process, so that a rapid correction can be carried out, which does not first have to calculate the parameters for the correction from the data acquisition, but rather for a reconstruction at the conclusion of the acquisition Data collection already available.
  • a large time saving of the calculation method is the result.
  • the correction and thus the reconstruction at the end of the acquisition process can provide improved CT reconstruction.
  • the first reconstruction can thus work with correction data, which are available immediately at the end of the recording process, after they were previously determined during the data acquisition.
  • a correction can also be made during the recording process (data acquisition), even if only partially with regard to some of the artifacts that occur during the recording.
  • a reconstruction of the surveyed test object is therefore carried out with corrected measurement data and is not only available faster in time, but also qualitatively better.
  • FIG. 4 illustrates a symbolic signal flow diagram or flowchart of a data acquisition 70 that can be viewed in time, starting with its beginning on the left and its end on the right.
  • A-priori knowledge 69 is first given and allows a registration 71 which is coarse and can be made more accurate by using, for example, feature point pairs, each of which is a measurable singular point (e) on the detector 31 and associated with each one singular point (s) in the digital model.
  • the successful registration then allows a simulation 72 which is a virtual CT. It is used to provide input data for CT reconstruction correction procedures.
  • correction data are determined which can lead to a correction of the data of the data acquisition 70, which is symbolized by the arrows 73a.
  • a correction 73b can take place only when the data acquisition has been completed and the projection or data recording is transferred to the calculations "correction of the measured data" 74. From this correction, which can take place very quickly in terms of time, there results a reconstruction 75, which likewise can proceed very fast in order to obtain the corrected volume 11 * which forms the reconstruction.
  • the right edge of the block "recording" 70 symbolizes both the area before the immediate end by influencing the correction parameters via the influences 73a on the data acquisition, and / or the area 74,73b, which is downstream and the correction and the reconstruction is concerned.
  • Industrial quality control is a preferred field of application, in particular in the field of automotive engineering and based on castings as test items 10,11. X-rays were mentioned as preferred measuring beams.
  • the projections required for the parameter determination are less than all the images provided for a rotation angle of 360 °. Which are recorded in the increments ⁇ .

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  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Molecular Biology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Analysing Materials By The Use Of Radiation (AREA)

Abstract

L'invention concerne un procédé de correction en ligne de non-linéarités du système d'imagerie pendant l'enregistrement de données en tomographie industrielle assistée par ordinateur (CT). Ladite invention concerne en particulier un procédé pour fournir des données de projection corrigées sous la forme d'une reconstruction CT améliorée, procédé selon lequel des rayons de mesure (q) sont émis d'une source de rayonnement (Q), lesdits rayons traversant la pièce à tester (10, 11) et leur intensité étant détectée sur un détecteur (31). Ledit procédé comprend une étape de première initialisation, lors de laquelle une première orientation de la pièce à tester (10) est déterminée de façon seulement approximative par un premier enregistrement rapide, une étape d'enregistrement lors de laquelle le positionnement de la pièce à tester (10) est déterminé de façon plus précise, en particulier par des paires de points caractéristiques, une étape de mouvement, lors de laquelle, après un enregistrement effectué avec succès sur au moins quelques projections, la position de la pièce à tester (10, 11) est calculée pour au moins une autre projection, une étape de simulation, lors de laquelle une tomographie virtuelle assistée par ordinateur est effectuée au moyen des résultats des étapes précédentes, laquelle tomographie fournit des données d'entrée pour un procédé de correction de la reconstruction CT, une étape de correction, lors de laquelle des paramètres sont déterminés à partir des données de correction pendant l'enregistrement de données (70) par le détecteur (31) puis une correction est effectuée (73a, 73b), ainsi qu'une étape de reconstruction, lors de laquelle des données de projection corrigées (11*) sont présentes à la fin du processus d'enregistrement de données (70) sous la forme d'une reconstruction CT améliorée (74, 75).
EP06722577A 2005-03-09 2006-03-09 Correction de non-linearites d'un systeme d'imagerie par une connaissance a priori en radiographie Withdrawn EP1861734A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102005011161 2005-03-09
PCT/DE2006/000420 WO2006094493A2 (fr) 2005-03-09 2006-03-09 Correction de non-linearites d'un systeme d'imagerie par une connaissance a priori en radiographie

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EP1861734A2 true EP1861734A2 (fr) 2007-12-05

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US (1) US20080212734A1 (fr)
EP (1) EP1861734A2 (fr)
CA (1) CA2600648A1 (fr)
DE (1) DE112006001354A5 (fr)
WO (1) WO2006094493A2 (fr)

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WO2010094774A2 (fr) 2009-02-20 2010-08-26 Werth Messtechnik Gmbh Procédé de mesure d'un objet
DE102009038505A1 (de) 2009-08-21 2011-03-03 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Konzept zum Ermitteln von Korrekturwerten für eine Reduktion von Artefakten bei einer Computertomographie eines zu untersuchenden Teilbereichs eines Prüfkörpers
AT509965B1 (de) * 2010-05-25 2012-06-15 Fh Ooe Forschungs & Entwicklungs Gmbh Verfahren zur bestimmung der optimalen lage eines objektes für eine 3d-ct-durchstrahlung
WO2013167616A2 (fr) 2012-05-07 2013-11-14 Werth Messtechnik Gmbh Procédé de tomographie assistée par ordinateur et dispositif de détermination de caractéristiques d'un objet à analyser
JP6131606B2 (ja) * 2013-01-21 2017-05-24 株式会社島津製作所 放射線撮影装置およびそれにおける画像処理方法
JP6631624B2 (ja) * 2015-04-24 2020-01-15 株式会社ニコン Ｘ線検査装置、ｘ線検査方法および構造物の製造方法
WO2018083930A1 (fr) * 2016-11-01 2018-05-11 株式会社島津製作所 Procédé d'étalonnage du grossissement d'imagerie pour dispositif de tomographie par rayonnement
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EP3798684A1 (fr) 2019-09-26 2021-03-31 Siemens Healthcare GmbH Correction de données dans l'imagerie par rayons x
CN112763517A (zh) * 2020-12-24 2021-05-07 中国原子能科学研究院 一种堆内辐照试验装置
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US20080212734A1 (en) 2008-09-04
DE112006001354A5 (de) 2008-03-06
WO2006094493A2 (fr) 2006-09-14
WO2006094493A8 (fr) 2010-08-05
WO2006094493A3 (fr) 2006-11-16
CA2600648A1 (fr) 2006-09-14

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