Preparation of medical image data of heart for deformation analysis

Abstract

The invention relates to preparation of medical image data of a heart for deformation analysis. A method for generating segmented, masked 4D image data (M-BD) of a heart is described. In the method, a 4D image record, preferably an arteriography record, of the heart of the patient (O) is provided with 4D image data (4D-BD) of the heart of the patient (O). Subsequently, first segmented 4D image data (SG1-BD), in which the heart wall of the ventricle is segmented, is generated on the basis of the 4D image data (4D-BD). Furthermore, second segmented 4D image data (SG2-BD) is generated on the basis of the first segmented 4D image data (SG1-BD), in which the epicardium (EPD) and the endocardium (EKD) of the ventricle are segmented. Finally, segmented, masked 4D image data (M-BD) is generated on the basis of the second segmented 4D image data (SG2-BD), in which the interior region of the ventricle is masked. In addition, a heart deformation analysis method is described. An image data generation device (50) is also described. Further, a medical imaging system is described.

Description

Technical Field

[0001] The invention relates to a method for generating segmented, masked 4D image data of a heart. The invention also relates to a method for analyzing heart deformation. The invention also relates to an image data generating device. The invention also relates to a computed tomography system. Background Art

[0002] Image data for visualizing the imaged examination object are generated by means of modern imaging methods. The image data or image data sets obtained in this way can also be used for further applications or analyses. The invention relates to further applications or analyses of the image data or image data sets obtained in this way.

[0003] Ischemic heart disease is one of the most common causes of death worldwide. The reduced blood supply caused by plaque deposits, which narrow the blood supplying blood vessels, leads to insufficient myocardial supply and limited function. In addition, the disease can be identified with the help of the blood volume pumped by the heart contraction. This assessment measures the cardiac ejection fraction and is part of the cardiac function analysis (CFA). The disadvantage of this method is that the disease can only be identified at a later stage with this method, because the method is based on indirect symptoms.

[0004] In contrast, Cardiac Strain Analysis (CSA) can identify smaller, locally restricted functional heart diseases even in apparently asymptomatic patients. In CSA, the heart movements that lead to thickening and thinning of the myocardium and thus to stress are measured. CSA is therefore suitable as a complementary method for identifying and localizing myocardial dysfunction.

[0005] Most commonly, non-invasive imaging modalities are used to detect heart deformations throughout the cardiac cycle. In clinical settings, heart deformation analysis is mainly performed with the aid of echocardiography. However, it is known that echocardiography-based heart deformation analysis reacts sensitively to the quality of the image recording. Therefore, this heart deformation analysis is error-prone and the results are not always reliable.

[0006] Another imaging method that is currently gaining popularity in the field of cardiac deformation analysis is cardiac magnetic resonance tomography (CMRT), which provides better image quality in view of sound suppression and tissue differentiation. This enables accurate CMRT-based CSA. However, CMRT is not widely used and is associated with time-consuming recording methods. CMRT is described in "Quantifizierung der Myokardverformung durch verformbare, registrierungsbasierte Analyse von Cine-MRT: Validierung mit getaggter CMR" by MMLamacie et al., European Radiology, Vol. 29, No. 7, pp. 3658-3668, 2019, doi: 10.1007 / s00330-019-06019-9.

[0007] In cardiac imaging, computed tomography (CT for short) is used in particular for coronary angiography, which is a method for showing the coronary vessels of the heart with the aid of contrast agents. Analysis of cardiac deformation with the aid of cardiac CT imaging is an area of ​​active research. Previous methods for cardiac deformation analysis with the aid of CT scans have achieved moderate success. They have mostly failed because the motion estimation algorithms cannot cope with the low tissue contrast in CT images. Therefore, CT cardiac deformation analysis has not yet been implemented in clinical practice.

[0008] Existing methods for cardiac deformation analysis with the aid of CT images are not adequate for clinical practice due to their inaccuracy. In some attempts at solutions, motion estimation methods were transferred from other modalities with moderate success to CT. This approach was described in “CT-abgeleitete” by F. Ammon et al. globaleBelastung: a direkter Vergleich mit der Speckle-Tracking-Echocardiography”, The International Journal of Cardio Imaging, Vol. 35, No. 9, pp. 1701-1707, 2019, doi:10.1007 / s10554-019-01596-8 and described in SJ Buss et al., “Quantitative Analysis of Left Ventricular Strain Using Cardiac Computed Tomography”, European Journal of Radiology, Vol. 83, No. 3, pp. e123-e130, 2014, doi:10.1016 / j.ejrad.2013.11.026.

[0009] Other methods of estimating myocardial motion based on models fitted to cardiac CT images at different points in time appear to be the most promising in the prior art, even though they may not be fully automated, are limited to the left ventricle, and have certain inaccuracies. The method is described in Z. Peled et al., "Automation of 4-dimensional regional myokardbelastungsbewertung mittels kardialer Computertomographie", The international Journal of Cardio Imaging, Vol. 36, No. 1, pp. 149-159, 2020, doi:10.1007 / s10554-019-01696-5 and in Y. Lamash et al., "Strain Analysis From 4-DCardiac CT Image Data", IEEE Transactions on Biomedical Engineering, Vol. 62, No. 2, pp. 511-521, 2015, doi:10.1109 / TBME.2014.2359244. Summary of the invention

[0010] Therefore, a method for adapting 4D-CT imaging of the heart is described in such a way that it is suitable for the task of cardiac deformation analysis.

[0011] This object is achieved by a method according to the invention for generating medical image data for analyzing a heart deformation, a method according to the invention for analyzing a heart deformation, an image data generation device according to the invention and a computed tomography system according to the invention.

[0012] In the method according to the invention for generating segmented, masked 4D image data of a heart, a 4D image data record of a patient's heart, preferably image data of an angiography record, particularly preferably a coronary angiography record, preferably as a CT image record, is provided, which has 3D or 4D image data of the patient's heart. Coronary angiography is an angiography of the coronary vessels of the heart and is therefore a special form of X-ray examination in which the coronary vessels of the heart are imaged. In angiography, contrast agents are usually used for imaging in order to make the vessels visible.

[0013] The method according to the invention for generating segmented, masked 4D image data of a heart and the method according to the invention for analyzing heart deformation described further below are designed in particular as computer-implemented methods.

[0014] In addition to coronary angiography, all other methods for recording 4D data should be included in which the muscle of the ventricle can be separated from the blood in the ventricle. Therefore, such a recording can also include a CT recording with high CT resolution without contrast agent. The recording can also include a recording using transesophageal 4D ultrasound. Alternatively, the 4D data recording can also include an MRT recording.

[0015] First segmented 4D image data are generated based on the 4D image data. Therein, the wall of the ventricle, preferably the left ventricle, is segmented. It is preferred to apply the method according to the invention to the left ventricle, because the state of the left ventricle has the greatest influence on the functioning of the body circulation. The right ventricle has a much thinner wall than the left ventricle. The function of the blood circulation affected by the right ventricle is usually not as clinically important as the function of the body circulation. However, at this point, the imaging of the right ventricle should also be explicitly included, although less prominently.

[0016] The method of cardiac chamber segmentation is described in "Four-chamber heart modeling and automatic segmentation for 3-D cardiac CT volumes using marginal space learning and steerable features" by Y. Zheng et al., IEEE transactions on medical imaging, Vol. 27, No. 11, pp. 1668-1681, 2008, doi: 10.1109 / TMI.2008.2004421. The above document is incorporated into the present patent application by reference.

[0017] 4D image data are understood to be time-resolved three-dimensional image data. The heart wall is formed by the so-called myocardium, i.e. myocardial tissue. The segmentation is performed so that the heart wall of the ventricle, preferably the left ventricle, is separated from the environment. As will be explained in detail later, preferably measures are taken to highlight the heart wall of the ventricle, preferably the left ventricle, relative to the image area surrounding the heart wall, so that the movement of the heart wall of the ventricle, especially the left ventricle, in particular the contraction or expansion or expansion of the heart wall can be tracked more accurately and clearly.

[0018] Based on the first segmented 4D image data, second segmented 4D image data are generated, wherein the epicardium and endocardium of the ventricle are segmented. The epicardium forms the outermost layer or epithelium of the heart. It is bonded to the myocardium. The endocardium forms the innermost layer of the heart, which covers the entire inner surface of the heart as a smooth cardiac endothelium. The second segmented 4D image data preferably includes a highlighted representation of the endocardium and the epicardium relative to the environment, so that the movement of the endocardium and the epicardium can be tracked more accurately and more clearly.

[0019] Segmented, masked 4D image data are generated based on the second segmented 4D image data, wherein the interior area of ​​the ventricle, preferably the left ventricle, is masked. The interior of the ventricle, in particular the left ventricle, includes the valve muscles of the heart valves, which can also move in the event of deformation of the associated ventricle. The movement of the valve muscles can be mistakenly interpreted as a movement of the heart wall of the associated ventricle, whereby the deformation analysis is erroneous.

[0020] Advantageously, the ventricle, preferably the left ventricle, and its contours become more clearly visible and more clearly separated from the surroundings, whereby more precise surface mapping can also be achieved. Furthermore, by increasing the contrast of the cardiac structures, improved motion tracking can be achieved.

[0021] Intensity-based registration between images better focuses on the actual region of interest for left ventricular myocardial loading analysis or cardiac deformation analysis by improving images of adjacent cardiac phases. The registration algorithm provides deformation regions from which intrinsic myocardial motion trajectories can be derived.

[0022] Intensity-based registration algorithms use smoothness constraints in order to create realistic motion estimates. Motion around the object being inspected can mislead the registration process and lead to inaccurate motion estimates of the object. This effect can be eliminated by fading misleading motion / objects in the image.

[0023] If a ventricle, preferably the left ventricle, contracts, an increase in density is achieved in the myocardium, which is indicated by an increase in brightness or contrast in this area. Due to better utilization of the bandwidth of possible brightness values, contraction can be detected more accurately and quantitatively. Conversely, expansion or dilation can also be identified by detecting a decrease in density. In addition, the distance between the epicardium and the endocardium also changes in the case of contraction and dilation, which can also be more easily identified due to the above-mentioned segmentation.

[0024] If necessary, distortions that occur during shrinkage can also be detected.

[0025] The method according to the invention for generating segmented, masked 4D image data of a heart can be used particularly advantageously in low-contrast imaging methods, on the basis of which a cardiac function analysis, in particular a cardiac deformation analysis, is to be carried out.

[0026] In the heart deformation analysis method according to the present invention, the method according to the present invention for generating segmented, masked 4D image data of the heart is first performed. Subsequently, the deformation area is determined based on the segmented, masked 4D image data generated in the method. For this purpose, the dynamic 4D image data is registered with the reference image.

[0027] The deformation region has a displacement vector from an image point of the object image to an image point of the reference image, which is caused in part by the elastic registration method.

[0028] Based on the determined deformation zone, an intrinsic myocardial motion trajectory is determined. Based on the determined intrinsic myocardial motion trajectory, a myocardial deformation analysis of a ventricle, preferably a left ventricle, is performed.

[0029] Due to the improved image data on which the heart deformation analysis method is based, the deformation of the heart can be analyzed more accurately, thereby improving the effectiveness and accuracy of the diagnosis of the health status of the patient's heart.

[0030] The image data generation device according to the invention has an input interface for receiving 4D image data of the patient's heart. Part of the image data generation device according to the invention is also a first segmentation unit for generating first segmented 4D image data based on the 4D image data, wherein the heart wall of the ventricle, preferably the left ventricle, is segmented.

[0031] The image data generation device according to the invention further comprises a second segmentation unit for generating second segmented 4D image data based on the first segmented 4D image data, wherein the epicardium and the endocardium of a ventricle, preferably the left ventricle, are segmented.

[0032] Furthermore, the image data generation device according to the invention comprises a mask unit for generating segmented, masked 4D image data based on the second segmented 4D image data, wherein the inner region of the ventricle, preferably the left ventricle, is masked. The image data generation device according to the invention has the advantages of the method according to the invention for generating segmented, masked 4D image data of a heart.

[0033] The medical imaging system according to the invention has a scanning unit for detecting measurement data, preferably projection data, of a patient and a control device for controlling the scanning unit and for generating image data based on the measurement data, preferably projection data. A part of the medical imaging system according to the invention is also an image data generation device according to the invention. The imaging system according to the invention has the advantages of the method according to the invention for generating segmented, masked 4D image data of a heart.

[0034] In particular, the features and advantages described in conjunction with the method according to the invention can also be designed as corresponding subunits of the medical imaging system according to the invention or of the computer program product according to the invention.

[0035] Rather, features and advantages described in conjunction with the medical imaging system according to the invention and the computer program product according to the invention may also be configured as corresponding method steps of the method according to the invention.

[0036] The medical imaging system preferably comprises a computed tomography system. The computed tomography system according to the invention has a scanning unit for detecting projection data of a patient and a control device for controlling the scanning unit and generating image data based on the projection data. A part of the computed tomography system according to the invention is also the image data generation device according to the invention. The computed tomography system according to the invention has the advantages of the method according to the invention for generating segmented, masked 4D image data of a heart.

[0037] Alternatively, the medical imaging system may also comprise an ultrasound imaging system with transesophageal 4D ultrasound.Alternatively, the 4D data recording may also comprise an MRT recording.

[0038] The computer program product according to the invention has a program code section with which all steps of the method according to the invention for generating image data based on projection data or a heart deformation analysis method are carried out when the program is executed in a control device of a medical imaging system, preferably a computed tomography system.

[0039] A predominantly software-based implementation has the advantage that a medical imaging system, preferably a computed tomography system or a control device thereof can be easily adapted by means of a software update in order to operate in the manner according to the invention.

[0040] Most of the above-mentioned components of the image data generation device according to the invention can be implemented completely or partially in the form of software modules in a processor of a corresponding computing system, for example in the form of a control device of a medical imaging system or a computer for controlling such a system. The implementation based mainly on software has the advantage that computing systems that have been used so far can also be converted in a simple manner by software updates so as to work in the manner according to the invention. In this regard, the object is also solved by a corresponding computer program product with a computer program, which can be directly loaded into a computing system and has program sections so that when the program is executed in the computing system, the steps of the method according to the invention for generating segmented, masked image data of the heart based on projection data or the steps of the heart deformation analysis method are executed. In addition to the computer program, such a computer program product may also include additional components, such as documentation and / or additional components, hardware components for using the software, such as hardware keys (dongles, etc.).

[0041] A computer-readable medium, such as a memory stick, a hard disk or another portable or fixedly mounted data carrier, can be used for transmission to a computing system or a control device and / or for storage on a computing system or a control device or wherein program sections of a computer program that are readable and executable by a computing system are stored on the computer-readable medium. For example, a computing system can have one or more cooperating microprocessors or the like for this purpose.

[0042] The following descriptions respectively contain particularly advantageous designs and improvements of the present invention. In addition, within the scope of the present invention, different embodiments and different features of the present invention can also be combined into new embodiments.

[0043] In a variant of the method for generating segmented, masked 4D image data of a heart according to the invention, the step of generating first segmented 4D image data comprises generating a mask of the wall of the left ventricle. The mask of the wall of the left ventricle marks the region that is relevant in the deformation analysis of the heart. If this region is better visible, the registration of the heart wall and its surface, in particular the epicardium and the endocardium, is facilitated. Thus, the registration of the heart wall and the surface based on such improved 4D image data can improve the accuracy and reliability of the deformation analysis of the left ventricle.

[0044] The mask of the wall of the left ventricle is preferably generated by applying a four-chamber segmentation algorithm to the 4D image data. Advantageously, the left ventricle can be segmented by a four-chamber segmentation algorithm of the remaining heart chambers.

[0045] In a variant of the method according to the invention for generating segmented, masked 4D image data of a heart, a high-contrast mask image is generated. In this case, voxels within the mask are determined whose grayscale values ​​or brightness values ​​deviate from the statistical mean by a predetermined value at most. The grayscale values ​​are mapped to high-contrast grayscale values ​​that are between the grayscale value 0 and the sum of the statistical mean and the predetermined value. Advantageously, the ratio of the brightness values ​​in the mask area is used to better make textures and contrasts clearer.

[0046] In a preferred variant of the method according to the invention for generating segmented, masked 4D image data of a heart, the predetermined value is two standard deviations from the mean. In a normal distribution, 95% of the distribution values ​​lie within a value range bounded by two standard deviations around the mean. The value range of possible brightness values ​​is advantageously determined such that the values ​​of the majority of the voxels in the mask region that are located within the mask lie within this value range.

[0047] In a particularly preferred embodiment of the method according to the invention for generating segmented, masked 4D image data of a heart, first segmented 4D image data are generated by weighted combination of a high-contrast mask image with the 4D image data. Advantageously, image data of the surroundings for the mask region are retained, and the contrast in the mask region is improved by adding 4D image data with a higher contrast in the mask region.

[0048] In a preferred variant of the method according to the invention for generating segmented, masked 4D image data of a heart, the weighted combination is performed with a predetermined percentage. The original image information is also advantageously contained in the segmented image data. In particular, the voxels outside the wall of the left ventricle are not changed.

[0049] In a preferred embodiment of the method for generating segmented, masked 4D image data of a heart according to the present invention, the percentage of the high-contrast mask image relative to the segmented 4D image data is between 20% and 40%, preferably about 30%. This means that for the segmented, masked 4D image data, the high-contrast mask image accounts for 20% to 40%, and the original image accounts for 60% to 80%. When the value is 30%, the weight of the high-contrast mask image is 30%, and the weight of the original 4D image data is 70%. Advantageously, a major part of the original image information is included in the segmented, masked 4D image data of the heart.

[0050] Preferably, the second segmented 4D image data is generated by highlighting the contrast of the epicardium and the endocardium of the left ventricle. Advantageously, the surface of the left ventricle is clearly highlighted, which facilitates the registration process and enables more accurate tracking of the motion of the surface of the left ventricle.

[0051] Preferably, when generating the second segmented 4D image data based on the first segmented 4D image data, the brightness value of the region segmented into the epicardium and the endocardium is changed to the average value plus twice the standard deviation from the average value. Advantageously, the surface of the left ventricle is made particularly well visible.

[0052] An interface gain factor is preferably determined so as to preserve texture information on the surface of the left ventricle. The interface gain factor is used to determine the percentage at which the voxel values ​​in the surface are set to the above-mentioned mean value plus twice the standard deviation from the mean value, and the percentage at which the original values ​​of the voxels in the surface are retained in the resulting image. The grayscale values ​​in the surface of the left ventricle may be multiplied by an additional factor greater than 1. Thereby, the endocardium and epicardium become well visible in the resulting image and intensity-based registration is facilitated.

[0053] Also preferably, the step of generating segmented, masked 4D image data comprises generating and flipping a mask for the intraventricular blood cavity including endocardial tissue. The mask for the intraventricular blood cavity is flipped so as to cover the entire blood-filled volume or blood cavity. Advantageously, the portion of the left ventricle to be imaged is segmented or separated relative to the intraventricular blood cavity. As already mentioned, the interior of the ventricle comprises the valve muscles of the heart valves, which also move in the event of ventricle deformation. The movement of the valve muscles may be mistakenly interpreted as a movement of the heart wall of the ventricle, whereby the deformation analysis is erroneous. Therefore, covering the inner area of ​​the ventricle facilitates the heart deformation analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The present invention will be explained in more detail below with reference to the accompanying drawings, using exemplary embodiments.

[0055] Figure 1A flow chart illustrating a method for generating segmented, masked 4D image data of a heart according to an embodiment of the present invention is shown,

[0056] Figure 2 FIG. 1 is a diagram illustrating an embodiment of the present invention. Figure 1 The image sequences of steps 1.I and 1.II of the method shown,

[0057] Figure 3 It also illustrates an embodiment according to the present invention. Figure 1 A schematic diagram of steps 1.I and 1.II of the method shown,

[0058] Figure 4 FIG. 1 is a diagram illustrating an embodiment of the present invention. Figure 1 Pictorial representation of steps 1.III and 1.IV of the method shown,

[0059] Figure 5 A schematic diagram showing an image data generating device according to an embodiment of the present invention is shown.

[0060] Figure 6 FIG. 4 is a flowchart of a heart deformation analysis method according to an embodiment of the present invention.

[0061] Figure 7 FIG. 4 is a schematic diagram showing a cardiac deformation analysis device according to an embodiment of the present invention.

[0062] Figure 8 A schematic diagram of a computed tomography system according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0063] Figure 1 A flow chart illustrating a method for generating segmented, masked 4D image data M-BD of a heart according to an embodiment of the present invention is shown.

[0064] In step 1.I, a coronary angiography recording of the heart of a patient O is provided, which recording comprises 4D image data 4D-BD of the heart of the patient O.

[0065] In step 1.II, first segmented 4D image data SG1-BD are generated based on the 4D image data 4D-BD, wherein the wall of the left ventricle of the heart of the patient O is segmented.

[0066] In step 1.III, second segmented 4D image data SG2-BD is generated based on the first segmented 4D image data SG1-BD, wherein the epicardium and the endocardium of the left ventricle are segmented.

[0067] Finally, in step 1.IV, segmented masked 4D image data M-BD are generated based on the second segmented 4D image data SG2-BD, wherein the inner region of the left ventricle is masked.

[0068] Figure 2 FIG. 1 is a diagram illustrating an embodiment of the present invention. Figure 1 Image sequences of steps 1.I and 1.II of the method are shown. Figure 2 The image sequence in comprises three sub-images, of which the sub-image shown on the left shows image data BD of a perspective view of the heart with the left ventricle LV. The middle sub-image shows a longitudinal axis view SA of the left ventricle, and the right sub-image shows a short axis view DA of the left ventricle. Partition lines are shown in the middle sub-image and in the right sub-image, which separate the cardiac muscles inwardly and outwardly. The outer partition line ASL shown in dashed lines separates the muscle tissue outwardly relative to the pericardium, and the inner partition line ISL shown in dotted lines separates the muscle tissue inwardly relative to the endocardium.

[0069] Figure 3 FIG. 1 is a diagram illustrating an embodiment of the present invention. Figure 1 Schematic diagram of steps 1.I and 1.II of the method shown. In step 1.I, the already described recording of the patient's heart takes place, wherein 4D image data 4D-BD of the heart of the patient O are obtained.

[0070] In step 1.II, except Figure 2 In addition to the segmentation of the left ventricle shown, a change in the image representation is also performed, wherein the contrast of the segmented region, ie the representation of the left ventricle, is increased.

[0071] In substep 1.IIa, a mask covering the wall of the left ventricle is generated. Subsequently, in substep 1.IIb, the brightness values ​​or grayscale values ​​of the voxels included in the mask are statistically analyzed. Here, the average value of the brightness values ​​or grayscale values ​​measured in Hounsfield units (HU) is calculated. In addition, in step 1.IIb, the standard deviation from the average value is calculated. In a normal distribution, 95% of the brightness values ​​of all voxels are within the value range represented by the mean value MW plus / minus the standard deviation STAW9 (as a boundary value) of twice the mean value MW.

[0072] In substep 1.IIc, the brightness values ​​of the voxels located within the mask are limited to this value range. In particular, the brightness values ​​outside the mentioned value range are set to the limit value, ie the already mentioned mean value MW plus / minus twice the standard deviation STAW.

[0073] In substep 1.IId, the brightness values ​​of the voxels located in the mask area are redistributed to an extended value interval EWI, which extends from the value 0 to a value formed by the sum of the mean value MW and twice the standard deviation STAW. In this way, 4D image data 4D-BDK with increased contrast are formed in the mask area.

[0074] In substep 1.IIe, the original 4D image data 4D-BD and the 4D image data 4D-BDK with increased contrast generated in substep 1.IId are combined or superimposed in a weighted manner using a weighting factor, wherein combined 4D image data 4D-BDKK with increased contrast is generated. The weighting factor specifies the percentage of the 4D image data 4D-BDK with increased contrast in the mask region and the percentage of the original 4D image data 4D-BD in the mask region to be combined with one another. Voxels of the original 4D image data 4D-BD outside the mask region remain unchanged.

[0075] Figure 4 FIG. 1 is a diagram illustrating an embodiment of the present invention. Figure 1 Image illustration of steps 1.III and 1.IV of the method shown. In step 1.III, the boundary area of ​​the ventricle is provided with a surface mask. The mask can be obtained by a morphological dilation operation. Here, the boundary area is obtained starting from the 4D image data 4D-BDK with increased contrast in the point inside the mask or in the mask area generated in step 1.II. Subsequently, the brightness value of the surface mask is increased to the maximum value of the value range generated above, that is, to twice the mean value plus the standard deviation STAW. In order to maintain the texture information in the surface mask, the original brightness values ​​of the pixels in the area of ​​the surface mask can also be combined with the increased brightness value in a weighted manner. In this way, the endocardium EKD and the epicardium EPD are illuminated. In step 1.IV, segmented, masked 4D image data M-BD are generated by shading the internal area of ​​the left ventricle. That is, the internal area of ​​the left ventricle that is brightly shown due to the contrast agent supply and the associated increased X-ray absorption is flipped in terms of its X-ray attenuation, that is, shown as dark.

[0076] Figure 5 FIG. 5 is a schematic diagram of an image data generating device 50 according to an embodiment of the present invention. The image data generating device 50 comprises an input interface 51, which is designed to receive 4D image data 4D-BD of a patient's heart.

[0077] Part of the image data generation device 50 is also a first segmentation unit 52 which is designed to generate first segmented 4D image data SG1 -BD based on the 4D image data 4D-BD, in which the wall of the left ventricle is segmented.

[0078] The image data generation device 50 further comprises a second segmentation unit 53 which is designed to generate second segmented 4D image data SG2 -BD based on the first segmented 4D image data SG1 -BD, wherein the epicardium and the endocardium of the left ventricle are segmented.

[0079] Furthermore, the image data generation device 50 has a masking unit 54 which is designed to generate segmented, masked 4D image data M-BD based on the second segmented 4D image data SG2 -BD, wherein the inner region of the left ventricle is masked.

[0080] Figure 6 A flow chart 600 illustrating a heart deformation analysis method according to an embodiment of the present invention is shown.

[0081] In step 6.I, the method according to the embodiment of the present invention is performed. Figures 1 to 4 A method for generating segmented, masked 4D image data M-BD of a heart is shown.

[0082] In step 6.II, the deformation region DF is determined based on the segmented, masked 4D image data M-BD generated in the method.

[0083] In step 6.III, the intrinsic myocardial motion trajectory T is determined based on the determined deformation zone.

[0084] In step 6.IV, a myocardial deformation analysis of the left ventricle is performed based on the determined intrinsic myocardial motion trajectory, and a result AE of the deformation analysis is output.

[0085] Figure 7 FIG. 7 is a schematic diagram of a cardiac deformation analysis device 70 according to an embodiment of the present invention.

[0086] The heart deformation analysis device 70 has an input interface 71 for receiving segmented, masked 4D image data M-BD of the heart. The segmented, masked 4D image data M-BD of the heart is as follows: Figure 7 The heart deformation analysis device 70 shown receives the deformation zone DF. A part of the heart deformation analysis device 70 is also a zone determination unit 72 which is designed to determine the deformation zone DF based on the segmented, masked 4D image data M-BD generated in the method.

[0087] A part of the heart deformation analysis device 70 is also a trajectory determination unit 73 which is designed to determine the intrinsic myocardial motion trajectory T based on the determined deformation zone DF.

[0088] Furthermore, a part of the heart deformation analysis device 70 is an analysis unit 74 which is designed to perform a deformation analysis of the left ventricle based on the ascertained intrinsic myocardial motion trajectory T and to output a result AE of the deformation analysis.

[0089] Figure 8 A schematic diagram of a computed tomography system 80 according to an embodiment of the present invention is shown.

[0090] The computed tomography system 80 has a control device 81 and a scanning unit 82 controlled by the control device 81. The control device 81 has a control unit 83 for generating control data SD and a control interface 84 for transmitting a control signal SS generated based on the control data SD to the scanning unit 82. A part of the control device 81 is also an input interface 85, which is designed to receive projection data PD from the scanning unit 82. The projection data PD is transmitted to a reconstruction unit 86, which is also a part of the control device 81 and is designed to reconstruct 4D image data 4D-BD of the heart of a patient (not shown) located in the scanning unit 82. A part of the control device 81 is also an input interface 85, which is designed to receive projection data PD from the scanning unit 82. The projection data PD is transmitted to a reconstruction unit 86, which is also a part of the control device 81 and is designed to reconstruct 4D image data 4D-BD of the heart of a patient (not shown) located in the scanning unit 82. Figure 5 The image data generating device 50 shown in FIG. 1 is designed to generate mask image data M-BD based on the 4D image data 4D-BD of the heart. The control device 81 also includes Figure 7 A heart deformation analysis device 70 is shown which is designed to perform a deformation analysis based on the generated segmented, masked 4D image data M-BD and to output analysis result data AE.

[0091] Finally, it is also pointed out again that the detailed methods and structures described above are embodiments, and the basic principles can also be changed by those skilled in the art in a wide range of fields without departing from the scope of the present invention, as long as the scope is preset by the claims. It should be pointed out here that the features of all embodiments or improvements disclosed in the drawings can be used in any combination.

[0092] For the sake of completeness, it should also be pointed out that the use of the indefinite article "a" does not exclude that the relevant feature may also be present multiple times. Likewise, the term "unit" does not exclude that it consists of a plurality of parts, which may also be spatially distributed. Regardless of the grammatical gender of the specific term, masculine and feminine persons are included.

Claims

1. A method for generating segmented, masked 4D image data (M-BD) of a heart, comprising the following steps: - providing a 4D image recording of a heart of a patient (O), said 4D image recording comprising 4D image data (4D-BD) of the heart of said patient (O), - generating first segmented 4D image data (SG1-BD) based on the 4D image data (4D-BD), wherein a wall of a ventricle of the heart is segmented, - generating second segmented 4D image data (SG2-BD) based on the first segmented 4D image data (SG1-BD), wherein the epicardium (EPD) and the endocardium (EKD) of the ventricle are segmented, - generating segmented, masked 4D image data (M-BD) based on the second segmented 4D image data (SG2-BD), wherein an inner region of the ventricle is masked.

2. The method according to claim 1, wherein: The cardiac chambers include the left ventricle (LV).

3. The method according to claim 1 or 2, wherein: The step of generating first segmented 4D image data (SG1-BD) comprises producing a mask of a wall of said ventricle (LV).

4. The method according to claim 3, wherein: The mask is generated by applying a four-chamber segmentation algorithm to the 4D image data (4D-BD).

5. The method according to claim 3 or 4, wherein: A high-contrast mask image is generated, wherein voxels within the mask are obtained, the grayscale values ​​of the voxels deviate from the statistical mean (MW) by a predetermined value at most, and the grayscale values ​​are mapped to high-contrast grayscale values, which are between the grayscale value 0 and the sum of the statistical mean (MW) and the predetermined value.

6. The method according to claim 5, wherein: The predetermined value is two standard deviations (STAW) from the mean (MW).

7. The method according to claim 5 or 6, wherein: The first segmented 4D image data (SG1-BD) is generated by weightedly combining the high-contrast mask image with the 4D image data (4D-BD).

8. The method according to claim 7, wherein: The weighted combination is performed at predetermined percentages.

9. The method according to claim 8, wherein: The percentage of the high-contrast mask image to the first segmented 4D image data (SGB1-BD) is between 20% and 40%, preferably about 30%.

10. A method according to any one of the preceding claims, wherein: - generating said second segmented 4D image data (SG2-BD) by highlighting the contrast of the epicardium (EPD) and the endocardium (EKD) of said ventricle (LV), and / or - The step of generating segmented, masked 4D image data (M-BD) comprises generating and flipping a mask within the ventricle.

11. A method for analyzing cardiac deformation, comprising the following steps: - performing a method according to any one of claims 1 to 10, - determining the deformation field (DF) based on the segmented, masked 4D image data (M-BD) generated in the method, - based on the obtained deformation zone (DF), the intrinsic myocardial motion trajectory (T) is obtained, - performing a myocardial deformation analysis of the left ventricle (LV) based on the determined intrinsic myocardial motion trajectory (TG).

12. An image data generating device (50), comprising: - an input interface (51) for receiving 4D image data (4D-BD) of the heart of a patient (O), - a first segmentation unit (52) for generating first segmented 4D image data (SG1-BD) based on the 4D image data (4D-BD), wherein a wall of a ventricle of the heart is segmented, - a second segmentation unit (53) for generating second segmented 4D image data (SG2-BD) based on the first segmented 4D image data (SG1-BD), wherein the epicardium (EPD) and the endocardium (EKD) of the ventricle are segmented, A masking unit (54) for generating segmented, masked 4D image data (M-BD) based on the second segmented 4D image data (SG2-BD), wherein an inner region of the ventricle is masked.

13. A medical imaging system, preferably a computed tomography system (80), comprising: - a scanning unit (82) for detecting measurement data (PD) of a patient (O), a control device (81) for controlling the scanning unit (82) and for generating 4D image data (4D-BD) based on the measurement data (PD), - The image data generating device (50) according to claim 12.

14. A computer program product comprising: Computer program, said computer program product being loadable directly into a memory of a control device (81) of a medical imaging system, A program code section, so that when the program is executed in the control device (81), all steps of the method according to any one of claims 1 to 11 are executed. 15 . A computer-readable medium on which a program segment executable by a computing unit is stored, so that when the program segment is executed by the computing unit, the steps of the method according to claim 1 are performed.

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