Method of acquiring length from image representing cross-section of volume of tissue

Abstract

In a method of acquiring a first length from a first two-dimensional image (71) representing a cross-section of a three-dimensional tissue volume at a first time and a second length from a second two-dimensional image (81) representing a cross-section of the three-dimensional tissue volume at a second time, a first point (61.1) and a second point (61.2) are marked in the first two-dimensional image (71). Next, third data relating to the first two-dimensional image (71) is acquired. A fourth point (61.4) and a fifth point (61.5) are marked in the second two-dimensional image (81), and sixth data relating to the second two-dimensional image (81) is acquired. Using the first, the second, the fourth and the fifth points (61.1, 61.2, 61.4, 61.5) of the mark and the third and the sixth data, it is checked whether the positions and orientations of the first two-dimensional image (71) and the second two-dimensional image (72) are sufficiently matched. If the positions and directions of the first two-dimensional image and the second two-dimensional image match sufficiently, the first length is determined from the marked first point, second point (61.1, 61.2) and third data, and the second length is determined from the marked fourth point, fifth point, and sixth data. In particular, the third data and the sixth data are obtained by marking a third point (61.3) and a sixth point (61.6), respectively. The third point (61.3) and the sixth point (61.6) may correspond to physiological markers visible in the first image (71) and the second image (81), respectively.

Description

Technical Field

[0001] The present invention relates to a method of obtaining a first length from a first two-dimensional image representing a cross section of a three-dimensional tissue volume at a first time, and obtaining a second length from a second two-dimensional image representing a cross section of the three-dimensional tissue volume at a second time. Background Art

[0002] Data obtained from medical imaging can be used in a variety of applications to examine or monitor the characteristics or development of physiological conditions. These images can be obtained using imaging methods such as ultrasound, magnetic resonance imaging, X-rays, or optical coherence tomography (OCT). In many cases, determining the dimensions of identifiable structures in the images is crucial for further evaluation of the physiological condition. Typically, these dimensions are characterized by one or more lengths.

[0003] Patent PCT / EP 2022 / 072593, currently pending by the same applicant, describes a method that involves measuring a first length at a first time point and a second length at a second time point. This method is used to detect changes in the elasticity of a tissue structure over time.

[0004] Typically, it is necessary to compare corresponding results obtained from two or more images taken at different points in time and / or under different external or internal influences (e.g., different external pressures, different blood circulation or respiratory cycle phases, etc.). Generally, such a comparison is meaningful only if the tissue volume represented by the first image and the tissue volume represented by the second image, as well as the measurement modality (e.g., the direction of the axis along which the length value is determined), are sufficiently matched. Summary of the Invention

[0005] The object of the present invention is to create a method related to the initially mentioned technical field, which allows for a reliable comparison of length values ​​obtained from two or more two-dimensional images representing sections of a three-dimensional tissue volume.

[0006] The solution of the invention is specified by the features of claim 1. According to the invention, the method comprises the following steps:

[0007] a) marking a first point in the first two-dimensional image;

[0008] b) marking a second point in the first two-dimensional image;

[0009] c) acquiring third data related to the first two-dimensional image;

[0010] d) marking a fourth point in the second two-dimensional image;

[0011] e) marking a fifth point in the second two-dimensional image;

[0012] f) acquiring sixth data related to the second two-dimensional image;

[0013] g) checking whether positions and orientations of the first two-dimensional image and the second two-dimensional image sufficiently match using the marked first point, second point, fourth point, and fifth point and the third data and sixth data; and

[0014] If the positions and orientations of the first two-dimensional image and the second two-dimensional image sufficiently match;

[0015] (h) determining a first length based on the marked first point, second point, and third data; and

[0016] i) Determine the second length based on the marked fourth point, fifth point and sixth data.

[0017] The user may manually mark the first point, the second point, the fourth point, and the fifth point using a suitable user interface.

[0018] Marking points can be achieved by directly marking point-like locations (e.g., pixels in the image data) in the first or second two-dimensional image, respectively. The marking step can be facilitated by providing a cursor, crosshairs, or similar visual aid. All or some of the points can be marked indirectly by marking extended one-dimensional structures and / or two-dimensional structures, for example:

[0019] - a line or arrow, where a single point is mapped to a specified position on the line or arrow, such as a center point or a specified endpoint, or two points are mapped to two specified positions, in particular two endpoints;

[0020] - arcs, where a single point is mapped to a specified location on the arc, such as the center point on the arc, the center of rotation of the arc, or a specified endpoint, or two points are mapped to two specified locations, in particular the two endpoints of the arc;

[0021] - Shapes such as circles, triangles, rectangles, etc., where a single point maps to a specified location, such as the center point of a circle, triangle, or rectangle or a specified corner of a polygon, where two points map to the center and another specified location or two specified locations on the perimeter, or where three points map to the center and / or other specified locations, particularly locations on the perimeter.

[0022] The marked points on the first two-dimensional image and / or the second two-dimensional image can be obtained by calculations based on the marker structure or based on more than one marker structure (same or different types). These calculations may involve determining the center or symmetry point of a line or area, calculating an average value, etc.

[0023] To increase the accuracy of the marking step, a magnified view of the image can be displayed.

[0024] The invention includes variants of the method in which more than two (or more than three) points are marked for each image, as well as variants in which more than two images acquired at different points in time are marked. In principle, the number of marked points does not need to be the same for all processed images.

[0025] Depending on the properties being inspected, the two (or more) images may be acquired minutes, hours, days, or even weeks or months apart. Marking the points and acquiring the third and / or sixth data can occur simultaneously with capturing the corresponding images, or at a later stage before or after capturing the other images. However, to allow for immediate user feedback, it is preferred that marking the fourth and fifth points and acquiring the sixth data occur approximately simultaneously with capturing the second two-dimensional image. Immediate user feedback allows further image data to be captured until a second image is acquired that meets the matching criteria for the first image.

[0026] The method of the present invention ensures that two or more images representing the same tissue volume used to examine a condition meet certain matching criteria. These two or more images can be taken consecutively during a single measurement session, or they can be taken separately during separate time periods ranging from minutes to months. In the first instance, the two or more images may represent conditions under different external or internal influences, such as applied external pressures, or different phases of the blood circulation or respiratory cycle. In the second instance, the images can be used to monitor the temporal progression of a condition affecting the tissue volume.

[0027] In particular, the matching criteria should be chosen in a way that ensures that relevant attributes and their variations between images can be reliably obtained from the images and / or sensor data. This is particularly important for images taken in independent time periods, involving independent placement of the imaging equipment and possibly different operators.

[0028] The matching criteria or associated thresholds may differ between comparing two images acquired during the same measurement period and comparing two images acquired during different measurement periods. For example, if relative attributes (e.g., ratios of distance values) are obtained during each different measurement period, then a close match of site and imaging conditions may be more critical for two or more images from a single measurement period used to obtain relative attributes than for images from different periods.

[0029] The method of the present invention is particularly suitable for processing B-ultrasound images, but is also applicable to various other imaging modalities, including X-ray, OCT and MRI.

[0030] In an embodiment of the present method, at least one of the first, second, fourth, and fifth points is automatically labeled based on a structure imaged in the corresponding image. Automatic labeling can be based on known digital image processing techniques, including machine learning-based methods. The structure can be a readily recognizable landmark, such as an interface between layers of imaged tissue, blood vessels, bone, and the like.

[0031] All of the mentioned points can be automatically marked, particularly if they are associated with automatically identifiable structures in the image data. In one variation, only some of the points are automatically marked, where, for example, the second point is automatically marked based on the manual marking of the first point, and the fourth point is automatically marked based on the manual marking of the third point. After the automatic marking of one or more points, the operator may be asked for confirmation. The operator is then given the opportunity to confirm the automatic marking or to manually modify the marking or some of the markings.

[0032] In a preferred embodiment of the method, the third data is obtained by marking a third point in the first two-dimensional image, and the sixth data is obtained by marking a sixth point in the second two-dimensional image.

[0033] Likewise, the third and sixth points can be manually marked, with the same options as described above with respect to the first, second, fourth and fifth points. The third and sixth points can be obtained in a single marking step together with the first and / or second point or the fourth and / or fifth point, respectively, for example by marking an extended one-dimensional or two-dimensional structure.

[0034] Likewise, the third and sixth points can be automatically labeled using the techniques described above with respect to the first, second, fourth, and fifth points.

[0035] In a preferred embodiment, the third and sixth points are automatically marked, while the first, second, fourth, and fifth points are manually marked. In this case, the third point can be automatically defined and / or marked taking into account the marked first and second points, while the sixth point can be automatically defined and / or marked taking into account the marked fourth and fifth points. In this case, displaying the third or sixth point on the corresponding image is not mandatory but is only used for internal purposes. Nevertheless, in many cases, it is useful to display the points marked by the fully automated process so that the user can monitor the process.

[0036] Nevertheless, in this case, the manual marking step of the first, second, fourth, and fifth points can also be assisted based on image processing or segmentation. For example, this may include the step of providing suggestions for the positions of the first, second, fourth, and fifth points for the operator to confirm (or possibly change).

[0037] Several criteria can be used to check whether the positions and orientations of the first two-dimensional image and the second two-dimensional image sufficiently match. One criterion involves intensity or grayscale values, i.e., in the checking step, the intensity or grayscale value of the area where the third marker point is located is compared with the intensity or grayscale value of the area where the sixth marker point is located. If the difference exceeds a certain threshold, the images will be considered as not matching. This area may be as small as a single pixel at the location of the marker point, or preferably include an area around the marker point. The intensity or grayscale values ​​of the points in this area can be suitably averaged, for example using a weighted average, where the weight of the pixel decreases as the distance from the corresponding marker point increases.

[0038] Another criterion is based on data from a position sensor, particularly one integrated into an imaging device, particularly a handheld imaging probe. In this case, the third data is obtained by the position sensor measuring the first position of the image sensor when capturing the first two-dimensional image, and the sixth data is obtained by the position sensor measuring the second position of the image sensor when capturing the second two-dimensional image. It is worth noting that the second image can be acquired using the same imaging device as the first image, or using a different imaging device (thus, the sixth data will be acquired by a different position sensor).

[0039] In particular, the first position is a first inclination and the second position is a second inclination, wherein the inclination is preferably a two-dimensional inclination or a three-dimensional inclination, which can be represented by two or three Euler angles, respectively.

[0040] Instead of or in addition to the inclination, the first position may be a first position relative to the tissue, in particular relative to the patient's body surface.Preferably, the position is measured in two directions, for example in an XY Cartesian coordinate system.

[0041] In a preferred embodiment, an optical sensor is used to track the position of a handheld device (i.e., an ultrasound probe) guided over the surface of the patient's body. The sensor may include a light source (e.g., an infrared laser diode) and an image sensor (e.g., a CCD sensor), similar to an optical computer mouse device. Such a position sensor is compact, reliable, and capable of producing accurate results, particularly with respect to relative motion of the handheld device relative to the body surface, as long as the device (and the sensor) are in contact with the body surface. The computational load is significantly reduced compared to tracking based on image data. Furthermore, even if the image data represents a single slice extending along the imaging array, the optical sensor is able to track the position not only along that direction of extension, but also in a direction parallel to the direction of extension.

[0042] Based on the position data, processing (and comparing) views relating to substantially different imaging planes may be avoided.

[0043] In other variations of the method of the present invention, position data (particularly location data) can be used to generate three-dimensional data. This data may include three-dimensional tissue imaging volume data. Alternatively or additionally, the extension of tissue structures (e.g., compartments) can be tracked along the path of travel of the imaging probe. Based on this detection, for example, the maximum extension along a predetermined direction can be automatically determined.

[0044] During a single measurement session, sensors can be used to track the motion of the imaging device to detect motion associated with compromised image quality and / or matching of images captured consecutively during the measurement session. For example, if a measurement session requires capturing two or more images at different values ​​of external pressure applied by the imaging device to the examined body part, movement along the longitudinal axis of the device is acceptable, while other movements, such as sliding that moves the measurement part, tilting that changes the measurement axis, and rotation that changes the imaging plane, should be minimized. Therefore, if unacceptable movement is detected from the position data, a warning is issued to the operator. The warning may be accompanied by instructions to support the operator in correcting the position and / or orientation of the imaging device, such as arrows indicating the direction (and possibly the degree) of correction, particularly to minimize errors due to suboptimal positioning during periods of increasing external pressure. The warning and / or indication may be provided via visual, audible, and / or tactile information provided directly on the probe and / or the user interface for displaying and labeling images. In the latter case, the information may be displayed within and / or alongside the live image. Generally speaking, the visual indication may be a light signal, a color change, a graphic symbol (such as an arrow or a line), a numerical value, or the like.

[0045] The position data recorded during one or more measurement sessions can be used to provide a (summary) report to the operator, in particular in order to improve the operator's operating accuracy in future measurement sessions, where the accuracy may be particularly related to the positioning of the probe and / or the movement of increasing external pressure.

[0046] Alternatively or additionally, relative distortion of the imaging planes can be detected based on the image data itself, for example using speckle tracking techniques. If a vector representing the distortion can be obtained from the position data and / or the image data, one or both images can be corrected to allow for a meaningful comparison. In these cases, the two images are classified as mismatched only if correction is not possible or would result in an intolerable increase in the margin of error.

[0047] Another criterion involves the geometric relationship between the marker points and the third and sixth data. In this case, during the inspection step, at least one first reference angle is determined based on the first and second marker points and the third data, and at least one second reference angle is determined based on the fourth and fifth marker points and the sixth data. The first and second reference angles are then compared. Again, the reference angles indicate the orientation of the imaging plane. Furthermore, a significant mismatch in these angles may indicate other issues with the comparability of the two images.

[0048] Another geometric criterion relates to length. In this case, during the inspection step, at least one first reference length is determined based on the first marker, the second marker, and the third data, and at least one second reference length is determined based on the fourth marker, the fifth marker, and the sixth data. The first and second reference lengths are then compared. If the positions of the markers, the properties of the third and sixth data, and the reference lengths are appropriately selected, these reference lengths will correlate to geometric relationships that are substantially constant within a given tissue volume. In this case, if the reference lengths obtained from the first and second images differ significantly, this indicates a mismatch between the images.

[0049] In some embodiments, the first length represents the distance between the first point and the second point, the second length represents the distance between the fourth point and the fifth point, the first length is normalized based on the third data, and the fourth length is normalized based on the sixth data.

[0050] Thus, a consistent imaging ratio can be ensured, which is particularly important when determining absolute values ​​from two images. As described above, the normalization can be based on a length obtained from the two points and further data (e.g., another marker point) and / or an angle obtained from these points and further data that may indicate a distortion between the imaging planes.

[0051] Preferably, during the capture of the second two-dimensional image, candidate images for the first two-dimensional image and the second two-dimensional image are displayed to the operator to assist in capturing the second two-dimensional image. In particular, the candidate images for the second two-dimensional image represent the most recently captured image data ("live view"). This allows for an immediate side-by-side comparison of the second image with the first image, facilitating the capture of a matching image.

[0052] Particularly preferably, the first and second marked points, as well as a geometric object representing the third data, are displayed together with the first two-dimensional image. In particular, if the third data is a point, the geometric object may be a direct representation of the point. If the fourth and fifth points (and possibly the sixth point) are manually marked in the second image, the display of the markings in the first image will assist the operator and reduce the risk of incorrect markings.

[0053] In a preferred embodiment, the fourth point, the fifth point, and a geometric object representing the sixth data are marked in the candidate image of the second two-dimensional image, and a verification result and / or an intermediate result based on the marked first point, second point, fourth point, and fifth point and the third data and sixth data are displayed together with the first two-dimensional image. If the sixth data is a point, the geometric object may be a direct representation of the point.

[0054] This allows for an iterative search process when taking a second image, for example, to correctly position the imaging probe. Positioning can be supported by displaying appropriate information based on the points and / or intermediate results based on further data and verification. Appropriate information can be displayed using arrows, gauges, or other elements.

[0055] In some embodiments, in addition to the first marker point, the second marker point, the fourth marker point, and the fifth marker point and the third data and the sixth data, seventh data can be obtained from a position sensor at the first position where the image sensor measures the first two-dimensional image, and eighth data can be obtained from a position sensor at the second position where the image sensor measures the second two-dimensional image, wherein the seventh data and the eighth data are used to check whether the positions and directions of the first two-dimensional image and the second two-dimensional image are sufficiently matched and / or to determine the first length and / or to determine the second length.

[0056] In particular, the first position is a first inclination and the second position is a second inclination, wherein the inclination is preferably a two-dimensional inclination or a three-dimensional inclination, which can be represented by two Euler angles or three Euler angles, respectively.

[0057] Instead of or in addition to the inclination, the first position may be a first position relative to the tissue, in particular relative to the patient's body surface.Preferably, the position is measured in two directions, for example in an XY Cartesian coordinate system.

[0058] In a preferred embodiment, an optical sensor is used to track the position of a handheld device (i.e., an ultrasound probe) guided over the surface of the patient's body. The sensor may include a light source (e.g., an infrared laser diode) and an image sensor (e.g., a CCD sensor), similar to an optical computer mouse device. Such a position sensor is compact, reliable, and capable of producing accurate results, particularly with respect to relative motion of the handheld device relative to the body surface, as long as the device (and the sensor) are in contact with the body surface. The computational load is significantly reduced compared to tracking based on image data. Furthermore, even if the image data represents a single slice extending along the imaging array, the optical sensor is able to track the position not only along that direction of extension, but also in a direction parallel to the direction of extension.

[0059] Additional verification and / or correction can be performed using additional marker points and data obtained from the position sensor.This embodiment of the method of the present invention can be combined with any of the optional features described above, involving embodiments in which the third and sixth points are marked in the first and second two-dimensional images, respectively.

[0060] Further advantageous embodiments and combinations of features result from the following detailed description and the entirety of the claims.

[0061] BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings used to illustrate the embodiments are as follows:

[0063] Figure 1 is a flow chart of a method for processing a two-dimensional image representing a three-dimensional tissue cross-section according to the present invention;

[0064] Figure 2 a, b are schematic diagrams of two embodiments of an imaging device having a position sensor suitable for use in the method;

[0065] Figure 3 a, b are schematic diagrams of measurement periods using an imaging device;

[0066] Figure 4a - c is an image representing a cross section of a three-dimensional tissue volume under different external pressures, wherein the marking points are related to the lengths and anatomical landmarks to be determined;

[0067] Figure 5a - c is an image representing a cross section of a three-dimensional tissue volume under different external pressures, wherein the marker points are related to the lengths and anatomical landmarks to be determined, including reference angles; and

[0068] Figure 6a ,b is a part of the graphical user interface of the imaging device, which displays the results of the previous measurement and the current measurement, including the quality assessment of the current measurement.

[0069] In the figures, the same components are given the same reference numerals.

[0070] Preferred embodiments

[0071] Figure 1 is a flow chart of a method for processing a two-dimensional image representing a three-dimensional tissue cross section according to the present invention. The embodiment described relates to a sequence of two images of the same tissue volume acquired at different external pressures. In this embodiment, the images are obtained from an ultrasound imaging device that provides B-ultrasound images, such as Figure 2 As shown in a and 2b. Figure 2In the first embodiment shown in Figure a, a probe 1 includes an ultrasound array 2 for transmitting and receiving ultrasound waves 8 in a known manner. A flexible membrane 3 is provided on the surface of the probe 1 that contacts the subject's skin surface 9, defining a fluid chamber 4. A pressure sensor 5 is provided for measuring the pressure within the fluid chamber 4. A corresponding device is described in the pending application PCT / EP2022 / 079972 by the same applicant.

[0072] Furthermore, the probe 1 is provided with a position sensor, namely an accelerometer 6. The accelerometer 6 can determine, in particular, the orientation of the probe 1 in space, namely the three Euler angles α, β and γ.

[0073] exist Figure 2 In the second embodiment shown in FIG. 2 , a probe 101 includes an ultrasound array 102 for transmitting and receiving ultrasound waves 108 in a known manner. A flexible membrane 103 is provided on the surface of the probe 101 that contacts the subject's skin surface 9 . This membrane 103 defines a fluid chamber 104. A pressure sensor 105 is provided for measuring the pressure within the fluid chamber 104. A corresponding device is described in the pending application PCT / EP 2022 / 079972 by the same applicant.

[0074] In addition, the probe 101 is provided with a position sensor, namely an optical sensor 106, which includes an infrared laser source for illuminating the area of ​​the skin surface 9 below the probe 101 and a CCD sensor for imaging the area. Based on the CCD image, the movement of the probe 101 relative to the skin surface 9 in both the X and Y directions can be identified.

[0075] Further embodiments of the probe include an accelerometer and an optical sensor, which are capable of determining the position and orientation of the probe.

[0076] Thus, a first image is acquired using probe 1, 101 (step 10.1). The first image is pre-processed on probe 1 and / or processing and display device 101 connected to probe 1 (step 11.1). The pre-processed image is then displayed on a display (step 12.1). Steps 10.1-12.1 are repeated in a loop, continuously updating the displayed image. Once the operator selects to mark the first point (step 13.1), the most recent image will be used for subsequent steps, and no new images will be acquired and / or displayed.

[0077] The marking of the first point (step 13.1) is achieved by the operator manually moving a cursor on the image using a suitable input device (e.g., a touch screen, a touch pad, cursor keys, etc.) and confirming the specific cursor position by a corresponding operation (e.g., pressing a designated position on the touch screen, pressing a confirmation button, or the like). The confirmed first marking point is displayed on the image, for example, using a crosshair (see Figure 4aand description below).

[0078] Once the operator manually marks the first point, the system automatically determines and displays suggested locations for the second and third points (steps 14.1 and 15.1). The suggested locations are determined by processing the image data representing the first image based on the location of the first point and the anatomical structures identified in the image data. This process is described in more detail below with reference to FIG4.

[0079] The suggested positions are displayed on the image along with the first marker point. The operator is then asked to confirm the suggestion or adjust the placement of the suggested positions (step 16.1). Again, this is done using a suitable input device. Once the operator considers all positions correct, they confirm their selection. The positions of the first, second, and third points are now saved along with the image data representing the first image and potentially further data such as a timestamp and the pressure reading of the pressure sensor 5 at the time the first image was acquired.

[0080] The operator is now asked to adjust the modality of image acquisition, in particular to increase the external pressure applied to the skin surface 9 (step 20).

[0081] Once the modality has been successfully adjusted, a second image can be acquired using the probe 1, 101 (step 10.2). The process is the same as that for acquiring the first image, i.e., the second image is pre-processed (step 11.2) and displayed on the monitor (step 12.2). Steps 10.2-12.2 are repeated in a loop to continuously update the displayed image.

[0082] Once the operator selects to mark the fourth point (step 13.2), subsequent steps will use the most recently acquired image, and no new images will be acquired and / or displayed. Based on the position of the first point in the first image, and possibly also based on the positions of the second and third points in the first image, and the image data representing the second image, a proposed position for the fourth point is determined and displayed on the second image. The operator can now confirm the proposed position or move the fourth point before confirming it.

[0083] Once the location of the fourth point has been confirmed, the system automatically determines and displays suggested locations for the fifth and sixth points (steps 14.2, 15.2). The suggested locations are determined by processing the image data representing the second image based on the location of the fourth point (which may be the location of the first, second, and / or third points) and the anatomical structures identified in the image data. The suggested locations are displayed on the image along with the fourth marker point. The operator is then asked to confirm the suggestion or adjust the placement of the suggested locations (step 16.2). Once the operator is satisfied that all locations are correct, they confirm their selections.

[0084] Next, reference data is generated based on the positions of the first to third points, and comparison data is generated based on the positions of the fourth to sixth points (step 30). The reference data is compared with the comparison data (step 31). If the comparison indicates a sufficient match between the first and second images and / or the markers in the first and second images, the positions of the fourth, fifth, and sixth points are stored along with the image data representing the second image and potentially further data (e.g., a timestamp and the pressure reading of the pressure sensor 5 at the time of acquisition of the second image). If the comparison indicates an insufficient match between the first and second images, the acquisition and marking of the second image are repeated (steps 10.2 et seq.).

[0085] Once the data associated with the two matching images is obtained, the length can be determined based on the positions of the first and second marker points, as well as the fourth and fifth marker points. This is described in more detail below with reference to FIG4. The determined length is saved along with other data associated with the first and second images.

[0086] Figure 3 is a schematic diagram of a measurement period using an imaging device. Figure 3 (a) shows the positioning of the probe 1, 101 relative to the subject's skin surface 9 when acquiring the first image. With the probe 1 of the first embodiment, the orientation in space is determined by the accelerometer 6 and saved together with the image data representing the first image (and further data as described above). Figure 3 As shown in (b), when a second image is acquired in the same measurement sequence, the accelerometer 6 continuously tracks the orientation of the probe 1. As soon as the current orientation differs from the saved orientation by more than a certain threshold, a warning is displayed on the display, and the fourth and subsequent points cannot be marked until a sufficient matching orientation of the probe 1 is achieved. In addition to the warning, further information can be displayed to support the operator in finding the previous orientation (e.g., an arrow indicating that a change of direction is required in a certain direction).

[0087] For the probe 101 of the second embodiment, the optical sensor 106 continuously determines and tracks the position of the probe 101 relative to the skin surface 9 throughout the measurement sequence. If the displacement of the probe 101 during the sequence exceeds a certain limit, a warning is displayed, and further measurements are allowed only when the probe 101 is in its previous position during the first measurement (or multiple previous measurements). In addition to the warning, further information can be displayed to support the operator in finding the previous position (e.g., an arrow indicating that a change of direction is required).

[0088] During the measurement period, further checks can also be performed based on the position data. For example, the acceleration and / or velocity of the probe 1 can be monitored during the measurement period, and if they exceed certain limits, a warning can be issued.

[0089] Figure 4a -c is an image representing a cross section of a three-dimensional tissue volume at different external pressures, with marker points associated with the lengths and anatomical landmarks to be determined.

[0090] Figure 4a represents a first image taken at a first point in time. In the described embodiment, FIG4 shows tissue including the anterior tibial compartment 51, which is covered by the superficial myofascia 52. Behind the anterior tibial area 51, the tibia 53 and the interosseous membrane 54 can be seen. For the sake of simplicity, only the skin surface 9, the interfaces between the above-mentioned structures, namely the interface 56 between the superficial myofascia 52 and the anterior tibial compartment 51, the interface 57 between the anterior tibial compartment 51 and the interosseous membrane 54, and the edge 58 of the tibia 53 are shown in FIG4-6. In practice, a pre-processed B-ultrasound image will be displayed, and if necessary, the interfaces or edges can be identified by image processing based on the brightness values ​​of the pixels.

[0091] Figure 4a Three points are marked in the first image shown, including a first point 61.1 on the skin surface 9, which is shown as a crosshair. A second point 61.2 is marked where the axis passing through the first point 61.1 intersects the edge 58 of the tibia 53, and the marking of the second point 61.2 is again shown as a crosshair. A third point 61.3 is marked where the edge 58 of the tibia 53 intersects the interface 57 between the anterior tibial compartment 51 and the interosseous membrane 54. This is an anatomical landmark that can be marked easily and reproducibly. The marking of the third point 61.3 is shown as a box. The markings have been made according to Figure 1 The image data were obtained using the procedure described in

[15] .

[0092] Figure 4b , represents a second image taken at a second point in time. The tissue volume represented generally corresponds to the volume represented by the first image, however, the external pressure applied to the subject's skin surface 9 has increased, and therefore the compressible structures in the volume, namely the anterior tibial compartment 51, the superficial myofascia 52, and the interosseous membrane 4, are compressed. Again, three points are marked, including a fourth point 61.4 on the skin surface 9, a fifth point 61.5 where an axis passing through the fourth point 61.4 intersects the edge 58 of the tibia 53, and a sixth point 61.6 representing the location where the edge 58 of the tibia 53 intersects the interface 57 between the anterior tibial compartment 51 and the interosseous membrane 54. Again, these markings have been made according to Figure 1 The image data were obtained using the procedure described in

[15] .

[0093] Figure 4c represents another second image taken at a second time point, wherein the external pressure on the skin surface 9 increases. Figure 4bThe orientation, scale, and cuts are different compared to the image shown. Three points are again marked, including a fourth point 62.4 on the skin surface 9, a fifth point 62.5 where the axis passing through the fourth point 62.4 intersects the edge 58 of the tibia 53, and a sixth point 62.6 representing the intersection of the edge 58 of the tibia 53 and the interface 57 between the anterior tibial compartment 51 and the interosseous membrane 54. Again, these marks have been based on Figure 1 The image data were obtained using the procedure described in

[15] .

[0094] exist Figure 4c middle, Figure 4b The axis between the fourth point 61.4 and the fifth point 61.5 defined in is shown as a dotted line. Figure 4b as well as Figure 4a Obviously, if one wants to determine the length between the fourth point 61.4 and the fifth point 61.5, for example in order to compare this length with the length between the first point 61.1 and the second point 61.2 in the first image, then from Figure 4c The measurement results from the marked position will be better than those from Figure 4b The measurement results at the location marked in are worse. Therefore, Figure 4c The tag in should be declared invalid and another tagging and / or acquisition cycle should be started.

[0095] Combine Figure 5a -c describes possible methods for evaluating the quality of the second image. These figures are essentially the same as Figure 4a Corresponding to -c, but adds a reference angle. Figure 5a Reference angle 63.1 in the first image shown is the angle between an axis passing through first point 61.1 and second point 61.2 and a line connecting second point 61.2 and third point 61.3. The value of reference angle 63.1 is determined to be 114.8°. Simultaneously, the distance l1 between second point 61.2 and third point 61.3, expressed in units related to image size, is determined to be 43.3% of the image width.

[0096] exist Figure 5b In the second image shown, the corresponding comparison angle 63.2 is determined to be 114.0°, and the distance l2 between the fifth point 61.5 and the sixth point 61.6 is determined to be 46.5% of the image width.

[0097] exist Figure 5c In the second image shown, the corresponding comparison angle 64.2 is determined to be 120.3°, and the distance l3 between the fifth point 62.5 and the sixth point 62.6 is determined to be 39.6% of the image width.

[0098] When the general Figure 5b or Figure 5cWhen comparing the second image shown with the first, the first step is to compare the comparison angle with the reference angle. Large deviations between the angles indicate that the length being determined does not lie along the same axis and / or at the same location in the tissue. If the deviation exceeds a certain threshold, such as 1.5%, the second image is deemed insufficiently high quality and requires re-acquisition.

[0099] In the second step, if the angle comparison result is satisfactory, the length measurement in the second image can be normalized using the comparison between the comparison length and the reference length. In this embodiment, the comparison length is 7.4% greater than the reference length. Therefore, assuming isotropic image scaling, the distance measured between the fourth point 61.4 and the fifth point 61.5 will be scaled by a factor of 0.931 to compensate for the scaling difference. Further thresholds may be present for the comparison between the reference length and the comparison length to discard images with scaling differences exceeding a certain limit. In this case, even if the angle comparison is satisfactory, the acquisition may have to be repeated due to the excessive scale difference.

[0100] Figure 6a 、 6b A portion of a graphical user interface of an imaging device is shown, displaying the results of previous and current measurements, including a quality assessment of the current measurement.

[0101] The graphical user interface includes a first display area 70 that displays a first B-ultrasound image taken at a first time point, representing a tissue volume at a first external pressure value, which in the illustrated embodiment is 10 mmHg. The graphical user interface also includes a second display area 80 that displays a second ultrasound image taken at a second time point subsequent to the first time point, representing a substantially identical tissue volume at a second external pressure value, which in the illustrated embodiment is 80 mmHg. In both images, points 61.1...5 have been manually and / or automatically labeled, as described above in conjunction with FIG. 4 .

[0102] Figure 6a An embodiment is shown in which the second image 81 meets predetermined matching criteria with the first image 71. Therefore, the second image 81 indicated by the check mark 86 above the second display area 80 is accepted and the distance between the fourth point 61.4 and the fifth point 61.5 is determined and displayed.

[0103] Figure 6bAn embodiment is shown in which second image 82 does not meet the predetermined matching criteria with first image 71. Clearly, the axis with marker points 64.4 and 64.5 is located at a different position than the axis connecting marker points 61.1 and 61.2 in the first image. In this embodiment, even the sixth point cannot be marked because the corresponding anatomical landmark is not within the acquired image. Therefore, second image 82 is rejected, as indicated by a cross mark 87 above second display area 80. Therefore, the acquisition of the second image is repeated.

[0104] The present invention is not limited to the above-described embodiments. Specifically, the validity of the second image can be assessed based on a combination of multiple criteria, including, in particular, comparison results between reference and comparison geometrical properties (e.g., angles, lengths, or length ratios), measurements performed by sensors such as position sensors, and other properties obtained from image data processing.

[0105] The marking process may be different from that described above. In some embodiments, all points are manually marked, while in other embodiments, the marking process can be fully automatic without requiring user confirmation.

[0106] In summary, the present invention provides a method for reliably comparing length values ​​obtained from two or more two-dimensional images representing a cross-section of a three-dimensional tissue volume.

Claims

1. A method for obtaining a first length from a first two-dimensional image representing a cross section of a three-dimensional tissue volume at a first time, and obtaining a second length from a second two-dimensional image representing a cross section of the three-dimensional tissue volume at a second time, comprising the following steps: a) marking a first point in the first two-dimensional image; b) marking a second point in the first two-dimensional image; c) acquiring third data related to the first two-dimensional image; d) marking a fourth point in the second two-dimensional image; e) marking a fifth point in the second two-dimensional image; f) acquiring sixth data related to the second two-dimensional image; g) checking whether the positions and directions of the first two-dimensional image and the second two-dimensional image sufficiently match using the marked first point, the second point, the fourth point, and the fifth point and the third data and the sixth data; and If the positions and orientations of the first two-dimensional image and the second two-dimensional image sufficiently match; (h) determining the first length based on the marked first point, the second point, and the third data; as well as i) determining the second length based on the marked fourth point, the fifth point and the sixth data.

2. The method according to claim 1, characterized in that At least one of the first point, the second point, the fourth point, and the fifth point is automatically marked based on a structure imaged in a corresponding image.

3. The method according to claim 1 or 2, characterized in that The third data is obtained by marking a third point in the first two-dimensional image, and the sixth data is obtained by marking a sixth point in the second two-dimensional image.

4. The method according to claim 3, characterized in that At least one of the third point and the sixth point is automatically marked based on a corresponding image of the imaged structure.

5. The method according to claim 4, characterized in that The third point and the sixth point are automatically marked, whereas the first point, the second point, the fourth point, and the fifth point are manually marked.

6. The method according to any one of claims 3 to 5, characterized in that In the checking step, the intensity or grayscale value of the area where the third marking point is located is compared with the intensity or grayscale value of the area where the sixth marking point is located.

7. The method according to claim 1 or 2, characterized in that The third data is obtained by a position sensor that measures the first position, in particular the first inclination and / or position, of the image sensor when taking the first two-dimensional image, and the sixth data is obtained by a position sensor that measures the second position, in particular the second inclination and / or position of the image sensor when taking the second two-dimensional image.

8. The method according to any one of claims 1 to 7, characterized in that In the checking step, at least one first reference angle is determined based on the first marking point, the second marking point and the third data, and at least one second reference angle is determined based on the fourth marking point, the fifth marking point and the sixth data, and then the first reference angle and the second reference angle are compared.

9. The method according to any one of claims 1 to 8, characterized in that In the checking step, at least one first reference length is determined based on the first marking point, the second marking point and the third data, and at least one second reference length is determined based on the fourth marking point, the fifth marking point and the sixth data, and then the first reference length and the second reference length are compared.

10. The method according to any one of claims 1 to 9, characterized in that The first length represents the distance between the first point and the second point, the second length represents the distance between the fourth point and the fifth point, the first length is normalized based on the third data, and the fourth length is normalized based on the sixth data.

11. The method according to any one of claims 1 to 10, characterized in that During the process of capturing the second two-dimensional image, candidate images of the first two-dimensional image and the second two-dimensional image are displayed to an operator to assist in capturing the second two-dimensional image.

12. The method according to claim 11, characterized in that The first marker point, the second marker point, and a geometric object representing the third data are displayed together with the first two-dimensional image.

13. The method according to claim 11 or 12, characterized in that The fourth point, the fifth point and the geometric object representing the sixth data are marked in the candidate image of the second two-dimensional image, and the verification results and / or intermediate results based on the marked first point, the second point, the fourth point and the fifth point and the third data and the sixth data are displayed together with the first two-dimensional image.

14. The method according to any one of claims 3 to 6, characterized in that The seventh data is obtained from a position sensor measuring the first position, in particular the first inclination and / or position, of the first two-dimensional image captured by the image sensor, and the eighth data is obtained from a position sensor measuring the second position, in particular the second inclination and / or position, of the second two-dimensional image captured by the image sensor, wherein the seventh data and the eighth data are used to check whether the positions and directions of the first two-dimensional image and the second two-dimensional image are sufficiently matched and / or for determining the first length and / or for determining the second length.

Images