Patent Description:
Three-dimensional (3D) ultrasound data acquisition (or volumetric ultrasound) is a developing technological field.

One useful application for 3D ultrasound is for imaging the heart, since it allows for more accurate observation of heart structures, such as heart chambers and heart valves. 3D ultrasound however can usefully be applied to the imaging of any anatomical region or structure.

Four-dimensional (4D) ultrasound data acquisition comprises the acquisition of a temporal series of 3D ultrasound imaging frames.

The acquisition of 4D ultrasound data encompasses a trade-off between 3D spatial resolution, temporal resolution, and the size of the 3D field of view (FOV). For a fixed temporal resolution (i.e. frames per second), then a larger 3D FOV means reduced spatial resolution within each 3D frame and vice versa. Likewise, for a fixed FOV size, increased temporal resolution necessitates a reduced spatial resolution.

Thus, in most instances, in order to ensure that the required anatomical object or region is fully captured in the FOV, the FOV size is kept relatively large meaning that temporal resolution or spatial resolution has to be reduced. The FOV captured by a 3D ultrasound scan is typically either a cone shape or pyramid shape emanating from the ultrasound emission source. Reducing the size of the cone or pyramid risks cutting off part of the object being imaged.

For example, in cardiac imaging, often parts of the heart are cut off, either at the apex, at the lateral wall, or at the right ventricle. If the acquisition is wide enough to cover the complete heart, the frame rate is consequently quite low.

This frame rate not only affects diagnostic capability of the clinician, but also impacts on the accuracy of automated segmentation and quantification algorithms applied to the data for identifying anatomical object dimensions, and determining physiological parameters (e.g. hemodynamic parameters in the case of cardiac imaging). Such algorithms and models require high frame rate, e.g. in the case of 3D coronary artery disease detection by regional wall motion analysis. In current clinical setups, in order to achieve the required frame rate, 2D imaging must be used instead of 3D. Several 2D sequences are acquired with high frame rate (e.g. ~<NUM>). The sonographer then has to mentally compile or amalgamate these 2D results to make a diagnosis since, in principle, motion abnormality analysis is a 3D problem. This stitching process is complex and might lead to misinterpretations.

It is an aim to find a technical solution to address one of more of the above-identified problems.

<CIT> discloses an ultrasound imaging method in which an entire volume is scanned and a sub-volume is separately scanned with different settings for beamforming parameters.

<CIT> discloses an ultrasound control unit for coupling with an ultrasound transducer unit and adapted to control a drive configuration or setting of the transducers of the transducer unit, each drive setting having a known power consumption level associated with it.

<CIT> discloses a method for switching between fields of view of an ultrasound probe.

In accordance with an aspect of the invention, there is provided a computer-implemented method. The method comprises obtaining reference 3D ultrasound data of an anatomical region for a first 3D FOV, wherein the reference ultrasound data comprises data for a series of scan lines, each scan line having a scan angle relative to a first (ϕ) and second (θ) angular scan direction, and maximum scan depth (d) along a direction of the scan line.

The method further comprises defining a volumetric region within the anatomical region, the volumetric region having one or more boundaries.

The method further comprises adjusting one or more scanning parameters to acquire new 3D ultrasound data with an adjusted 3D FOV, wherein adjusting the scanning parameters is performed in dependence upon the boundaries of the volumetric region, and wherein the adjusted 3D FOV fully encompasses the volumetric region, and wherein adjusting the scanning parameters comprises adjusting the maximum scan depth (d) of each individual scan line.

The method further comprises acquiring new 3D ultrasound data for the adjusted 3D FOV using the adjusted scanning parameters.

Thus the method is based on modifying individual scan line depths (or lengths) so as to enable acquisition of an arbitrarily shaped and sized 3D FOV. This allows for the 3D FOV to be reduced in size in a more controlled and directed way, so that risk of missing part of the anatomy of interest is reduced. For example, the adjusting the maximum scan depth (d) of each individual scan line may comprise adjusting a time duration of a receive phase of a transmit/receive sequence of one or more transducers used to acquire the relevant scan line.

As result, in the context of 4D imaging, the frame rate can be increased. This may improve the quality of results derived from automated quantification operations, which determine physiological parameters from ultrasound image data. It may also enable new applications, such as analysis of regional wall motion abnormalities in 3D, where a high frame rate is required.

The volumetric region may be a smaller 3D volume than the whole anatomical region covered by the reference scan. Therefore, it can be acquired in less time. The acquisition is enabled through controlling the scan depth of each individual scan line to match the desired 3D FOV. This ensures that the relevant anatomical sub-region is captured (where the region this could be user-defined, or automatically detected through segmentation).

Scan line depth means a depth along a direction of the scan line, i.e. along an axis parallel to the propagation path of the scan line through the body. In other words scan line depth in this context means the same as scan line length. The scan line depth is adjustable through control of acquisition or transmission parameters (i.e. drive parameters of the transducer array). Thus, the scan line depth is adjusted at the level of the transducers (rather than for example being adjusted through post-processing of acquired ultrasound signal data). In this way, acquisition speed can be improved, by limiting the scan line depth to only that needed for acquiring the volumetric region.

In particular, most commonly the scan line depth is controlled by controlling the time duration of the receive phase of the transmit/receive sequence of the relevant transducer(s) used to acquire the relevant scan line.

There are different ways that the region to be covered by the adapted FOV can be defined. It can be defined manually, for example using user input. It can be defined according to a pre-configured control scheme. In further examples, it can be defined automatically using anatomical image analysis applied to the reference image data. In all cases, the technical effect of reducing the total spatial volume over which data needs to be acquired is achieved, and this is achieved through modifying the FOV at the level of each individual scan line: adapting each scan line length so as to capture a 3D FOV having arbitrarily customizable boundaries.

In some cases, the adjusted FOV may have a set of boundaries which coincide with at least a subset of boundaries of the defined volumetric region.

In some (though not all) embodiments, the method comprises applying anatomical segmentation, and wherein the volumetric region is defined in dependence upon the anatomical segmentation.

There are different ways of controlling the scan parameters so as to enable to acquisition of the adjusted FOV, and these are now briefly outlined.

In at least one set of embodiments, the scan parameters are adjusted such as to define a set of scan lines having scan depths set such that each scan line terminates at a point of intersection of the scan line with a distal-most one of the one or more boundaries of the defined volumetric region. Distal-most means furthest along the length of scan line from the ultrasound emission source. All of the scan lines may be set in this way or just a portion. For instance, just the set of scan lines which coincide with the volumetric region may be set in this way.

As a variation on this, in some embodiments, the method may comprise defining a termination point for each scan line depth based on, for each scan line, identifying the line depth (or length) to the detected point of intersection with the boundary of the volumetric region, and adding a defined margin to this intersection depth, and setting the line depth for the adjusted FOV equal to this depth with the margin added. This allows for a certain margin or spacing around the volumetric region, in the depth direction.

The method may further comprise identifying a subset of scan lines which do not intersect with the defined volumetric region, and wherein the scan lines which do not intersect are deactivated when scanning the adjusted FOV. Deactivated means that, in acquiring ultrasound data for the adjusted 3D FOV, these scan lines are not generated/fired.

In some cases, all of the scan lines which do not intersect with the volumetric region are deactivated. In a variation on this, in some embodiments, a portion of the non-intersecting scan lines may be retained, for example to capture a pre-defined margin or spacing region around the volumetric region, as will be explained more later.

The scan lines in each of the reference and new 3D ultrasound data may be understood to span each of a series of 2D planes, wherein the series of 2D planes together span the respective 3D FOV across the first angular direction (ϕ), and the scan lines forming each plane span the plane across the second angular direction (θ), and wherein each 2D scan plane has an angular orientation along said first angular direction.

In some embodiments, adjusting the scan parameters may comprise:.

Scan lines outside of the maximum angular width are deactivated.

The maximum angular widths may be set in dependence upon the boundaries of the identified volumetric region.

In some cases, the maximum angular width (Δθ) for each plane is set to the minimum width required for said plane to fully encompass the boundaries of the volumetric region. The same might also be applied for the maximum angular width (Δϕ) along said first angular direction spanned by the series of scan planes. In this case, the adjusted 3D FOV is sized to just encompass the desired volumetric region.

In other examples, the maximum angular width (Δθ) for each plane is set to a sum of: the minimum width required for said plane to fully encompass the boundaries of the volumetric region, and a defined angular margin. The same may also be applied for the maximum angular width (Δϕ) along said first angular direction spanned by the series of scan planes.

In some examples, each 2D plane of ultrasound data may be acquired by sequentially firing a series of scan lines at sequentially incrementing or decrementing scan angles along the second angular direction θ relative to the transducer arrangement, and wherein all the lines lay in said same plane. This process is then repeated sequentially for a series of planes, and wherein each plane has an angle of orientation along said first angular dimension ϕ relative to the z-axis.

The planes may typically be triangular or truncated triangular, where the angular width of the plane means the angle of the apex of the plane.

In accordance with any of the above-described approaches, in some cases, the adjusted 3D FOV may include a subset of scan lines which do not intersect the volumetric region (e.g. when a margin or spacing is desired around the volumetric region). In these cases, optionally, the maximum scan depth for said subset of scan lines is set based on a scan depth which has been set for a nearest scan line which does intersect the object of interest.

Nearest may mean angularly nearest, i.e. the intersecting line whose scan angle θ, ϕ is closest to the respective non-intersecting scan line.

There are different approaches to defining the volumetric region. In some embodiments, it may be defined manually, e.g. through user input. In some cases, it may be predetermined. In a preferred set of embodiments, it is defined in dependence upon a result of an automated anatomical segmentation procedure applied to the reference ultrasound data.

Thus, in accordance with at least one set of embodiments, the method comprises applying segmentation to the reference 3D ultrasound data to detect boundaries of an anatomical object-of-interest in the reference 3D ultrasound data; and defining the volumetric region within the anatomical region in dependence upon the detected boundaries of the anatomical object-of-interest. In particular, the volumetric region may be defined so as to fully contain the detected boundaries of the anatomical object of interest.

Within this set of embodiments, there are further options for how the volumetric region is defined based on the segmentation.

For example, in a simple case, the boundaries of the detected anatomical object-of-interest are simply used as the boundaries of the volumetric region. In other words, the boundaries of the volumetric region are set so as to match the detected boundaries of the anatomical object of interest.

As a variation on this, the boundaries of the volumetric region may instead be defined so as to fully contain the detected boundaries of the anatomical object of interest in addition to a pre-defined spacing or margin around the boundaries of the object of interest, for instance for accommodating motion of the object.

In some embodiments, defining the volumetric region may comprise defining a 3D shape for the volumetric region, and defining a scale size of said shape which is the minimum able to accommodate the boundaries of the anatomical object of interest, and optionally in addition to a defined spacing around the boundaries.

Here, defining the 3D shape of the volumetric region may comprise: defining the shape according to a pre-defined shape template (for example a cylinder, a cuboid, an ellipsoid, a pyramid, a truncated or frustrated pyramid, an elliptical cylinder, or any other shape), or may comprise determining a custom shape based on the detected boundaries of the object. In the latter case for example, defining the shape may comprise determining a custom shape based on the detected boundaries of the object, and wherein the custom shape is a convex hull. In some cases for example, detecting the boundaries of the anatomical object may comprise detecting segmentation mesh vertex points which span the boundaries of the object, or may comprise detecting voxels which span the boundaries of the object, and wherein the convex hull is defined to connect said vertex points or voxels.

As mentioned, in some cases, the volumetric region is defined to include a spacing around the object of-interest for accommodating movement. Determining the spacing could in some cases be performed automatically based on the reference ultrasound data. In particular, if the reference ultrasound data is 4D ultrasound data (i.e. comprising a series of frames of 3D ultrasound data), then in cases where the volumetric region is defined so as to fully contain the detected boundaries of the anatomical object of interest in addition to a pre-defined spacing around the object boundaries, in some embodiments, an extent of said spacing around the boundaries may be determined based on detecting a maximal extent of the object-of-interest boundary across the series of frames.

A further aspect of the invention provides a computer program product comprising code means configured, when executed on a processor which is communicatively coupled with an ultrasound imaging apparatus, to cause the processor to perform a method in accordance with any embodiment or example outlined in this disclosure, in accordance with any claim of this application.

Another aspect of the invention provides a processing arrangement comprising: an input/output, for two-way communication with an ultrasound imaging apparatus, and one or more processors.

The one or more processors are adapted to perform at least the following steps:.

A further aspect of the invention provides a system comprising an ultrasound imaging apparatus; and a processing arrangement in accordance with any embodiment of examples outlined in this disclosure, or in accordance with any claim of this application. The processing arrangement is communicatively coupled with the ultrasound imaging apparatus for receiving ultrasound image data and for communicating the adjusted scanning parameters to the ultrasound imaging apparatus.

The invention provides a method for adapting a 3D field of view (FOV) in ultrasound data acquisition so as to minimize the FOV volume in a manner that is precisely controllable. The method comprises defining a volumetric region across which 3D ultrasound data is desired, and then adapting the data acquisition field of view (FOV) in dependence upon the defined volumetric region, to encompass the region. This is achieved based on adapting a scan line length (or scan depth) of each individual scan line based on the defined volumetric region. In some embodiments, the volumetric region may be defined based on anatomical segmentation of a reference ultrasound dataset acquired in an initial step, and setting the volumetric region in dependence upon boundaries of an identified object of interest. The volumetric region may in a subset of embodiments be set as the region occupied by a detected anatomical object of interest.

As aspect of the invention provides a computer implemented method as will be described below.

The computer-implemented method can be implemented by a processing arrangement, and a processing arrangement adapted to perform the method forms another aspect of this invention.

In implementing the method, the processing arrangement may be operatively coupled with an ultrasound imaging apparatus for acquisition of ultrasound data. A system which comprises the processing arrangement and the ultrasound imaging apparatus together also forms another aspect of this invention. The system may include further components such as a user interface comprising a display, which may be controlled to display a rendering of acquired ultrasound imaging data.

By way of illustration, <FIG> schematically outlines an example system <NUM> in accordance with one or more embodiments of the invention. The system comprises a processing arrangement <NUM>. The processing arrangement comprises an input/output (I/O) <NUM>, for two-way communication with an ultrasound imaging apparatus <NUM>, and further comprises one or more processors ("proc") <NUM>. The one or more processors are adapted to implement a method as will be outlined below. The system <NUM>, the processing arrangement <NUM> and the method described below each may be provided independently as a respective aspect of the invention.

The computer-implemented method in accordance with one or more embodiments comprises, in summary, at least the following steps:.

Adjusting the scanning parameters comprises adjusting a maximum scan depth (d) of each individual scan line. For example it may comprise, for at least a subset of the scan lines, adjusting a maximum scan depth of the line in dependence upon a detected point of intersection between a distal-most (along a direction of the line from the ultrasound source) boundary of the volumetric region. For example, in some cases, a terminal end point of each scan line is set to coincide with said detected point of intersection. For some scan lines, the line depth may be set to zero (i.e. the line is deactivated or not generated at all).

The reference 3D ultrasound data may be obtained passively, for example it is received at the input/output of the processing arrangement from an ultrasound imaging apparatus which has acquired it. Alternatively, the method may comprise actively controlling an ultrasound transducer arrangement comprised by the imaging apparatus to acquire the data, or may issue one or more control instructions to the ultrasound imaging apparatus to cause the imaging apparatus to acquire the reference ultrasound imaging data.

The method is further illustrated by <FIG>, which illustrate acquisition of ultrasound data with an ultrasound transducer unit <NUM> comprising an ultrasound transducer arrangement <NUM> which provides a source of ultrasound emissions.

With reference, to <FIG>, both the aforementioned reference 3D ultrasound data, and the new 3D ultrasound data, can be understood as comprising data for a series of scan lines <NUM> spanning each of a series of elevational 2D planes <NUM>. The series of elevational 2D planes together span the first 3D FOV <NUM> across a first angular direction, ϕ (see <FIG>), and the scan lines forming each plane span the plane across a second angular direction, θ (<FIG>). Each 2D scan plane 14j thus has an angular orientation ϕj along said first angular direction. The second angular direction, θ, is orthogonal to the first angular direction, ϕ. Each scan line 16i can be fully defined by a scan line angle (Φi, θi) defining its angular direction from the ultrasound source relative to each of the first ϕ and second θ angular directions. Each scan line also has a maximum scan depth, di, along a direction of the scan line. Within each given scan plane 14j , the scan lines <NUM>i all have the same scan angle in the first angular direction ϕ, equal to the orientation of the respective plane ϕj, and vary in orientation across the plane <NUM> in the second angular direction θ (<FIG>).

Each 2D scan plane <NUM>j has a maximum angular width, Δθ, along said second angular direction, spanned by the scan lines <NUM> in the scan plane (see e.g. <FIG>).

The complete 3D FOV furthermore has a maximum angle, Δϕ, along said first angular direction spanned by the series of scan planes (see <FIG>).

The first ϕ and second θ angular dimensions may be defined relative to a central z axis, or a central origin, where the origin centers on the source of the ultrasound emissions (i.e. the transducer arrangement <NUM>).

<FIG> illustrates how each 2D plane <NUM>j of data may be formed by sequentially generating a series of scan lines <NUM>i which span an angular width Δθ of the plane across the second angular dimension θ. Each plane of ultrasound data is acquired by sequentially firing the scan lines at sequentially incrementing or decrementing scan angles, θi, along the second angular direction θ relative to the transducer arrangement <NUM>, and all the scan lines lying in said same plane <NUM>. In this way, the data for the full plane is sequentially compiled, one scan line at a time. As shown in <FIG>, this process is then repeated sequentially for a series of planes <NUM>j, and wherein each plane has an angle of orientation ϕj along said first dimension ϕ relative to the z-axis (see <FIG>). <FIG> is schematic only, and more scan lines or fewer scan lines may in practice be used.

<FIG> schematically illustrates for a single example scan line <NUM>i the scan angle, θi, of the scan line along the second angular direction θ, and the scan depth di of the scan line along the direction of the line. The scan depth of each individual scan line is individually adjustable for example through control of the time duration of the receive phase of the transmit/receive sequence of the relevant transducer(s) used to acquire the relevant scan line. In particular, a scan line is acquired with a transmit/receive sequence in which an ultrasound pulse signal is transmitted from the transducer, and immediately following this, the same transducer or an adjacent transducer begins sensing or sampling the returning echo of the transmitted signal (the echo signal) for a certain sampling time window, which may be referred to as the receive phase window. By controlling the time duration of the receive phase time window, the depth to which the echo signal is sampled is controlled, since later received echo signal portions correspond to deeper locations within the body from which the echo signal portion has back-reflected. Thus, in this way, the scan depth of each scan line can be individually controlled, by controlling the corresponding transducer receive phase time window.

In more detail, the control of the transmit/receive sequences of the transducers may be implemented with a timing table that controls the length of each scan line. Each line effectively begins with a transmit pulse. A few microseconds after the transmit pulse, the returning echoes start to be received back from the body for that line. The scan line effectively terminates when the system ceases to measure or sample the returning echo signals. If the same transducer is used both for transmission and sensing (in alternating duty cycles), then a scan line effectively ends when the transmit pulse for the next line is generated. Therefore, controlling the scan depth of each scan line may in practice comprise configuring the timing table which controls the transmit/receive phase timings for each scan line, and this could be configured by a controller of the system.

<FIG> schematically illustrates for a single example 2D scan plane <NUM>j the maximum angular width Δθ of the plane across the second angular direction θ.

<FIG> illustrates for a single example 2D scan plane <NUM>j the angle of orientation ϕj of the plane along said first dimension ϕ relative to the z-axis.

<FIG> schematically illustrates acquisition of a full volumetric dataset covering a 3D FOV within an anatomical region by sequentially acquiring data across a series of 2D scan planes 14a-14e, where the series of scan planes together span a maximum angular width Δϕ across the first directional dimension ϕ. Although five planes <NUM> are shown in <FIG>, more or fewer planes may in practice form the 3D FOV.

For purposes of illustration, the 3D FOV shown in <FIG> is taken to be the first 3D FOV <NUM> referred to previously, the ultrasound data for which forms the reference ultrasound data referred to previously. In this example, the first 3D is taken to have a standard FOV geometry (e.g. using a cone or pyramid shaped geometry) which for example spans the maximum possible angular width in both the first ϕ and second θ directions, and in which each plane <NUM>i has identical shape. In other words it is the full possible FOV. However, this is not essential.

<FIG> illustrates defining an example volumetric region <NUM> within the anatomical region covered by the first 3D FOV <NUM>. In this example, the volumetric region <NUM> is a sub-region of the volume spanned by the first 3D FOV <NUM>, i.e. it defines smaller volume than the first 3D FOV. However, this is not essential, and the volumetric region could be larger than the first 3D FOV.

The first 3D FOV <NUM> acts for example as a survey scan, which may be used to inform the defining of the volumetric region <NUM>.

In the illustrated example, the volumetric region <NUM> is set simply as a pre-defined geometrical shape - in this case a cylinder. However, as will be explained in detail further below, in other examples, the shape of the volumetric region can be defined arbitrarily, and could have any regular or irregular 3D geometry. The volumetric region <NUM> may be manually defined, e.g. via user input, may be pre-defined, e.g. by a pre-set control scheme, or (as will be discussed in detail late) may be automatically defined based on anatomical image analysis applied to the reference image data. For example, the method may comprise applying segmentation to the reference 3D ultrasound data and the volumetric region may be defined in dependence upon boundaries of an identified anatomical object-of-interest obtained from the segmentation. The boundaries of the volumetric region may simply be set as the boundaries of the identified object, or it may be set differently, e.g. as a shape which encompasses the boundaries of the anatomical object, plus some margin or spacing.

Once the volumetric region <NUM> is defined, one or more scanning parameters are adjusted to acquire new 3D ultrasound data with an adjusted 3D FOV <NUM> having boundaries set in dependence upon the boundaries of the volumetric region <NUM>. The adjusted 3D FOV should at least fully encompass the volumetric region.

There are at least two main approaches to doing this.

The first is to identify the subset of the scan lines <NUM>i which intersect with at least one boundary of the volumetric region <NUM>; identify the point of intersection of each of the identified subset of scan lines with a boundary of the defined volumetric region; and then adjust each respective scan line <NUM>i depth, di, such that a terminal point of the scan line coincides with the identified point of intersection for the scan line, and preferably wherein the boundary is a distal-most boundary of the volumetric region along the direction of the scan line. Remaining non-intersecting scan lines <NUM> are deactivated (in other words, when scanning the adjusted FOV to acquire the new ultrasound data, the non-intersecting scan lines are not generated/fired). This results in an adjusted FOV which has boundaries which at least partially match or map onto boundaries of the volumetric region.

In a variation to this approach, instead of setting of the scan line <NUM>i depths, di, so that the scan line terminates at the aforementioned point of intersection, the scan line termination point may instead be set based on, for each scan line, identifying the line depth/length to the point of intersection, and adding a defined margin to this intersection depth, and then setting the line depth for the adjusted FOV equal to this depth with the margin added. This optionally allows for the adjusted FOV to include a spacing or margin around the volumetric region in the line depth direction.

The second approach is similar to the first except that, instead of simply deactivating scan lines which do not intersect with the volumetric region, instead the method comprises a step of determining a maximum scan width Δθ of each scan plane <NUM>j in the second angular direction, and a maximum scan width Δϕ spanned by the collection of planes <NUM> across the first angular direction, and where these are determined in dependence upon the identified boundaries of the volumetric region <NUM>. This allows for greater flexibility and control in the size and geometry of the adjusted FOV relative to the volumetric region <NUM> of interest. This optionally allows for example, for inclusion within the adjusted FOV of scan lines which do not intersect with the volumetric region, for instance to allow for a certain spacing or margin around the volumetric region. Thus, in particular, for each plane <NUM>j: the maximum angular width, Δθ, may be set to the minimum width required for said plane to fully encompass the boundaries of the volumetric region <NUM>; or the maximum angular width may be set to a sum of: the minimum width required for said plane <NUM>j to fully encompass the boundaries of the volumetric region, and a defined angular margin or spacing. Scan lines <NUM> outside of the maximum angular widths are deactivated. The same may also be applied for setting the maximum angular width, Δϕ, along said first angular direction spanned by the series of scan planes.

Determining the minimum angular widths Δθ, Δϕ, to fully encompass boundaries of the volumetric region can be done by identifying, within the same co-ordinate system used to define the scan lines <NUM> and scan places <NUM>, angular co-ordinates of points which lie on the boundaries (e.g. boundary surfaces) of the volumetric region, and then identifying the maxima among these points, for example maximum angular position among these points in each of the first ϕ and second θ angular directions.

To illustrate further, an example is considered below in which it is desired that the adjusted FOV be set so that its boundaries at least partially match or map onto the boundaries of the volumetric region (i.e. without a spacing or margin).

To achieve this, the scan depth of each scan line <NUM>i in each scan plane <NUM>j is individually adjusted, to set the scan depth equal to an identified point of intersection of the respective scan line with an outer boundary of the volumetric region <NUM>. Thus the method may comprise a step, after defining the volumetric region, of determining a point of intersection of each scan line with an outer boundary of the defined volumetric region, and setting the scan line depth of each line so that the scan line terminates at said point of intersection. In this way, the adjusted FOV <NUM> will have a 3D shape that at least partially matches the 3D shape of the defined volumetric region <NUM>. If the scan line coincides with more than one boundary of the volumetric region, its depth may be set to terminate at a point of intersection with the boundary of the volumetric region which is at the furthest distance along its length from the ultrasound source, i.e. the distal-most boundary.

To illustrate further, <FIG> schematically illustrates the acquisition of a single plane <NUM>j of data within the adjusted FOV <NUM>. As shown, the scan depth of the scan lines <NUM> in the plane have each been individually adjusted so that they terminate at a point of intersection with the outer boundary of the volumetric region. The resulting scan plane <NUM>j has a shape defined by a set of outer boundaries, and wherein a subset of these boundaries coincide with a subset of the boundaries of the volumetric region <NUM>. The plane also has further boundaries extending from the ultrasound source, and span the area of scan line propagation toward the volumetric region from the ultrasound source. The total resulting adjusted 3D FOV <NUM> will likewise comprise a set of outer boundaries, a subset of which coincide with the boundaries of the volumetric region <NUM>. In particular, the distal-most boundaries of the volumetric region along directions of ultrasound propagation from the ultrasound source will coincide with distal-most boundaries of the adjusted 3D FOV along said directions of propagation.

By way of further schematic illustration, <FIG> shows a further example first FOV <NUM>, the data for which forms an example reference ultrasound dataset. <FIG> shows a further example adjusted FOV <NUM>, having a shape configured according to a defined volumetric region within the first FOV. As shown, in this example, the shape is a contorted pyramid shape.

<FIG> illustrates the adjusted FOV <NUM> from different angles within the context of the first FOV <NUM>. As can be seen, the adjusted FOV <NUM> in this case is smaller than the original FOV <NUM>.

As mentioned above, the volumetric region <NUM> may be defined based on the result of anatomical segmentation applied to the reference ultrasound data. The volumetric region may simply be defined as the volume which is occupied by a detected anatomical feature or object, i.e. the boundaries of the volumetric region are set to match the boundaries of the detected anatomical object. In some other examples, the volumetric region may be set as a shape template which is sized and positioned to encompass the volume occupied by the detected anatomical object. The latter may be computationally more efficient, since it may allow for some of the scan line depth calculations to be performed partially in advance for instance.

Thus, by way of further explanation, in accordance with an advantageous set of embodiments, the method comprises applying segmentation to the reference 3D ultrasound data to detect boundaries of an anatomical object-of-interest in the reference 3D ultrasound data, and further comprises defining the volumetric region within the anatomical region in dependence upon the detected boundaries of the anatomical object-of-interest, wherein the volumetric region is defined so as to at least fully contain the detected boundaries of the anatomical object of interest.

For example, the segmentation may comprise application of a model-based segmentation operation, and/or a machine-learning based segmentation. The output of the segmentation may be a mesh comprising connected vertices which define outer boundaries of a segmented object-of-interest. An example output segmentation mesh <NUM> is shown in <FIG> (bottom right). In this example, the anatomical object-of-interest is the heart.

With regards to implementation of model-based segmentation, various segmentation algorithms are known in the art.

Reference is made for example to the following paper which outlines one example segmentation algorithm: <NPL>.

Reference is further made to the following paper which outlines a further example segmentation algorithm: <NPL>.

In some examples, the volumetric region <NUM> is defined so as to fully contain the detected boundaries of the anatomical object of interest, in addition to a pre-defined spacing around the object boundaries, for example for accommodating motion of the object. For example, at least the new 3D ultrasound data acquired with the adjusted FOV may in fact be 4D ultrasound data, comprising a plurality of frames of 3D ultrasound data. Thus, movement of the object may occur, for example if the object exhibits cyclical motion, e.g. the heart or the lungs.

In some examples, defining the volumetric region may comprise defining a 3D shape for said volumetric region, and wherein the 3D shape contains the anatomical object of interest. To relate the volumetric region to the anatomical object of interest, the method may further comprise defining a scale size of said shape which is the minimum able to accommodate the boundaries of the anatomical object of interest, and optionally in addition to said defined spacing around the boundaries (for accommodating movement).

There are different ways to define the 3D shape of the volumetric region. These will be explained in more detail to follow.

The 3D shape of the volumetric region may be defined according to a pre-defined shape template. By way of non-limiting example, the pre-defined shape template may be one of: a cylinder, a cuboid, an ellipsoid, pyramidal shape, truncated or frustrated pyramidal shape, elliptically cylindrical or any other 3D shape.

In further examples, the method further comprises determining a custom shape based on the detected boundaries of the object. For example, defining the shape may comprise determining a custom shape based on the detected boundaries of the object. The custom shape may be a convex hull. For example, the detecting the boundaries of the anatomical object comprises detecting segmentation mesh vertex points which span the boundaries of the object, or comprises detecting pixels which span the boundaries of the object, and wherein the convex hull is defined to connect said vertex points or pixels. This effectively results in a volumetric region with boundaries which match (as closely as possible) the boundaries of the detected anatomical object of interest.

As noted above, a technical advantage of the FOV adaptation method according to embodiments of the present invention is that it enables improved frame rate in 4D imaging by minimizing the size of the 3D FOV without risking excluding important anatomical details.

Thus, in some embodiments, the adjusted 3D FOV <NUM> may be set to be smaller in volume than the first 3D FOV, and wherein the method further comprises increasing an acquisition frame rate of the 4D ultrasound data after the FOV has been adjusted.

By way of further illustration of the invention, a further example implementation, in accordance with at least one set of embodiments, will now be described in detail. For illustration, this is described with reference to 4D ultrasound imaging of the heart. However, the same principles can be applied to imaging of any anatomical object or region of interest, and 4D imaging is not essential.

In this embodiment, 3D anatomical intelligence is used to compute a volumetric region, acquired with a computed 3D scanning pattern, which is the smallest sufficient needed to capture an anatomical region of interest. This allows, in the context of 4D imaging, highest possible frame rates. It allows, for example, to avoid (error prone) extraction of 3D information from 2D image data.

The method flow according to this embodiment is in accordance with the outline already provided above, and described with reference to <FIG>. In summary, the method flow is as follows.

As a first step, a first 3D ultrasound image of the heart is acquired. This may for example use a standard or default FOV geometry, e.g. with a cone or pyramid shaped FOV. This forms reference 3D ultrasound data.

The reference 3D ultrasound image is then processed with a segmentation operation to derive anatomical context. This may for example comprise application of a model-based segmentation, or a deep-learning-based artificial neural network. The output of the segmentation may for example be a labelled segmentation mesh comprising connected vertices which together span an outer boundary of an anatomical object-of-interest, i.e. the heart in this case. In further examples, the output may be a segmentation mask which defines one or more pixels lines and/or surfaces within the reference 3D image which represent the boundaries of the object-of-interest.

Neural networks for generic 2D or 3D image segmentation (voxel classification/labelling) are known in the art.

Using the mesh or the mask, a 3D volumetric region is then defined which contains within it all heart structures for which imaging data is desired, and optionally also a further margin to cover heart motion over the cardiac cycle, i.e. heartbeat to heartbeat. Such margins can also ensure that the target structures are imaged with some spatial anatomical context.

This can be achieved for example by processing all vertices of the mask, or all voxels of the mask, and recording the corresponding scan angles (θ, ϕ) relative to the z-axis at which the vertex of each voxel lies. From this, a minimum scan width Δϕ which needs to be spanned by the series of scan planes in order to capture all vertices or voxels can be determined. In addition, a minimum required width Δθ of each plane needed to include all vertices or voxels can be determined. Scan lines outside of these angular widths may be deactivated, i.e. not subsequently used in data acquisition.

Furthermore, from the recorded scan angle values of each vertex or voxel, a 3D volumetric region can be defined relative to the ultrasound apparatus co-ordinate system (d, θ, ϕ) which contains the whole of the detected boundary of the anatomical object of interest. For example, a standard 3D shape such as a circular, elliptic, or rectangular angular region can be determined, or a custom shape can be defined, e.g. a convex hull which connects the vertex points of the boundary mesh or the voxels/pixels of the boundary mask.

It is noted that the resulting angular region of the adjusted 3D FOV can be wider that the first FOV of the reference scan or may be less wide. For example, if certain portions of the target anatomical object were not fully covered in the first FOV, then the adjusted FOV can be larger. In other cases, the adjusted FOV may be smaller than the first FOV. Most generally, the adjusted FOV will overlap with the first FOV.

In a next step, the required scan depth for each scan line which has a scan angle within the planned maximum angular ranges Δϕ, Δθ of the adjusted FOV are computed. For each scan line (i.e., each scan angle θ, ϕ), the method comprises determining a distance, along a length of the line, between the ultrasound source and a boundary of the volumetric region defined previously (where this is either defined by a boundary of the anatomical structure itself (possibly plus a defined margin around it), or a shape which contains the structure, as described above).

For example, if the output of the segmentation is represented as a triangle mesh, the volumetric region might be defined so as to have a boundary which matches the shape of the defined mesh. Thus, to determine the scan depths for each scan line, the method may comprise determining all triangles of the mesh boundary structure that are intersected by a scan line and calculate the distance of the relevant intersection point. If the segmentation is instead represented as voxel mask, the method may comprise determining all voxels of the mask that are intersected by a scan line and calculating the distance along the scan line from the ultrasound source to the respective voxel (for instance either to voxel center or most distal corner of the voxel).

For a given scan line, if it intersects the volumetric region boundary at more than one point, the furthest intersection point is used. This results in a set of intersection point co-ordinates for each scan line.

By way of illustration, <FIG> shows a slice through a volumetric ultrasound dataset. The image illustrates an example set of segmentation boundaries <NUM> for the heart, and also shows a boundary of a defined volumetric region <NUM> which contains the whole of the heart.

<FIG> shows a further example, in which the anatomical object-of-interest is instead just a portion of the heart (the left ventricle). The boundaries of the whole heart <NUM> may be segmented, and a volumetric region <NUM> has then been defined which covers just the anatomical object/region of interest (i.e. the left ventricle).

As mentioned above, in some examples, the adjusted 3D FOV <NUM> includes a margin or spacing area around a detected anatomical object. The defined margin or spacing around the anatomical object may be pre-defined, it may be based on a user-input, or, if the acquired reference ultrasound data is 4D ultrasound data, then it may be determined from a detected motion pattern of the object over the series of frames. In other words, an extent of the spacing around the boundaries can be determined based on detecting a maximal extent of the object-of-interest boundary across the series of frames.

After setting the adjusted 3D FOV, new 3D ultrasound data can be acquired. This may be 4D ultrasound data comprising a series of frames of 3D ultrasound data. Areas outside of the adjusted FOV (i.e. beyond the newly set lengths/depths of the scan lines) are not scanned. In other words, each beam (scan line) is only acquired up to the designed scan line depth for that scan line. In this way, higher frame rates are enabled.

The method may further comprise controlling a display of a user interface to display a visual representation of the new acquired image data. Therefore, the adapted field of view is directly visible.

In some embodiments, the user interface may be used to generate a user alert if a currently set FOV does not cover a pre-defined anatomical object or region of interest. The user may manually trigger the FOV adjustment method to adapt the FOV to the anatomical object. If, upon execution of the method, the current FOV is in fact adequate, a hint might be provided to the user that the ultrasound transducer unit positioning needs to be adjusted.

A further aspect of the invention provides a computer program product comprising code means configured, when executed on a processor which is communicatively coupled with an ultrasound imaging apparatus, to cause the processor to perform a method in accordance with any of the examples or embodiments outlined above, or in accordance with any claim of this application.

As briefly outlined above with reference to <FIG>, another aspect of the invention provides a system <NUM> comprising: an ultrasound imaging apparatus <NUM>; and a processing arrangement <NUM> adapted to carry out a method in accordance with any of the examples or embodiments outlined above. The processor is communicatively coupled with the ultrasound imaging apparatus for receiving ultrasound image data and for communicating the adjusted scanning parameters to the ultrasound imaging apparatus.

By way of further, more detailed explanation, the general operation of an exemplary ultrasound imaging apparatus will now be described, with reference to <FIG>.

The apparatus comprises an array transducer probe <NUM> which has a transducer array <NUM> for transmitting ultrasound waves and receiving echo information. The transducer array <NUM> may comprise CMUT transducers; piezoelectric transducers, formed of materials such as PZT or PVDF; or any other suitable transducer technology. In this example, the transducer array <NUM> is a two-dimensional array of transducers <NUM> capable of scanning either a 2D plane or a three dimensional volume of a region of interest. In another example, the transducer array may be a 1D array.

The transducer array <NUM> is coupled to a microbeamformer <NUM> which controls reception of signals by the transducer elements. Microbeamformers are capable of at least partial beamforming of the signals received by sub-arrays, generally referred to as "groups" or "patches", of transducers as described in <CIT>), <CIT>), and <CIT>).

It should be noted that the microbeamformer is in general entirely optional. Further, the apparatus includes a transmit/receive (T/R) switch <NUM>, which the microbeamformer <NUM> can be coupled to and which switches the array between transmission and reception modes, and protects the main beamformer <NUM> from high energy transmit signals in the case where a microbeamformer is not used and the transducer array is operated directly by the main system beamformer. The transmission of ultrasound beams from the transducer array <NUM> is directed by a transducer controller <NUM> coupled to the microbeamformer by the T/R switch <NUM> and a main transmission beamformer (not shown), which can receive input from the user's operation of the user interface or control panel <NUM>. The controller <NUM> can include transmission circuitry arranged to drive the transducer elements of the array <NUM> (either directly or via a microbeamformer) during the transmission mode.

In a typical line-by-line imaging sequence, the beamforming system within the probe may operate as follows. During transmission, the beamformer (which may be the microbeamformer or the main system beamformer depending upon the implementation) activates the transducer array, or a sub-aperture of the transducer array. The sub-aperture may be a one dimensional line of transducers or a two dimensional patch of transducers within the larger array. In transmit mode, the focusing and steering of the ultrasound beam generated by the array, or a sub-aperture of the array, are controlled as described below.

For each line (or sub-aperture), the total received signal, used to form an associated line of the final ultrasound image, will be a sum of the voltage signals measured by the transducer elements of the given sub-aperture during the receive period. The resulting line signals, following the beamforming process below, are typically referred to as radio frequency (RF) data. Each line signal (RF data set) generated by the various sub-apertures then undergoes additional processing to generate the lines of the final ultrasound image. The change in amplitude of the line signal with time will contribute to the change in brightness of the ultrasound image with depth, wherein a high amplitude peak will correspond to a bright pixel (or collection of pixels) in the final image. A peak appearing near the beginning of the line signal will represent an echo from a shallow structure, whereas peaks appearing progressively later in the line signal will represent echoes from structures at increasing depths within the subject.

In addition, upon receiving the echo signals from within the subject, it is possible to perform the inverse of the above described process in order to perform receive focusing. In other words, the incoming signals may be received by the transducer elements and subject to an electronic time delay before being passed into the apparatus for signal processing. The simplest example of this is referred to as delay-and-sum beamforming. It is possible to dynamically adjust the receive focusing of the transducer array as a function of time.

The structural and motion signals produced by the B mode and Doppler processors are coupled to a scan converter <NUM> and a multi-planar reformatter <NUM>. The scan converter <NUM> arranges the echo signals in the spatial relationship from which they were received in a desired image format. In other words, the scan converter acts to convert the RF data from a cylindrical coordinate system to a Cartesian coordinate system appropriate for displaying an ultrasound image on an image display <NUM>. In the case of B mode imaging, the brightness of pixel at a given coordinate is proportional to the amplitude of the RF signal received from that location. For instance, the scan converter may arrange the echo signal into a two dimensional (2D) sector-shaped format, or a pyramidal three dimensional (3D) image. The scan converter can overlay a B mode structural image with colors corresponding to motion at points in the image field, where the Doppler-estimated velocities to produce a given color. The combined B mode structural image and color Doppler image depicts the motion of tissue and blood flow within the structural image field. The multi-planar reformatter will convert echoes that are received from points in a common plane in a volumetric region of the body into an ultrasound image of that plane, as described in <CIT>). A volume renderer <NUM> converts the echo signals of a 3D data set into a projected 3D image as viewed from a given reference point as described in <CIT>).

The 2D or 3D images are coupled from the scan converter <NUM>, multi-planar reformatter <NUM>, and volume renderer <NUM> to an image processor <NUM> for further enhancement, buffering and temporary storage for optional display on an image display <NUM>. The imaging processor may be adapted to remove certain imaging artifacts from the final ultrasound image, such as: acoustic shadowing, for example caused by a strong attenuator or refraction; posterior enhancement, for example caused by a weak attenuator; reverberation artifacts, for example where highly reflective tissue interfaces are located in close proximity; and so on. In addition, the image processor may be adapted to handle certain speckle reduction functions, in order to improve the contrast of the final ultrasound image.

In addition to being used for imaging, the blood flow values produced by the Doppler processor <NUM> and tissue structure information produced by the B mode processor <NUM> are coupled to a quantification processor <NUM>. The quantification processor produces measures of different flow conditions such as the volume rate of blood flow in addition to structural measurements such as the sizes of organs and gestational age. The quantification processor may receive input from the user control panel <NUM>, such as the point in the anatomy of an image where a measurement is to be made.

Output data from the quantification processor is coupled to a graphics processor <NUM> for the reproduction of measurement graphics and values with the image on the display <NUM>, and for audio output from the display device <NUM>. The graphics processor <NUM> can also generate graphic overlays for display with the ultrasound images. These graphic overlays can contain standard identifying information such as patient name, date and time of the image, imaging parameters, and the like. For these purposes the graphics processor receives input from the user interface <NUM>, such as patient name. The user interface is also coupled to the transmit controller <NUM> to control the generation of ultrasound signals from the transducer array <NUM> and hence the images produced by the transducer array and the ultrasound imaging apparatus. The transmit control function of the controller <NUM> is only one of the functions performed. The controller <NUM> also takes account of the mode of operation (given by the user) and the corresponding required transmitter configuration and band-pass configuration in the receiver analog to digital converter. The controller <NUM> can be a state machine with fixed states.

Embodiments of the invention described above employ a processing arrangement. The processing arrangement may in general comprise a single processor or a plurality of processors. It may be located in a single containing device, structure or unit, or it may be distributed between a plurality of different devices, structures or units. Reference therefore to the processing arrangement being adapted or configured to perform a particular step or task may correspond to that step or task being performed by any one or more of a plurality of processing components, either alone or in combination. The skilled person will understand how such a distributed processing arrangement can be implemented. The processing arrangement includes a communication module or input/output for receiving data and outputting data to further components.

The one or more processors of the processing arrangement can be implemented in numerous ways, with software and/or hardware, to perform the various functions required. A processor typically employs one or more microprocessors that may be programmed using software (e.g., microcode) to perform the required functions. The processor may be implemented as a combination of dedicated hardware to perform some functions and one or more programmed microprocessors and associated circuitry to perform other functions.

Claim 1:
A computer-implemented method, comprising:
obtaining reference 3D ultrasound data of an anatomical region for a first 3D field of view (<NUM>), FOV, wherein the reference ultrasound data comprises data for a series of scan lines (<NUM>), each scan line having a scan angle along a first (ϕ) and second (θ) angular scan direction, and maximum scan depth (d) along a direction of the scan line;
applying segmentation to the reference 3D ultrasound data to detect boundaries of an anatomical object-of-interest in the reference 3D ultrasound data;
defining a volumetric region (<NUM>) within the anatomical region, the volumetric region having one or more boundaries, wherein the volumetric region is defined in dependence upon the detected boundaries of the anatomical object-of-interest, and wherein the volumetric region is defined so as to fully contain the detected boundaries of the anatomical object-of-interest;
adjusting one or more scanning parameters to acquire new 3D ultrasound data with an adjusted 3D FOV (<NUM>), wherein adjusting the scanning parameters is performed in dependence upon the boundaries of the volumetric region, and wherein the adjusted 3D FOV fully encompasses the volumetric region, and wherein adjusting the scanning parameters comprises adjusting the maximum scan depth (d) of each individual scan line, such that the scan depth of each individual scan line can be modified, and
acquiring new 3D ultrasound data for the adjusted 3D FOV using the adjusted scanning parameters.