3D ULTRASOUND IMAGING SYSTEM

Abstract

The present invention relates to an ultrasound imaging system comprising: an image processor configured to receive at least one set of volume data resulting from a three-dimensional ultrasound scan of a body and to provide corresponding display data, an anatomy detector configured to detect a position and orientation of an anatomical object of interest within the at least one set of volume data, a slice generator for generating a plurality of two-dimensional slices from the at least one set of volume data, wherein said slice generator is configured to define respective slice locations based on the results of the anatomy detector for the anatomical object of interest so as to obtain a set of two-dimensional standard views of the anatomical object of interest, wherein the slice generator is further configured to define for each two-dimensional standard view which anatomical features of the anatomical object of interest are expected to be contained, and an evaluation unit for evaluating a quality factor for each of the generated plurality of two-dimensional slices by comparing each of the slices with the anatomical features expected for the respective two-dimensional standard view.

Claims

1. An ultrasound imaging system comprising: one or more processors operable to: receive, from a trans-esophageal echocardiography (TEE) probe positioned within an esophagus of a body, first volume ultrasound data of a first trans-esophageal scan of an anatomical object within the body and second volume ultrasound data of a different second trans-esophageal scan of the anatomical object; generate, based on the first volume ultrasound data, a first plurality of two-dimensional (2D) ultrasound images corresponding to a set of standard views of the anatomical object; generate, based on the second volume ultrasound data, a second plurality of 2D ultrasound images corresponding to the set of standard views; select, for a first standard view of the set of standard views, a first ultrasound image from the first plurality; select, for a second standard view of the set of standard views, a second ultrasound image from the second plurality; and output, to a display in communication with the one or more processors, a third plurality of 2D ultrasound images corresponding to the set of standard views, wherein the third plurality comprises the first ultrasound image and the second ultrasound image.

2. The ultrasound imaging system of claim 1, wherein, to select the first ultrasound image, the one or more processors are operable to: determine a first quality factor of the first ultrasound image; determine a second quality factor of a third ultrasound image from the second plurality, wherein the first ultrasound image and the third ultrasound image correspond to the first standard view; and select, for the first standard view, the first ultrasound image based on a comparison of the first quality factor and the second quality factor.

3. The ultrasound imaging system of claim 2, wherein the one or more processors are operable to: select the first ultrasound image responsive to determining, based on the comparison of the first quality factor and the second quality factor, that the first quality factor is greater than the second quality factor.

4. The ultrasound imaging system of claim 2, wherein, to determine the first quality factor, the one or more processors are operable to compare the first ultrasound image and the first standard view.

5. The ultrasound imaging system of claim 4, wherein the one or more processors are operable to compare of a field of view of the first ultrasound image and a feature of the anatomical object associated with the first standard view.

6. The ultrasound imaging system of claim 5, wherein the one or more processors are operable to determine an amount of overlap between the field of view and the feature.

7. The ultrasound imaging system of claim 4, wherein the one or more processors are operable to compare the first ultrasound image and a geometrical model comprising the first standard view.

8. The ultrasound imaging system of claim 2, wherein the one or more processors are operable to output a graphical representation of the first quality factor to the display.

9. The ultrasound imaging system of claim 8, wherein the graphical representation of the first quality factor comprises a percentage or an icon.

10. The ultrasound imaging system of claim 8, wherein the graphical representation of the first quality factor comprises: a first icon responsive to the first quality factor being within a first range of values; a second icon responsive to the first quality factor being within a second range of values; and a third icon responsive to the first quality factor being disposed within a third range of values.

11. The ultrasound imaging system of claim 10, wherein the first icon is configured to indicate that a user obtain additional volume ultrasound data of the anatomical object.

12. The ultrasound imaging system of claim 1, the one or more processors are operable to output the third plurality such that each 2D ultrasound image of the third plurality is displayed simultaneously.

13. The ultrasound imaging system of claim 1, further comprising the display.

14. The ultrasound imaging system of claim 1, further comprising the TEE probe.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0055] These and other aspects of the invention will be apparent from and elucidated with reference to the embodiment(s) described hereinafter. In the following drawings

[0056] FIG. 1 shows a schematic representation of an ultrasound imaging system in use to scan a volume of a patient's body;

[0057] FIG. 2 shows a schematic block diagram of an embodiment of the ultrasound imaging system;

[0058] FIG. 3 schematically shows an overview of different 2D standard views of a transesophageal echography (TEE);

[0059] FIG. 4 shows a flow diagram to illustrate an embodiment of the method according to the present invention;

[0060] FIG. 5 shows a first exemplary illustration of results received with the ultrasound imaging system;

[0061] FIG. 6 shows a second exemplary illustration of results received with the ultrasound imaging system; and

[0062] FIG. 7 shows a third exemplary illustration of results received with the ultrasound imaging system.

DETAILED DESCRIPTION OF THE INVENTION

[0063] FIG. 1 shows a schematic illustration of an ultrasound system 10 according to an embodiment, in particular a medical three-dimensional (3D) ultrasound imaging system. The ultrasound imaging system 10 is applied to inspect a volume of an anatomical site, in particular an anatomical site of a patient 12. The ultrasound system comprises an ultrasound probe 14 having at least one transducer array having a multitude of transducer elements for transmitting and/or receiving ultrasound waves. In one example, the transducer elements each can transmit ultrasound waves in form of at least one transmit impulse of a specific pulse duration, in particular a plurality of subsequent transmit pulses. The transducer elements are preferably arranged in a two-dimensional array, in particular for providing a multi-planar or three-dimensional image.

[0064] A particular example for a three-dimensional ultrasound system which may be applied for the current invention is the CX40 Compact Xtreme ultrasound system sold by the applicant, in particular together with a X6-1 or X7-2t TEE transducer of the applicant or another transducer using the xMatrix technology of the applicant. In general, matrix transducer systems as found on Philips iE33 systems or mechanical 3D/4D transducer technology as found, for example, on the Philips iU22 and HD15 systems may be applied for the current invention.

[0065] A 3D ultrasound scan typically involves emitting ultrasound waves that illuminate a particular volume within a body, which may be designated as target volume. This can be achieved by emitting ultrasound waves at multiple different angles. A set of volume data is then obtained by receiving and processing reflected waves. The set of volume data is a representation of the target volume within the body.

[0066] It shall be understood that the ultrasound probe 14 may either be used in a non-invasive manner (as shown in FIG. 1) or in an invasive manner as this is usually done in TEE (not explicitly shown). The ultrasound probe 14 may be hand-held by the user of the system, for example medical staff or a doctor. The ultrasound probe 14 is applied to the body of the patient 12 so that an image of an anatomical site, in particular an anatomical object of the patient 12 is provided.

[0067] Further, the ultrasound system 10 may comprise a controlling unit 16 that controls the provision of a 3D image via the ultrasound system 10. As will be explained in further detail below, the controlling unit 16 controls not only the acquisition of data via the transducer array of the ultrasound probe 14, but also signal and image processing that form the 3D images out of the echoes of the ultrasound beams received by the transducer array of the ultrasound probe 14.

[0068] The ultrasound system 10 may further comprise a display 18 for displaying the 3D images to the user. Still further, an input device 20 may be provided that may comprise keys or a keyboard 22 and further inputting devices, for example a trackball 24. The input device 20 might be connected to the display 18 or directly to the controlling unit 16.

[0069] FIG. 2 shows a schematic block diagram of the ultrasound system 10. As already laid out above, the ultrasound system 10 comprises an ultrasound probe (PR) 14, the controlling unit (CU) 16, the display (DI) 18 and the input device (ID) 20. As further laid out above, the probe (PR) 14 comprises a phased two-dimensional transducer array (TR) 26. In general, the controlling unit (CU) 16 may comprise a central processing unit (CPU) 28 that may include analog and/or digital electronic circuits, a processor, microprocessor or the like to coordinate the whole image acquisition and provision. However, it has to be understood that the central processing unit (CPU) 28 does not need to be a separate entity or unit within the ultrasound system 10. It can be a part of the controlling unit 16 and generally be hardware or software implemented. The current distinction is made for illustrative purposes only. The central processing unit (CPU) 28 as a part of the controlling unit (CU) 16 may control a beam former (BF) 30 and, by this, what images of the volume 40 are taken and how these images are taken. The beam former (BF) 30 generates the voltages that drive the transducer array (TR) 26, determines repetition frequencies, it may scan, focus and apodize the transmitted beam and the reception of receive beam(s) and may further amplify filter and digitize the echo voltage stream returned by the transducer array (TR) 26. Further, the central processing unit (CPU) 28 of the controlling unit (CU) 16 may determine general scanning strategies. Such general strategies may include a desired volume acquisition rate, lateral extent of the volume, an elevation extent of the volume, maximum and minimum line densities and scanning line times. The beam former (BF) 30 further receives the ultrasound signals from the transducer array (TR) 26 and forwards them as image signals.

[0070] Further, the ultrasound system 10 comprises a signal processor (SP) 32 that receives the image signals. The signal processor (SP) 32 is generally provided for analog-to-digital-converting, digital filtering, for example, bandpass filtering, as well as the detection and compression, for example a dynamic range reduction, of the received ultrasound echoes or image signals. The signal processor 32 forwards image data.

[0071] Further, the ultrasound system 10 comprises an image processor (IP) 34 that converts image data received from the signal processor 32 into display data. In particular, the image processor 34 receives the image data, preprocesses the image data and may store it in a memory (MEM) 36. This image data is then further post-processed to provide images to the user via the display 18. In the current case, in particular, the image processor 34 may form the three-dimensional images out of a multitude of two-dimensional images.

[0072] The ultrasound system 10 may in the current case further comprise an anatomy detector (AD) 38, a slice generator (SLG) 40 and an evaluation unit (EU) 42. It shall be noted that the latter mentioned components may either be realized as separate entities, but may also be included in the image processor 34. All these components may be hardware and/or software implemented.

[0073] The anatomy detector (AD) 38 identifies the orientation and position of the anatomical object of interest within the acquired 3D volume data. The anatomy detector (AD) may thereto be configured to conduct a model-based segmentation of the acquired 3D volume data. This may be done by finding a best match between the at least one set of volume data and a geometrical mesh model of the anatomical object of interest. The model-based segmentation may, for example, be conducted in a similar manner as this is described for a model-based segmentation of CT images in Ecabert, O. et al.: “Automatic Model-based Segmentation of the Heart in CT Images”, IEEE Transactions on Medical Imaging, Vol. 27(9), p. 1189-1291, 2008. The geometrical mesh model of the anatomical object of interest may comprise respective segments representing respective anatomic features. Accordingly, the anatomy detector 38 may provide an anatomy-related description of the volume data, which identifies respective geometrical locations of respective anatomic features in the volume data.

[0074] Such a model-based segmentation usually starts with the identification of the orientation of the anatomical object of interest (e.g. the heart) within the 3D ultrasonic volume data. This may, for example, be done using a three-dimensional implementation of the Generalized Hough Transform. Pose misalignment may be corrected by matching the geometrical model to the image making use of a global similarity transformation. The segmentation comprises an initial model that roughly represents the shape of the anatomical object of interest. Said model may be a multi-compartment mesh model. This initial model will be deformed by a transformation. This transformation is decomposed into two transformations of different kinds: A global transformation that can translate, rotate or rescale the initial shape of the geometrical model, if needed, and a local deformation that will actually deform the geometrical model so that it matches more precisely to the anatomical object of interest. This is usually done by defining the normal vectors of the surface of the geometrical model to match the image gradient; that is to say, the segmentation will look in the received ultrasonic image for bright-to-dark edges (or dark-to-bright), which usually represent the tissue borders in ultrasound images, i.e. the boundaries of the anatomical object of interest.

[0075] The segmented 3D volume data may then be further post-processed. The slice generator (SLG) 40 generates a plurality of two-dimensional slices from the 3D volume data. Landmarks are thereto encoded within the geometrical model that defines the planes of said 2D slices. A set of three or more landmarks can represent a plane. These encoded landmarks may be mapped onto the segmented 3D volume data so as to obtain a set of 2D standard views of the anatomical object of interest generated from the 3D volume data. The slice generator 40 may be furthermore configured to define for each 2D standard view which anatomical features of the anatomical object of interest are expected to be contained within said view. This may be done using the geometrical model that is encoded with the anatomic features of the anatomical object of interest. It should thus be known which anatomical features should occur in which 2D standard view.

[0076] The evaluation unit (EU) 42 may then evaluate a quality factor for each of the generated plurality of 2D slices by comparing each of said generated slices with the anatomical features expected for the respective 2D standard view. In other words, the evaluation unit 42 computes the coverage of each of the 2D standard views by the 3D volume data. This may be done by computing the overlap of the structure that should be covered and the field of view of the 3D ultrasound scan. The quality factor that is evaluated within the evaluation unit 42 for each of the generated plurality of 2D slices may thus be a quantitative factor that includes a ratio to which extent the expected anatomical features are included in the respective 2D slice. This may be done by comparing the field of view of each of the 2D slices to the geometrical model of the anatomical object.

[0077] In still other words, this means that for each 2D slice that is generated from the received 3D ultrasound volume data, it is determined how good the 2D standard view, that corresponds to the generated 2D slice, is covered. This information can be presented as a graphical icon, e.g. as a traffic light, and/or as a percentage on the display 18.

[0078] As it will be explained further below in detail with reference to FIGS. 5 to 7, the generated 2D slices of the anatomical object of interest are preferably illustrated on the display 18 simultaneously, wherein each illustrated 2D slice is illustrated together with a graphical representation of the quality factor (icon and/or percentage) that indicates the quality of the respective 2D slice.

[0079] In practice there is usually not only performed a single 3D ultrasound scan of the anatomical object of interest. Preferably, a plurality of 3D ultrasound scans of the anatomical object of interest are performed. This results in a plurality of sets of volume data, which result from the plurality of different 3D scans of the body. For each of these sets of 3D volume data, the above-mentioned processing (segmentation, slice generation and evaluation) is performed by the ultrasound system 10. The plurality of sets of volume data resulting from the different 3D scans and the 2D slices that are generated in the above-mentioned way from said sets of volume data may be stored within the memory (MEM) 36 together with the evaluated quality factors of each of the 2D slices.

[0080] In this case a selector (SEL) 44 is configured to select for each 2D standard view a 2D slice that has the highest quality factor. This may be done by comparing the evaluated quality factors of corresponding 2D slices that are generated from each of the plurality of 3D sets of volume data which are stored in the memory 36. In other words, the selector 44 selects for each standard view the best 2D slice out of all 2D slices that have been generated from the different sets of 3D volume data (different ultrasound scans). This means that the different 2D standard views that are simultaneously illustrated on the display 18 may result from different 3D ultrasound scans, wherein the selector 44 automatically determines from which 3D volume data set a specific 2D standard view may be generated best.

[0081] This will be explained in the following in further detail by example of a transesophageal echocardiography (TEE).

[0082] For a full TEE examination, 20 different 2D TEE standard views have to be acquired. An overview of the different standard views is given in schematical manner in FIG. 3. FIG. 3a e.g. illustrates the ME four chamber view, FIG. 3b the ME two chamber view, FIG. 3c the ME LAX view and so on.

[0083] FIG. 4 shows a schematic block diagram for illustrating the method according to an embodiment of the present invention. In a first step S10 a set of volume data resulting from a 3D ultrasound scan of a body is received. In the following step S12 a position and orientation of an anatomical object of interest (e.g. the human heart) is detected within the at least one set of volume data. Thereto, a model-based segmentation of the at least one set of volume data may be conducted. As already mentioned above, this is done by finding a best match between the at least one set of volume data and a geometrical model of the human heart.

[0084] Then, said model is used to compute the planes of all 20 TEE standard views. This is done in step S14 by generating a plurality of 2D slices from the at least one set of 3D volume data. Thereto, the respective slice locations are defined based on the geometrical model of the heart. Due to the segmentation that has been performed in advance (in step S12), these respective slice locations may be mapped onto the 3D volume data, such that it is possible to compute the 2D slices from the 3D volume data set by interpolating the 3D image. For example to compute the ME four chamber view (see FIG. 3a), the plane is given by the center of the mitral valve, the center of the tricuspid valve and the apex.

[0085] Then, in step S16 it is defined for each 2D standard view which anatomical features of the heart are expected to be contained in said standard view. This may be done by encoding the geometrical model with an anatomy-related description that identifies segments of the heart within each 2D standard view that correspond to respective anatomic features, for example, the heart chambers, the main vessels, the septa, the heart valves, etc. If the geometrical model is encoded with this anatomy-related information, it is easier in the further procedure to evaluate whether the generated 2D slices cover all information that should be included within the respective 2D standard view.

[0086] In step S18 it is then evaluated for each of the generated 2D slices how good the 2D standard view is covered. Thereto, a quality factor is computed for each of the generated 2D slices, wherein said quality factor may be a quantitative factor that includes a ratio to which extent the expected anatomical features are included in the respective 2D slice. This may be done by comparing the field of view of each of the generated 2D slices to the geometrical model of the heart.

[0087] FIG. 5 shows six 2D slices that have been generated in the above-mentioned way based on a single 3D TEE image (herein referred to as a single set of volume data). The results of the performed segmentation are therein illustrated by border lines 46. FIG. 5a shows the 2D slice that corresponds to the ME four chamber standard view (compare to FIG. 3a). FIG. 5B therein shows the 2D slice that corresponds to the ME two chamber standard view (compare to FIG. 3b). FIG. 3d shows the generated 2D slice that corresponds to the TE mid SAX standard view (compare to FIG. 3d). FIG. 5h shows the generated 2D slice that corresponds to the ME AV SAX standard view (compare to FIG. 3h). FIG. 5i shows the generated 2D slice that corresponds to the ME AV LAX standard view (compare to FIG. 3i). And FIG. 5m shows the generated 2D slice that corresponds to the ME RV inflow-outflow standard view (compare to FIG. 3m).

[0088] As it may be seen, most of the anatomical features of interest are within the slices 5a, b and d, i.e. most of the border lines 46 are within the field of view. The quality factors that have been evaluated for these slices are therefore comparatively high, which is indicated in FIG. 5a, b and d by means of a graphical icon 48 that is illustrated in the upper right corner of each slice image and represents a schematical traffic light showing a green light.

[0089] It may be furthermore seen that the generated slices 5h and i are still acceptable, because the main anatomical features of interest, e.g. the aortic valve within FIG. 5h, is still within the field of view. The traffic light 48′ therefore shows a yellow light for these slices. In FIG. 5m most of the border lines 46 are however out of the field of view, meaning that the anatomical features of interest, i.e. the in and outflow of the right ventricle, are not fully covered. The quality of this generated 2D slice is thus evaluated to be rather low, which is indicated in FIG. 5m with a traffic light 48″ that shows a red light.

[0090] Returning back to FIG. 4 now, the method steps S10-S18 are repeated for every new 3D TEE image. This means that for every 3D TEE image (every 3D volume data set), all 20 2D slices are generated and evaluated that correspond to the 20 different 2D TEE standard views illustrated in FIG. 3. For every 2D slice it is defined, which anatomical features are to be expected therein, i.e. which border lines 46 should occur in these 2D slices (step S16). And for every 2D slice it is evaluated, whether the expected border lines are within the field of view, or to which extend this is the case (step S18).

[0091] FIG. 6 illustrates 2D slices that have been generated (and evaluated) based on a second 3D TEE image (second set of volume data) with a different field of view. From FIG. 6 it may be seen that the generated slices 6a, b and d are compared to the slices shown in FIG. 5a, b and d rather unsuitable (indicated by red traffic light 48″). However, the generated 2D slices corresponding to the ME AV SAX standard view (FIG. 6h), the ME AV LAX standard view (FIG. 6i) and to the ME RV inflow-outflow standard view (see FIG. 6m) have a rather good quality, since the anatomical features of interest (border lines 46) are this time within the field of view.

[0092] It may therefore be seen that the 2D standard views a, b and d are best covered within the 2D slices that were generated from the first 3D volume data set (illustrated in FIG. 5a, b and d), while the 2D standard views h, i and m are best covered within the 2D slices that were generated from the second 3D volume data set (illustrated in FIG. 6h, i and m).

[0093] In step S20 (see FIG. 4) the best version for each 2D standard view is then automatically selected. For each 2D standard view one generated 2D slice is selected that has the highest quality factor. This may be done by comparing the evaluated quality factors of corresponding 2D slices generated from each of the received sets of volume data (from each of the received 3D TEE images). This “best selection” is finally illustrated on the display in step S24.

[0094] The result is shown in FIG. 7. As it may be seen in FIG. 7, the system 10 automatically selected the more suitable 2D slices that were generated from the first 3D TEE image as 2D standard views a, b and d, while it automatically selected the 2D slices that were generated from the second 3D TEE image as 2D standard views h, i and m. In summary, this means that only two 3D TEE images were necessary in this example to generate the exemplarily shown six 2D standard views, whereas six different ultrasound scans would be required when manually scanning the patient with a regular 2D ultrasound scanning system. The further significant advantage is that the system selects the best 2D slices by itself. The presented method is thus less error-prone and faster compared to the conventional TEE procedure.

[0095] A still further improvement of the method schematically illustrated in FIG. 4 is shown by step S22. Instead of using the 2D slices that were interpolated from the 3D volume data set, the 2D slices may also be generated by performing an additional 2D scan as soon as the system recognizes that a quality factor of a 2D slice that is generated in steps S10-S18 is above a predetermined threshold value. This means that as soon as the system recognizes that the field of view of the taken 3D image is suitable for a specific 2D standard view, the imaging parameters for this 2D standard view from the current location of the transducer probe 14 are computed and the transducer probe 14 automatically performs an additional 2D scan to directly receive the 2D standard view. This “extra” acquisition should however only be done if it has been found in step S18 that the quality of the generated 2D slice is rather high, meaning that the position and orientation of the transducer probe 14 is suitable for acquiring the respective 2D standard view.

[0096] It shall be noted that step S22 is not a mandatory, but an optional method step. Of course, a combination of both, generating the 2D slices from the 3D volume data set and generating the 2D slices directly by performing an additional 2D scan, is possible as well.

[0097] While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; the invention is not limited to the disclosed embodiments. Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims.

[0098] In the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. A single element or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

[0099] A computer program may be stored/distributed on a suitable medium, such as an optical storage medium or a solid-state medium supplied together with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems.

[0100] Any reference signs in the claims should not be construed as limiting the scope.