IMAGING METHOD WITH IMPROVED IMAGE QUALITY

Abstract

A vessel image, which maps a vessel structure, and a device image, which maps a device, are created. A processor, depending on the device image and the vessel image, creates an overlaying image. At least one filter algorithm is applied to the device image, creating a filtered device image. The overlaying image is created by overlaying of the vessel image with the filtered device image.

Claims

1. An imaging method comprising: creating a vessel image, which maps a vessel structure of an object to be imaged, and also a device image, which maps a device arranged in the object by an imaging apparatus; and applying, by a processor, at least one filter algorithm to the device image, resulting in a filtered device image; and creating, by the processor, an overlaying image by overlaying of the vessel image with the filtered device image.

2. The imaging method as claimed in claim 1, characterized in that the at least one filter algorithm includes a local contrast enhancement.

3. The imaging method as claimed in claim 2, characterized in that the local contrast enhancement comprises creating, by the processor in the applying: an unsharpened input image based on an input image dependent on the device image, a contrast image by subtraction of the unsharpened input image from the input image, and an enhanced-contrast image by overlaying of the input image with the contrast image or with an image dependent on the contrast image.

4. The imaging method as claimed in claim 3, characterized in that the processor modifies the contrast image locally asymmetrically with regard to a local intensity threshold value and creates the enhanced-contrast image by overlaying of the input image with the modified contrast image.

5. The imaging method as claimed in claim 4, characterized in that the local intensity threshold value is determined by the processor as the average intensity value of a predetermined environment of a pixel of the input signal.

6. The imaging method as claimed in claim 4, characterized in that, for modification of the contrast image, an intensity value of a pixel of the contrast image is made smaller by a measure of diminution, when the intensity value of the pixel of the contrast image is less than the intensity threshold value; and/or for modification of the contrast image, the intensity value of the pixel of the contrast image is not made larger or is made larger by a smaller measure of increase compared with the measure of reduction, when the intensity value of the pixel of the contrast image is greater than the intensity threshold value.

7. The imaging method as claimed in claim 2, characterized in that by application of the contrast enhancement, intensity values below a local intensity threshold value are made smaller and/or intensity values above the local intensity threshold value are made larger; wherein the contrast enhancement acts asymmetrically with regard to the local intensity threshold value.

8. The imaging method as claimed in claim 7, characterized in that the contrast enhancement makes intensity values below the local intensity threshold value smaller by a measure of diminution and does not make intensity values above the local intensity threshold value larger or makes them larger by a smaller measure of enlargement by comparison with the measure of diminution.

9. The imaging method as claimed in claim 1, characterized in that the at least one filter algorithm contains a bilateral filter algorithm characterized by a spatial filter kernel and an intensity filter kernel.

10. The imaging method as claimed in claim 9, characterized in that, by application of the bilateral filter algorithm to an input image dependent on the device image, a filtered input image according to a specification in the form
D.sub.i=d.sub.i−W.sub.i*Σ.sub.j[d.sub.j*f(d.sub.j)*g(δ.sub.j)] is created, wherein d.sub.i designates an intensity value of a pixel i of the input image, D.sub.i an intensity value of a corresponding pixel i of the filtered input image, Σ.sub.j a sum of all pixels j of the input image within a predetermined environment of the pixel i, d.sub.j an intensity value of the respective pixel j, f the intensity filter kernel, δ.sub.j a spatial distance of the respective pixel j from the pixel i, g the spatial filter kernel and W.sub.i a normalization factor.

11. The imaging method as claimed in claim 10, characterized in that: for the spatial filter kernel, the following relationship applies:
g(δ.sub.j)˜exp[−δ.sub.j.sup.2/S.sub.R.sup.2], wherein S.sub.R designates a predetermined reach of the spatial filter kernel; and/or for the intensity filter kernel, one of the following relationships applies:
f(d.sub.j)˜exp[−(d.sub.j−S.sub.0).sup.2/S.sub.I.sup.2],
f(d.sub.j)˜H(d.sub.j−S.sub.0), or
f(d.sub.j)˜1/[1−exp(−[d.sub.j−S.sub.0]/Δ)], wherein S.sub.I designates a predetermined reach of the intensity filter kernel, S.sub.0 a predetermined intensity reference value, H the Heaviside function and Δ a predetermined width.

12. The imaging method as claimed in claim 9, characterized in that: based on the device image, a check in respect of contrast medium residues is carried out by the processor; and the bilateral filter algorithm is applied depending on the result of the check.

13. The imaging method as claimed in claim 1, characterized in that: without using a contrast medium, a first reference image is created by the imaging apparatus and, using a contrast medium, a contrast medium image is created, the contrast medium image representing the vessel structure); and the vessel image is created by the processor as the first subtraction image of the contrast medium image and of the first reference image.

14. The imaging method as claimed in claim 13, characterized in that: after the creation of the contrast medium image, a second reference image is created by the imaging apparatus and an examination image is created, the examination image showing the device arranged in the object; and the device image is created by the processor as the second subtraction image of the examination image and of the second reference image.

15. An imaging apparatus comprising: an imaging apparatus configured to create at least one sensor dataset, which relates to a vessel structure of an object to be imaged, and to create at least one further sensor dataset, which relates to a device arranged in the object; and a processor configured to create a vessel image based on the at least one sensor dataset, the vessel image representing the vessel structure, to create a device image based on the at least one further sensor dataset, the device image representing the device arranged in the object, to create a filtered device image by application of at least one filter algorithm to the device image and, to create an overlaying image by overlay of the vessel image with the filtered device image.

16. A non-transitory computer readable medium storing instructions that, when executed by an imaging apparatus, perform imaging, the instructions being for: creation of a vessel image, which maps a vessel structure of an object to be imaged, and also a device image, which maps a device arranged in the object by an imaging apparatus; and application of at least one filter algorithm to the device image, resulting in a filtered device image; and creation of an overlaying image by overlaying of the vessel image with the filtered device image.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In the figures:

[0069] FIG. 1 shows a schematic diagram of an example of an embodiment of an imaging apparatus according to the improved concept;

[0070] FIG. 2 shows a schematic flow diagram of an example of an embodiment of an imaging method according to the improved concept;

[0071] FIG. 3 shows a schematic diagram of the processing of intensity values in accordance with a further exemplary embodiment of an imaging method according to the improved concept;

[0072] FIG. 4 shows a schematic diagram of the processing of intensity values in accordance with a further exemplary embodiment of an imaging method according to the improved concept;

[0073] FIG. 5 shows a schematic diagram of an overlaying image and also a further overlaying image created in accordance with a further example of an embodiment of an imaging method according to the improved concept;

[0074] FIG. 6 shows a schematic timing waveform of a contrast medium concentration in accordance with further examples of embodiments of an imaging method according to the improved concept; and

[0075] FIG. 7 shows a filtered device image and an overlaying image in accordance with a further example of an embodiment of an imaging method according to the improved concept and also a further overlaying image.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0076] Shown schematically in FIG. 1 is an example of an embodiment of an imaging apparatus 1 according to the improved concept, which is embodied as an x-ray imaging apparatus for example. Shown in the example depicted in FIG. 1 is a construction of the x-ray imaging apparatus according to the principle of a C-arm device with a rotatable and movable C-arm 6, which can be turned and driven accordingly, in order to image an object 4 to be imaged from different directions. An imaging apparatus 1 according to the improved concept can however also be constructed in other ways. In particular, the improved concept is not basically restricted to x-ray-based imaging methods.

[0077] The imaging apparatus 1 of FIG. 1 thus includes an x-ray source 2 for example, which is configured to create x-ray radiation and to emit it in the direction of the object 4. Arranged on a side of the object 4 lying opposite the x-ray source 2 is a sensor 3 of the imaging apparatus 1, which for example contains a detector array of photodiodes, in order to be able to detect x-ray quanta penetrating through the object 4. The sensor 3 can then for example transfer corresponding detector signals to a processing unit 5 of the imaging apparatus 1 for further processing.

[0078] The imaging apparatus 1 can be configured for example for carrying out a roadmap method, in particular a roadmap method based on the principle of double subtraction.

[0079] The functioning of the imaging apparatus 1 will be explained in greater detail below with regard to different embodiments of an imaging method according to the improved concept, in particular with reference to FIGS. 2 to 7.

[0080] As an alternative or in addition, the imaging apparatus 1 can be configured for carrying out a rotation angiography method. In this case, the processing unit 5 can for example create a multitude of two-dimensional projections recorded from different angles and the processing unit 5 or a further processing unit (not shown) can compute a three-dimensional reconstruction from them.

[0081] Shown in FIG. 2 is an example of an embodiment of an imaging method according to the improved concept, which is embodied as a roadmap method according to the principle of double subtraction.

[0082] To this end, a timeline, which schematically represents different recording phases P1, P2, P3, P4 as a function of the time t, is shown in an upper area of FIG. 2.

[0083] In a first phase P1, a first reference image RB1 of a region of the object 4 is created, which shows a vessel structure 7 (see FIG. 5 and FIG. 7) and a corresponding tissue environment of the vessel structure 7. The first reference image RB1 can also be designated as the first mask or acquisition mask. In a second phase P2 following the first Phase P1, in particular immediately following it, a contrast medium image KB of the same region of the object 4 is recorded, that accordingly likewise shows the vessel structure 7 and the environment. For creation of the first reference image RB1 however no contrast medium is used. A contrast medium is introduced into the vessel structure for example in the course of the second phase P2, so that the contrast medium image KB maps the vessel structure 7 in a highlighted way. Depending on the contrast medium used and depending on the processing of the resulting images, the vessel structure 7 can be shown brighter or darker than the surrounding tissue. The administration of the contrast medium in this case is not to be seen as a part of the method according to the improved concept, however.

[0084] Shown again in FIG. 6 is the timeline with the phases P1, P2, P3, P4, wherein a contrast medium concentration 9 in the vessel structure 7 as a function of the time is shown schematically on the ordinate. After the second phase, in a third phase P3, a second reference image RB2 is recorded, as shown once again in FIG. 2. In this case, the third phase P3 as a rule does not follow on immediately from the second phase P2, so that, as indicated in FIG. 6, the contrast medium concentration 9 has already almost dropped to zero at the beginning of the third phase P3. It can occur however that during the third phase P3 significant residues of contrast medium are still present in the vessel structure 7, as shown schematically by the alternate contrast medium concentration 9′ as a function of the time t. Such contrast medium residues can have various causes. For example, anatomical or pathological reasons can be present in the object 4. It can also occur that the third phase P3, initiated manually by a user for example, was incorrectly initiated too early, so that the creation of the second reference image RB2 is already started before the contrast medium concentration 9′ has dropped to zero.

[0085] After the third phase P3, in a fourth phase P4, an examination image UB is created, which maps a device 8 (see FIG. 5 and FIG. 7) that was introduced into the object 4 after the creation of the second reference image RB2, in particular into the vessel structure 7. The introduction of the device 8 into the object 4 or the movement of the administration of the contrast medium in this case however is not to be seen as part of the method according to the improved concept. The examination image UB therefore shows both the vessel structure 7 and where necessary the environment as well as the device 8. Likewise, no contrast medium is used for creation of the examination image UB.

[0086] The device 8 as a rule involves an object that has a greater resistance to x-rays than the surrounding tissue. Depending on the processing of the output images, the device 8 can therefore in particular be shown darker than the surrounding tissue. The device 8 can in particular include a metal, for example platinum, stainless steel or gold. The device 8 can fulfill different functions. For example, the device 8 can be part of a vessel catheter, a guide wire, or a part thereof, a part of a vessel prosthesis or of a stent, a marker and so forth. The device 8 can however also contain a less x-ray-proof material by comparison with the environment, such as for example CO.sub.2, in particular dry ice.

[0087] The processing unit 5 combines the first reference image RB1 with the contrast medium image KB in order to obtain a vessel image VB. The combination of the first reference image RB1 with the contrast medium image KB can for example include a registration of the contrast medium image KB with the first reference image RB1. Above and beyond this, the combination includes a subtraction of the first reference image RB1 from the contrast medium image KB or vice versa or the corresponding registered images. In addition, the combination can include a further processing of the subtracted images. In other words, the vessel image VB can be expressed as VB=VP(KB−RB1), wherein VP represents any given vessel processing function.

[0088] Similarly, the processing unit 5 can combine the second reference image RB2 with the examination image UB in order to create a device image DB. In this case, the second reference image RB2 is in particular subtracted from the examination image UB or vice versa or correspondingly registered images are subtracted from one another. Moreover, the result of the subtraction can likewise be processed. Accordingly, the device image DB can be expressed as DB=DP(UB−RB2), wherein DP designates any given device processing function.

[0089] Usually, the contrast medium is selected in the second phase P2 and the images are also processed in such a way that the device image DB shows the device 8 darker than the device environment and in particular darker than the vessel structure 7 (see for example upper image in FIG. 7). This is however not necessarily the case.

[0090] The processing unit 5 applies at least one filter algorithm to the device image DB in order to obtain as a result a filtered device image DB′. The processing unit 5 then overlays the filtered device image DB′ with the vessel image VB in order to obtain an overlaying image RMB, which can also be designated as a roadmap image. The overlaying image RMB can thus also be expressed as RMB=MIX(VB,DB′), wherein MIX represents an overlaying function, in the simplest case an addition.

[0091] The device image DB′ in this case is given by a multitude of pixels, which each correspond to an intensity value. The spatial position of each pixel can be specified by corresponding two-dimensional spatial coordinates. This also applies in a similar way to vessel image VB. While the reference images RB1, RB2 and the contrast medium image KB can be static images, i.e., in particular not be updated over the course of time, the examination image UB is generally updated during consecutive frames, which correspond to repetitions of the fourth phase P4. Accordingly, the examination image UB is also occasionally referred to as a live image. As a consequence, the filtered device image DB′ as intensity value can be understood as a function of the two-dimensional spatial coordinates and the time, while the vessel image VB as intensity value can be understood as a function of the two-dimensional spatial coordinates, but not of the time.

[0092] The at least one filter algorithm can for example include an asymmetric contrast enhancement algorithm. The way in which the asymmetric contrast enhancement algorithm functions is shown by way of example in FIGS. 3 to 5.

[0093] Shown in FIG. 3 is the creation of a contrast image based on an input image. The input image in this case can correspond to the device image DB or to an image dependent thereon. Shown in FIG. 3 is an input signal E, which as a schematic spatial waveform corresponds to the intensity values in a region of the input image. The input signal E has a more or less steep step, which corresponds to the transition from a less x-ray-proof material to a more x-ray-proof material, for example a transition from tissue to the device 8. The processing unit 5 creates a spatially unsharpened signal E′, which can also be designated as a blurred signal, for example by convolution of the input signal E or of the entire input image with a Gaussian filter or a box kernel filter. As an alternative a multiscalar filter approach can also be used.

[0094] The unsharpened input signal E′ is then for example subtracted from the input signal E by the processing unit 5 in order to create a contrast signal KS. As an alternative, the process can be understood in such a way that an unsharpened input image is subtracted from the input image in order to create a contrast image.

[0095] The contrast signal KS or the contrast image is now modified asymmetrically by the processing unit, as is shown in FIG. 4. As a result, a modified contrast signal KS′ or a corresponding modified contrast image is obtained.

[0096] Since typically more x-ray-proof materials are used as devices in x-ray imagings, for example guide wires, stents, platinum markers, iodine and so forth, these are contained in the input image with a negative or dark contrast by comparison with the environment. The contrast signal KS can thus be processed by the modification in such a way that positive, i.e., bright values are weakened in the contrast signal KS and negative, i.e., dark, values in the contrast signal KS are intensified. This can be achieved for example by a parameterizable look-up table or another predetermined function, as is depicted for example to the far right in FIG. 4.

[0097] The modified contrast signal KS′ is then overlaid with the input image E, for example the two are summed. Accordingly, in the input image dark portions are locally intensified by the application of the asymmetric contrast enhancement algorithm, i.e., their brightness is further reduced, while bright portions are not locally intensified or are intensified less than the dark parts.

[0098] In alternative embodiments, the brighter values can also be amplified in the contrast signal KS and the darker values suppressed. This can be advantageous in order to delimit less dense materials, such as for example CO.sub.2, more strongly from the environment.

[0099] In FIG. 5, an example of a resulting overlaying image RMB is shown on the right in FIG. 5. Shown on the left in FIG. 5 is a further overlaying image RMB′, in which the asymmetric contrast enhancement algorithm has not been applied. By comparison, the tool 8 in the overlaying image RMB, in which the local asymmetric contrast enhancement algorithm was used, can be seen more clearly. This is indicated by the fact that the tool 8 on the right in FIG. 5 is depicted as a solid line and on the left in FIG. 5 as a dashed line.

[0100] The particular effect of the asymmetric local contrast enhancement algorithm, in particular by comparison with conventional local or global contrast enhancement algorithms, lies in its fundamental effect on human perception. The human perception of adjacent image regions of different brightness is deceived by the asymmetric increase of the contrast in such a way that the average difference in brightness on the side of the image region border on which the contrast is asymmetrically increased appears greater than it actually is. In other words, the darker region appears to be darkened even more, and this not only at the border but over an entire image region. This effect is utilized to highlight relevant regions in the filtered images even more strongly.

[0101] Optionally, the more evident highlighting of the device 8 can be intensified even further if the modified contrast signal KS′ in different embodiments is weighted with a measure of the local gradient strength. The local gradient strength can be computed in this case for example via a Sobel operator.

[0102] As an alternative or in addition to the asymmetric contrast enhancement algorithm, the at least one filter algorithm can include a bilateral filter algorithm. The effect of the bilateral filter algorithm is shown by way of example in FIG. 7.

[0103] The use of the bilateral filter algorithm can be advantageous in particular, when, as explained with regard to FIG. 6, the contrast medium concentration 9′ at the start of the third phase P3 has not yet dropped completely, so that artifacts or influences of the contrast medium are also undesirably present in the second reference image RB2. This leads for example to bright areas being present in the device image DB, which influence the recognizability of the vessel structure 7 and/or of the device 8 or the position of specific parts of the device 8 in the vessel structure 7. This can be seen for example in the upper image in FIG. 7, in which a contrast medium residue 10 is visible as a bright speck. Optionally the contrast medium residues can be automatically detected in the device image DB in order to trigger the bilateral filter algorithm, thus, to cause it to be used. The bilateral filter algorithm in this case is comparable to a DDO filter embodied with a specific sensitivity for larger white regions. This can be achieved for example by a filtering in the form given by equation (1) and for example equations (2) to (5).

[0104] The intensity filter kernel f can also be understood in this case as a weighting function of the signal difference. The weighting factor W.sub.i can be used for example to ensure a rescaling of the sum to a constant value, for example 1.

[0105] This enables the adverse effect on image quality caused by the contrast medium residues to be completely or partly compensated for automatically. Shown on the right at the bottom in FIG. 7 is a corresponding resulting overlaying image RMB. Shown on the left at the bottom in FIG. 7 is a further overlaying image RMB′, for the creation of which the bilateral filter algorithm has not been applied. As can be seen by comparison, the disruption 10 by the contrast medium residue in overlaying image RMB, for which the bilateral filter has been used, is diminished.

[0106] With regard to the figures, it has been described in particular how, inter alia, the asymmetric contrast enhancement algorithm can be used gainfully in the context of roadmap methods. The application of such an asymmetric contrast enhancement algorithm is however where necessary also advantageous in other imaging methods. For example, in particular in the use of C-arm devices, the option exists of recording rotation angiographies. Here an object is recorded from different angles with 2D projections and from these a 3D reconstruction is computed. The 2D data before the 3D reconstruction can be displayed as additional information. As well as the 3D reconstruction, a user can in addition or as an alternative orient themself to displaying the 2D projections. In particular, the display of devices, but also the display of vessel structures and the relationship of the device to the vessel structure, is very easily possible on the basis of the 2D projections.

[0107] To improve the display of the 2D projections, the asymmetric contrast enhancement filter described above can therefore be applied to the 2D projections and a corresponding result displayed. The 3D reconstruction in this case is in particular not influenced by the contrast enhancement filter, since for this the raw data from the two-dimensional recordings is required.

[0108] The different forms of application of the imaging method according to the improved concept can accordingly be transferred to an imaging method for rotation angiography.

[0109] It is intended that the foregoing description be regarded as illustrative rather than limiting, and that it be understood that all equivalents and/or combinations of embodiments are intended to be included in this description.

[0110] It is to be understood that the elements and features recited in the appended claims may be combined in different ways to produce new claims that likewise fall within the scope of the present invention. Thus, whereas the dependent claims appended below depend from only a single independent or dependent claim, it is to be understood that these dependent claims can, alternatively, be made to depend in the alternative from any preceding or following claim, whether independent or dependent, and that such new combinations are to be understood as forming a part of the present specification.