Automatic navigation echo placement detection

Abstract

The invention relates to a method of determining the position of a body landmark in a tomographic image slice of a subject, and a method of determining the positioning of a navigation echo in a three-dimensional preview image of a subject by successively applying a method of determining the position of a body landmark in at least three tomographic image slices of a subject in different viewing directions.

Description

Technical Field

[0001] This invention relates to a computer-implemented method for determining the position of body landmarks in a tomographic image slice of an object, a computer-implemented method for determining the location of navigation echoes, and a method for acquiring tomographic images of an object using a tomographic scanner. Background Technology

[0002] The paper "Automated Navigator Tracker Placement for MRI LiverScans" by Goto Takao et al., published on December 11, 2014, ISBN: 978-3-030-90436-4, describes a method for automatically placing a navigation tracker for MRI liver scans. The authors propose using a set-based classifier to detect pixels and correct landmarks on the upper edge of the liver, then identifying regions containing edge pixels in the up / down directions. After fitting to a quadratic function, the navigation tracker position is calculated from the peak position of the convex shape formed by the edge pixels.

[0003] Magnetic resonance imaging (MRI) is a widely used diagnostic tool that preferably requires navigation echoes during image acquisition to correct for motion artifacts. Navigation echoes are a method used in MRI to mitigate the effects of motion artifacts caused by patient movement during image acquisition. This technique involves capturing low-resolution images of a region of interest (ROI) before acquiring high-resolution images. The navigator sequence requires obtaining one or more slices of the ROI in a plane perpendicular to the main imaging sequence using parameters similar to or different from the main sequence. Navigator images are typically acquired rapidly over several seconds and are used to monitor ROI motion during high-resolution image acquisition. Throughout the high-resolution image acquisition, the navigator sequence is acquired continuously to track ROI motion. The motion data extracted from the navigator sequence can then be used to modify imaging parameters of the high-resolution sequence, such as gradients and RF pulse timing, to account for ROI motion. This parameter modification is performed in real time to ensure that the acquired images are free of motion-related artifacts. Navigation echoes are particularly valuable when imaging the chest and abdominal regions, where respiratory motion significantly affects image quality. Motion caused by other factors, such as patient movement and cardiac motion, can also be considered. Ultimately, navigation echo technology enhances image quality and reduces the need for repeated scans, thus saving time and reducing the overall cost of the MRI procedure. A simple and commonly used version of navigation echo can be to graphically place a navigator pencil beam, approximately 30×30×100mm in size, on a dome of the liver using reconnaissance images.

[0004] However, manually placing the navigation echo on reconnaissance images can be a complex task. Automated detection of the navigation echo can improve efficiency and reduce the expertise required for its placement in MRI image acquisition, thereby facilitating the diagnosis and treatment of various medical conditions.

[0005] Therefore, the inventors of this invention have found that an improved method for determining the positioning of navigation echoes would be advantageous, the method ensuring that the navigation echoes are placed in the optimal position, thereby producing better image quality. Summary of the Invention

[0006] The purpose of this invention is to provide an improved method for determining the location of navigation echoes, which provides reliable and accurate positioning.

[0007] The object of the invention is achieved by the subject matter of the independent claims, wherein further embodiments are incorporated in the dependent claims.

[0008] The described embodiments similarly relate to computer-implemented methods for determining the location of body landmarks in a tomographic image slice of an object, computer-implemented methods for determining the location of navigation echoes, and methods for acquiring tomographic images of an object using a tomographic scanner. The further described embodiments can be combined in any possible manner. Synergistic effects can arise from different combinations of embodiments, although they may not be described in detail.

[0009] According to one aspect of the present invention, a computer-implemented method for determining the location of a navigation echo is provided. The method includes:

[0010] Receive a three-dimensional preview image of an object acquired by a tomographic scanner, the preview image including the region of interest of the object;

[0011] A first tomographic image slice of the three-dimensional preview image is determined, wherein the first tomographic image slice is a central slice relative to the region of interest of the object in a preferred coronal view of the object;

[0012] Segmentation is performed on the first tomographic image slice, thereby dividing the first tomographic image slice into at least two body regions;

[0013] An edge detection algorithm is applied to the segmented first tomographic image slice to determine the first external shape of at least one of the at least two body regions;

[0014] The position of the center point of the first external shape of at least one of the at least two body regions is determined as the first position of the body landmark in the first tomographic image slice;

[0015] A second tomographic image slice of the three-dimensional preview image is determined. The second tomographic image slice is an image slice of the object relative to the region of interest of the object in a preferred sagittal view of the object. The second tomographic image slice is perpendicular to the first tomographic image slice and includes the first position of the determined body landmark.

[0016] Segmentation is performed on the second tomographic image slice, thereby dividing the second tomographic image slice into at least two body regions;

[0017] The edge detection algorithm is applied to the segmented second tomographic image slice to determine the second external shape of at least one of the at least two body regions;

[0018] The position of the center point of the second external shape of at least one of the at least two body regions is determined as the second position of the body landmark in the second tomographic image slice;

[0019] A third tomographic image slice of the three-dimensional preview image is determined, the third tomographic image slice being an image slice relative to the region of interest of the object in a preferred coronal view of the object, the third tomographic image slice being perpendicular to the second tomographic image slice and parallel to the first tomographic image slice, and including the second position of the determined body landmark;

[0020] Segmentation is performed on the third tomographic image slice, thereby dividing the third tomographic image slice into at least two body regions;

[0021] The edge detection algorithm is applied to the segmented third tomographic image slice to determine the third external shape of at least one of the at least two body regions;

[0022] The position of the center point of the third external shape of at least one of the at least two body regions is determined as the third position of the body landmark in the second tomographic image slice; and

[0023] The positioning of the navigation echo is provided based on the second position and the third position of the body landmark, as the output of the method.

[0024] The use of navigation echoes has proven crucial for monitoring respiration and defining the location of the heart. This, in turn, helps enhance imaging of the coronary arteries and other cardiac regions. To locate the navigation tracker, it may be necessary to understand, for example, the shape of the liver dome. To achieve this, a three-step image processing method has been proposed, which utilizes sequential application across different image slices in different viewing directions. Sequences of coronal, sagittal, and coronal views are preferred for many applications. However, other combinations of first and third parallel tomographic image slices perpendicular to the second imaging slice are also possible.

[0025] After determining the first tomographic image slice in the coronal view (which may be a central slice of the region of interest), the position of a body landmark (e.g., the dome of the liver) is determined within this slice in the coronal view, and the x-coordinate of the determined position is used to select the correct image slice in the sagittal view, which in turn is used to determine the position of the body landmark in the sagittal view. The corresponding coordinates of the determined body landmark in the sagittal view are again used to determine the correct final image slice in the coronal view. With this correct coronal image slice available, the final position of the body landmark can be determined, thereby determining the localization of the navigation echo.

[0026] Performing the "navigator placement process" as described above three times in the preferred coronal view, sagittal view, and re-coronal view is advantageous for finding the correct position in all three dimensions to determine the correct positioning of the navigator. This provides improved robustness for the navigator's positioning.

[0027] Therefore, according to this method, automatic navigation echo detection and placement are possible. Furthermore, in cardiac imaging, automatic navigation echo placement detection can be used to detect the navigation echo and place it in the optimal position for cardiac gating, which can be crucial for acquiring high-quality cardiac images. Navigator placement can be challenging, especially in patients with irregular breathing patterns. Automatic navigation echo placement detection can help overcome this. Additionally, scan time can be reduced, as automatic navigation echo placement detection can be performed in just a few seconds.

[0028] In an embodiment of the present invention, the positioning of the navigation echo in the front-back direction of the object is determined based on the second position of the body landmark, and the positioning of the navigation echo in the left-right direction and the up-down direction is determined based on the third position of the body landmark.

[0029] In embodiments of the present invention, the center slice is determined to be located in the middle of the range of the 3D preview image, the middle of the region of interest of the object, and / or the middle of the object.

[0030] The navigator placement process method, performed three times as described above, includes determining the position of body landmarks in a tomographic image slice of the object. The method includes the steps of: receiving a tomographic image slice of the object in a predefined view of the object, the tomographic image slice including the object's region of interest; performing segmentation on the tomographic image slice, preferably based on a threshold, thereby segmenting the tomographic image slice into at least two body regions; and applying an edge detection algorithm to the segmented tomographic image slice to determine the external shape of at least one of the at least two body regions. The method further includes the steps of: determining the position of the center point of the external shape of the at least one of the at least two body regions; and providing the position of the center point of the external shape as the position of the body landmark in the tomographic image slice as the output of the method. The external shape may also be referred to as an edge shape, contour, or curve.

[0031] Therefore, according to this method, the location of body landmarks in a tomographic image slice of an object can be determined. The body landmark can be the highest point of the liver dome, or at least the highest point of the liver dome included in a corresponding image slice in a given view of the image slice. Therefore, a threshold-based segmentation algorithm is preferably applied to segment, for example, the lungs and / or the liver, and an edge detection algorithm can be applied to the segmented tomographic image slice to determine the external shape of at least one body region in the lungs and liver. Next, a custom filter can be used to locate the lower edge of the lungs, which corresponds to the liver dome. Therefore, when determining the contour of the liver dome in the image slice, the highest vertex of the contour can be determined, which can correspond to the liver dome, provided that the liver dome is included in the corresponding image slice. Subsequently, a navigator beam can be placed on the median of the liver dome curve as the desired body landmark. However, it should be noted that the proposed method may only work if a correct image slice that already contains the liver dome is selected. Therefore, a novel three-stage image processing-based method is proposed for automatically locating the liver dome in three dimensions in MRI images and placing a navigation tracker on top of it, which will be described in more detail below.

[0032] In an embodiment of the present invention, the step of applying an edge detection algorithm to the segmented first, second and / or third tomographic image slices includes the following sub-steps: applying an edge detection algorithm to the segmented tomographic image slices to determine the contour of at least one of at least two body regions; and applying at least one filter to the determined contour to determine the external shape of at least one of the at least two body regions.

[0033] In an embodiment of the present invention, the step of applying an edge detection algorithm to a segmented tomographic image slice further includes the following sub-steps: performing localization of the external shape of at least one of the determined at least two body regions relative to the region of interest of the object; and discarding portions of the external shape of at least one of the determined at least two body regions, as a result of performing localization, said portions are considered not to be portions of the region of interest of the object.

[0034] In an embodiment of the invention, the body landmark is the highest point of the dome of the liver in the segmented first, second and / or third tomographic image slices.

[0035] In embodiments of the invention, the region of interest includes at least a portion of the chest of the object, particularly the interface between the lungs and liver of the object.

[0036] In an embodiment of the invention, the segmentation separates the lung tissue from the liver tissue.

[0037] In an embodiment of the invention, the center point of the first, second and / or third outer shape of at least one of the at least two body regions is the highest point of the outer shape in the vertical direction of the object.

[0038] According to another aspect of the present invention, a method for acquiring tomographic images of an object using a tomographic scanner is provided. The method includes the following steps: acquiring a three-dimensional preview image of the object; determining the location of a navigation echo in the preview image according to any of the methods described in the foregoing embodiments; and acquiring a tomographic image of the object while correcting for motion of the object based on movement of the navigation echo location.

[0039] According to another aspect of the present invention, a data processing apparatus is provided, comprising a module for performing the steps of the method according to any of the foregoing embodiments.

[0040] According to another aspect of the present invention, a computer program including instructions is provided, which, when executed by a computer, cause the computer to perform the steps of the method according to any of the foregoing embodiments.

[0041] According to another aspect of the present invention, a computer-readable storage medium including instructions, which, when executed by a computer, cause the computer to perform the steps of the method according to any of the foregoing embodiments, are provided.

[0042] Therefore, the benefits provided by any of the above aspects also apply to all other aspects, and vice versa.

[0043] In summary, the present invention relates to a method for determining the location of a navigation echo in a three-dimensional preview image of an object by sequentially applying a method that determines the position of body landmarks in at least three tomographic image slices of an object in different viewing directions.

[0044] One advantage of embodiments of the present invention is that it can effectively automate the placement of the navigation echo in MRI scans. Another advantage is that automated navigation echo placement detection ensures the navigation echo is placed in the optimal position, resulting in better image quality, as navigation echo placement is crucial for accurately correcting motion-induced artifacts in MRI scans. Another advantage is that automated navigation echo placement ensures consistency between different operators, as manual placement can vary between operators, leading to inconsistencies in image quality. Yet another advantage is that automated navigation echo placement detection reduces the need for human intervention and expertise, and can be more cost-effective.

[0045] These advantages are not limiting, and other advantages may be envisioned in the context of this application.

[0046] The above aspects and embodiments will become apparent from and will be set forth with reference to the exemplary embodiments described below. Exemplary embodiments of the invention will now be described with reference to the following figures: Attached Figure Description

[0047] Figure 1 A block diagram illustrates a computer-implemented method for determining the location of body landmarks in a tomographic image slice of an object according to an embodiment of the present invention.

[0048] Figure 2 A block diagram of a computer-implemented method for determining the location of a navigation echo according to an embodiment of the present invention is shown.

[0049] Figure 3 A flowchart illustrating a method for determining the location of body landmarks in a tomographic image slice of an object according to an embodiment of the present invention is shown.

[0050] Figure 4 A flowchart of a method for determining the location of a navigation echo according to an embodiment of the present invention is shown.

[0051] List of reference numerals in the attached diagram:

[0052] 110 Tomographic image slice

[0053] 111 First tomographic image slice

[0054] 112 Second Fault Photographic Image Slice

[0055] 113 Third Fault Photographic Image Slice

[0056] 120 Body Landmark

[0057] 130 Areas of Interest

[0058] 140 Two body areas Detailed Implementation

[0059] about Figure 1 The diagram illustrates a block diagram of a computer-implemented method for determining the position of a body landmark 120 in a tomographic image slice 110 of an object according to an embodiment of the present invention. This method is also referred to as a navigator placement process. The method includes step S110 of receiving a tomographic image slice 110 of an object in a predefined view of the object, wherein the tomographic image slice includes a region of interest 130 of the object. The method further includes step S120 of performing threshold-based segmentation on the tomographic image slice 110 to segment the tomographic image slice into at least two body regions 140. The method further includes step S130 of applying an edge detection algorithm to the segmented tomographic image slice 110 to determine the external shape of at least one of the at least two body regions 140. The method further includes step S140 of determining the position of the center point of the external shape of at least one of the at least two body regions; and step S150 of providing the position of the center point of the external shape as the position of the body landmark 120 in the tomographic image slice 110 as the output of the method.

[0060] Figure 2 A block diagram of a computer-implemented method for determining the location of a navigation echo according to an embodiment of the present invention is shown. The method includes: step S210 of receiving a three-dimensional preview image of an object acquired by a tomographic scanner, the preview image including a region of interest 130 of the object; and step S220 of determining a first tomographic image slice 111 of the three-dimensional preview image, the first tomographic image slice 111 being a slice centered relative to the region of interest 130 of the object in a coronal view. The method further includes: according to the above description regarding... Figure 1 The navigator placement process includes step S230, which determines the first position of the body landmark 120 in the first tomographic image slice 111; and step S240, which determines a second tomographic image slice 112 of the three-dimensional preview image, the second tomographic image slice 112 being an image slice in the sagittal view of the object relative to the region of interest 130 of the object, the second tomographic image slice 112 being perpendicular to the first tomographic image slice 111 and containing the determined first position of the body landmark 120. The method also includes steps based on the above description regarding... Figure 1The navigator placement process includes step S250, which determines the second position of the body landmark 120 in the second tomographic image slice 112. The method further includes step S260, which determines a third tomographic image slice 113 of the three-dimensional preview image. The third tomographic image slice 113 is an image slice in the coronal view of the object relative to the region of interest 130 of the object. The third tomographic image slice 113 is perpendicular to the second tomographic image slice 112 and parallel to the first tomographic image slice 111, and contains the determined second position of the body landmark 120. The method also includes: according to the above description regarding... Figure 1 The navigator placement process includes step S270, which determines the third position of the body landmark 120 in the third tomographic image slice 113; and step S280, which provides the positioning of the navigation echo as the output of the method based on the second and third positions of the body landmark 120.

[0061] Figure 3 A flowchart illustrating a method for determining the position of body landmarks 120 in a tomographic image slice 110 of an object according to an embodiment of the present invention is shown. Figure 3 As illustrated in this exemplary diagram, a sagittal view of the object's chest is used as a tomographic image slice 110, which includes the object's lungs and liver as regions of interest 130. After applying step S120, which performs threshold-based segmentation to distinguish the lungs from the liver, the object's lungs and liver can be easily distinguished in the image slice as two body regions 140 to be detected, particularly the boundary region between these two body regions 140. After performing edge detection on the output of the threshold-based segmentation to capture the edge shape of the lungs in step S130, the boundary region between the lungs and liver, which are the two body regions 140, is clearly highlighted. Optionally, a custom-defined filter can be applied to the contour of the lungs to preserve only the dome shape of the liver, and further localization can be performed to avoid the filter detecting both the dome of the liver and the top of the lungs (which can typically have similar shapes). Thus, additional noise in the image can be eliminated. Furthermore, the processing steps applied to the corresponding tomographic image slice 110 include step S140, which determines the location of the center point of the contour of the boundary between the lungs and liver, and the coordinates of this center point are provided as body landmark 120 as output.

[0062] Figure 4A flowchart illustrating a method for determining the location of a navigation echo according to an embodiment of the present invention is shown. Therefore, the proposed method may require the following steps. For example, an MRI scanner can acquire three-dimensional intelligent reconnaissance images with good image quality. The reconnaissance scan can be performed with free breathing or breath-holding. A region of interest 130 can be determined, which may be the left half of the scan, typically including the liver dome in a coronal view.

[0063] To locate the liver dome as a body landmark within the region of interest using the navigation echo, the correct dome placement in the sagittal view must first be determined. Therefore, it may be necessary to find potential image slices to predict the liver dome in the sagittal view. For this purpose, several processing steps are performed on the central or intermediate slice of the coronal view. After the intermediate slice of the coronal view has been identified as the first tomographic image slice 111, these steps are as follows, also as described above.

[0064] The processing steps applied to the intermediate slice of the coronal view, which serves as the first tomographic image slice 111, include at least performing (threshold-based) segmentation to distinguish the lungs from the liver, and performing edge detection on the output of the (threshold-based) segmentation to capture the edge shape of the lungs. Optionally, a custom-defined filter can be applied to the contour of the lungs to preserve only the dome shape of the liver, and further localization can be performed to avoid the filter detecting both the dome of the liver and the top of the lungs (which can typically have similar shapes). This eliminates additional noise in the image. Furthermore, the processing steps applied to the intermediate slice of the coronal view may include picking the center of the pixels remaining in the final output of the shape of the boundary between the lungs and the liver.

[0065] After applying these steps to the intermediate slices in the coronal view, the x-coordinate value of the center or vertex of the determined contour found in the above process will be the slice number used to predict the liver dome in the sagittal view.

[0066] The potential image slice used to predict the liver dome in the sagittal view is now defined as a second tomographic image slice 112, and the above processing steps are applied to this image slice in the sagittal view. Specifically, (threshold-based) segmentation is performed to distinguish the lungs from the liver, edge detection is applied to the output of the threshold-based segmentation to capture the edge shape of the lungs, and the center of the pixel remaining in the final output of the shape of the boundary between the lungs and the liver is selected. This will result in the correct navigator placement in the sagittal view.

[0067] Now, the position of the navigation echo is correctly placed in the correct slice in the sagittal view. The correct x-coordinate values ​​of the points found in the sagittal view in the above steps are used to determine the correct image slice in the coronal view as the third tomographic image slice 113, and to perform the final detection of the position of the liver dome in this correct slice of the coronal view. Now that the correct slice of the coronal view has been determined, the above steps are applied to this coronal third tomographic image slice 113. In particular, (threshold-based) segmentation is performed to distinguish the lungs from the liver, edge detection is applied to the output of the threshold-based segmentation to capture the edge shape of the lungs, and the center of the pixel remaining in the final output of the shape of the boundary between the lungs and the liver is selected.

[0068] The steps described in this application, when viewed in the correct coronal view, will result in a final estimate of the body landmark 120 to be determined as the navigation echo placement.

[0069] Performing the "navigator placement process" described above three times—in coronal, sagittal, and again in coronal views—facilitates finding the correct position in all three dimensions to robustly determine the correct localization of the navigation echo. The proposed method was evaluated on 60 clinical MRI datasets and achieved 96.7% accuracy in detecting the correct placement of the navigation echo.

[0070] Although the invention has been described and illustrated in detail in the accompanying drawings and the foregoing description, such description is to be considered illustrative or exemplary rather than restrictive. The invention is not limited to the disclosed embodiments. Other variations to the disclosed embodiments will be understood and implemented by those skilled in the art in practicing the claimed invention upon studying the drawings, the disclosure, and the dependent claims.

[0071] In the claims, the word "comprising" does not exclude other elements or steps, and the quantifiers "a" or "an" do not exclude a plurality. The fact that certain measures are re-referenced only in mutually different dependent claims does not indicate that a combination of these measures cannot be used advantageously. Any reference numerals in the claims should not be construed as limiting the scope.

Claims

1. A computer-implemented method for determining the location of a navigation echo, the method comprising the following steps: Receive (S210) a three-dimensional preview image of an object acquired by a tomographic scanner, the preview image including the region of interest (130) of the object. Determine (S220) the first tomographic image slice (111) of the three-dimensional preview image, wherein the first tomographic image slice (111) is the center slice of the object relative to the region of interest (130) of the object in the preferred coronal view of the object; Segmentation (S120) is performed on the first tomographic image slice (111) to divide the first tomographic image slice into at least two body regions (140). An edge detection algorithm (S130) is applied to the segmented first tomographic image slice (111) to determine the first external shape of at least one of the at least two body regions (140); The position of the center point of the first external shape of at least one of the at least two body regions is determined (S140) as the first position of the body landmark (120) in the first tomographic image slice; Determine (S240) a second tomographic image slice (112) of the three-dimensional preview image, the second tomographic image slice (112) being an image slice relative to the region of interest (130) of the object in a preferred sagittal view of the object, the second tomographic image slice (112) being perpendicular to the first tomographic image slice (111) and containing the first position of the determined body landmark (120); Segmentation (S120) is performed on the second tomographic image slice (112) to divide the second tomographic image slice into at least two body regions (140). The edge detection algorithm described in (S130) is applied to the segmented second tomographic image slice (112) to determine the second external shape of at least one of the at least two body regions (140); The position of the center point of the second external shape of at least one of the at least two body regions is determined (S140) as the second position of the body landmark (120) in the second tomographic image slice; (S260) Determine (S260) a third tomographic image slice (113) of the three-dimensional preview image, the third tomographic image slice (113) being an image slice relative to the region of interest (130) of the object in a preferred coronal view of the object, the third tomographic image slice (113) being perpendicular to the second tomographic image slice (112) and parallel to the first tomographic image slice (111) and containing the second position of the determined body landmark (120); Segmentation (S120) is performed on the third tomographic image slice (113) to divide the third tomographic image slice into at least two body regions (140). The edge detection algorithm described in (S130) is applied to the segmented third tomographic image slice (113) to determine the third external shape of at least one of the at least two body regions (140); The position of the center point of the third external shape of at least one of the at least two body regions is determined (S140) as the third position of the body landmark (120) in the third tomographic image slice; and The positioning of the navigation echo is provided (S280) based on the second position and the third position of the body landmark (120) as the output of the method.

2. The method according to claim 1, wherein, The step of applying the edge detection algorithm to the segmented first, second, and / or third tomographic image slices (111, 112, 113) includes the following sub-steps: The edge detection algorithm is applied to the segmented tomographic image slices (111, 112, 113) to determine the contour of at least one of the at least two body regions (140); and At least one filter is applied to the determined contour to determine the external shape of at least one of the at least two body regions (140).

3. The method according to claim 2, wherein, The step of applying the edge detection algorithm to the segmented tomographic image slices (111, 112, 113) further includes the following sub-steps: Perform positioning of the external shape of at least one of the at least two body regions (140) relative to the region of interest (130) of the object; as well as Discard portions of the external shape of at least one of the at least two body regions (140) as a result of the positioning performed, such portions are considered not to be part of the region of interest (130) of the object.

4. The method according to any one of claims 1-3, wherein, The body landmark (120) is the highest point of the dome of the liver in the segmented first, second and / or third tomographic image slices (111, 112, 113).

5. The method according to any one of claims 1-3, wherein, The region of interest includes at least a portion of the object's chest.

6. The method according to any one of claims 1-3, wherein, The segmentation is based on a threshold.

7. The method according to any one of claims 1-3, wherein, The segmentation distinguishes lung tissue from liver tissue.

8. The method according to any one of claims 1-3, wherein, The center point of the first outer shape, the second outer shape, and / or the third outer shape of at least one of the at least two body regions (140) is the highest point of the outer shape in the vertical direction of the object.

9. The method according to any one of claims 1-3, wherein, The navigation echo is positioned in the front-back direction of the object based on the second position of the body landmark (120), and the navigation echo is positioned in the left-right direction and the up-down direction based on the third position of the body landmark (120).

10. The method according to any one of claims 1-3, wherein, The central slice is determined to be located in the middle of the range of the 3D preview image, the middle of the region of interest (130) of the object, or the middle of the object.

11. The method according to claim 5, wherein, The region of interest includes the interface between the lungs and liver of the object.

12. A method for acquiring tomographic images of an object using a tomographic scanner, the method comprising the following steps: Acquire a 3D preview image of the object; The method according to any one of the preceding claims determines the location of the navigation echo in the preview image; as well as The tomographic images of the object are acquired while the motion of the object is corrected based on the positioning movement of the navigation echo.

13. A data processing apparatus comprising a module for performing the steps of the method according to any one of claims 1 to 11.

14. A computer program product storing a computer program including instructions that, when executed by a computer, cause the computer to perform the steps of the method according to any one of claims 1 to 11.

15. A computer-readable storage medium comprising instructions that, when executed by a computer, cause the computer to perform the steps of the method according to any one of claims 1 to 11.

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