JP2010514486A - Medical imaging system - Google Patents

Abstract

The present invention relates to a medical imaging system. First, the determination of the boundaries of at least one region of the feature of interest is performed. Second, a confidence level representing the determination of the boundary of at least one region of the feature of interest is calculated. Third, information is displayed that represents at least one region of the feature of interest, wherein the associated boundary has a confidence level below a predetermined threshold.

Description

  The present invention relates to medical imaging systems and corresponding methods. The present invention finds its use especially in the area of ultrasound imaging.

  Known medical imaging systems take a sequence of 3D images of features of interest in the body, such as the left ventricle, and display them on the screen to determine the borders of such features of interest Display errors on the screen, visually detect boundary determination errors on the screen, and manually correct such errors. To visually detect such errors, the user selects a region of interest on the 3D sequence and sees all the 2D images that make up the 3D image. Then, when the user sees an error in the boundary determination, the user can manually correct it.

  One drawback of the imaging system is that the user of the system needs to extract all 2D corresponding images if he wants to see and correct if necessary all the boundaries of the regions of the feature of interest in the 3D sequence. Yes, a single 3D image consists of about 100 2D images, which means that the user loses. The user needs to see about 3000 images during the heart cycle, which is very laborious.

  It is an object of embodiments of the present invention to propose a system that saves the user time and to assist the user in correcting the boundaries of the regions of the feature of interest.

To this end, the system has, in one embodiment, control means for controlling the following operations:
Automatic determination of the boundaries of at least one region of a feature of interest in a sequence of images of a body part,
A calculation of a confidence level representing the determination of the boundary of at least one region of the feature of interest;
Display of information representing at least one region of the feature of interest, wherein the associated boundary has a confidence level lower than a predetermined threshold.

  Although the invention is suitable for sequences of images having multiple images, such as a sequence of images representing the entire cardiac cycle, the invention may be used with a sequence of images consisting of a single image. . Therefore, the expression “sequence of images” should be understood as meaning also “at least one image”.

  Displaying information that represents the boundary along with its confidence level allows the user to save time. This is because the user automatically has to focus attention, because it sees boundaries that may need to be corrected.

  According to one non-limiting embodiment, the displayed information is a map of confidence levels each associated with the boundaries of multiple regions of the feature of interest. It allows the user to have a global view of the region of features of interest and its associated confidence level.

  According to one non-limiting embodiment, the control means allows control of the display of second information representing at least one region of the feature of interest, the boundary of which has been corrected. It allows users to follow their modifications.

  According to a non-limiting embodiment, the control means allows control of automatic display of a 2D slice view of a low confidence region based on the information.

The present invention is also a method of medical imaging comprising:
Automatically determining the boundaries of at least one region of a feature of interest in a sequence of images of a body part;
Calculating a confidence level representing a determination of the boundary of at least one region of the feature of interest;
Displaying information representing at least one region of the feature of interest, wherein the associated boundary has a confidence level lower than a predetermined threshold;
Regarding the method.

  Finally, the present invention is a computer program product having program instructions, wherein the program instructions are program instructions for executing the method when the program is executed by a processor. Regarding products.

  These and other aspects of the invention will be apparent from and elucidated with reference to the embodiments described hereinafter.

  The present invention will now be described in more detail, by way of non-limiting example, with reference to the accompanying drawings.

FIG. 2 is a schematic diagram of a system according to an embodiment of the invention cooperating with a probe. FIG. 2 is a schematic view of a feature of interest, such as the left ventricle, from which a sequence of images is acquired via a system according to an embodiment of the invention. FIG. 3 is a first view of a segmentation of a feature of interest, such as the left ventricle, that can be used by a system according to an embodiment of the invention. FIG. 4 is a second diagram of a segmentation of a feature of interest, such as the left ventricle, that can be used by a system according to an embodiment of the invention. FIG. 3 is a display showing a feature of interest, such as the left ventricle, with a bordered region having a low confidence level performed by a system according to an embodiment of the invention. FIG. 4 is a display illustrating the boundaries of several regions of a feature of interest, such as the left ventricle, performed by a system according to an embodiment of the invention. FIG. 4 is a first display of a map of confidence levels associated with various regions of a feature of interest, such as the left ventricle, performed by a system according to an embodiment of the invention. FIG. 5 is a second display of a map of confidence levels associated with various regions of a feature of interest, such as the left ventricle, performed by a system according to an embodiment of the invention. FIG. 3 illustrates a method for medical imaging according to an embodiment of the present invention.

  A system SYS according to an embodiment of the invention is described in FIG.

  The system SYS works with an array of transducers TAR and its associated electronic circuitry, which together form the probe PRB.

The system SYS has a controller CTRL that controls the following actions:
・ Acquisition of sequence SQ of images of body parts;
Automatic determination of the boundary B of at least one region RI of the feature of interest (FI) in the sequence SQ of the image of the body part;
Calculation of a confidence level CL representing the determination of the boundary associated with the boundary B of at least one region RI of the feature FI of interest;
Display of information IN representing at least one region RI of the feature FI of interest and having an associated boundary with a confidence level CL lower than a predetermined threshold TH.

  The system SYS further comprises a screen SCR and a user interface M_USER, optionally displaying a sequence SQ of acquired images, such as an LCD screen. The system SYS may include a memory MEM for storing the acquired image I.

  In an embodiment, the controller CTRL is further configured to control the display of the sequence of images SQ and the automatic display of the 2D slice view of the unreliable region RI based on the information IN.

  Note that the controller CTRL includes a microprocessor that can be pre-programmed by instructions or can be programmed by a user of the system SYS, for example via the interface M_USER.

  Note that image I is a 3D gray level image that can be decomposed into 2D slices, typically referred to as an MPR “Multiplanar Reconstruction” view.

  Such a system SYS can be used in ultrasound, especially when organ measurements such as the left ventricle LV need to be performed. As shown in FIG. 2, the heart is composed of left ventricle LV and right ventricle RV, aorta AO, left atrium LA and right atrium RA, and arterial blood goes from left ventricle LV to aorta AO, while right ventricle RV is right Recall that the venous blood received from the atrium RA is put into the pulmonary artery. Since the manner in which the left ventricle LV is functioning indicates the health of the heart, the left ventricle LV is particularly focused when using the ultrasound imaging system SYS.

  Referring now to FIG. 3, the inner wall of the left ventricle LV is the standard American Heart Association Cardiac Imaging Committee of Clinical Cardiology. Can be segmented into 17 segments SG as defined in “Standardized Myocardial Segmentation and Nomenclature for Tomographic Imaging of the Heart”. Thus, FIG. 3 is a representation on a circumferential polar plot of such a segmentation, called a “bulls eye”, and FIG. 4 is a 3D view of such a segmentation. The 17 segments are named according to the standard. For example, segment 17 identifies the apex, and the location of the anterior wall in the lower and middle cavities. Segments 1 and 7 include the basal anterior and mid-anterior. ). Such segmentation can be used by an ultrasound imaging system as described below.

  To obtain an image of the left ventricle LV, in one non-limiting embodiment, at the apex near the heart, the ultrasound probe PRB is applied to the patient's body, and the imaging system SYS performs the operations described below.

1) Acquisition of a three-dimensional image sequence SQ The user of the system SYS moves the probe PRB over the part of the body of interest, here the heart, more specifically the left ventricle.

  A sequence of gray level 3D images is acquired. The image sequence SQ is displayed on the screen SCR. Note that a sequence SQ of 3D images is executed at about 20 Hz, and one sequence SQ is composed of about 20 3D images. Note that in order to see the entire volume of the left ventricle LV, image acquisition is performed during 4 heart cycles, and a quarter of the left ventricle LV is acquired in each heart cycle. This 3D acquisition allows to obtain several volumes.

  It should be noted that acquisition of the image sequence SQ is not essential to the present invention. In the embodiment of FIG. 1, the controller CTRL also controls this acquisition, but this acquisition may be controlled by a separate system. For example, the acquisition is performed by an acquisition system, and the sequence of images controls the automatic determination of the boundaries of at least one region RI of the feature of interest FI in the sequence of images SQ, for example by wireless connection, and the Calculating a confidence level associated with the boundary of at least one region of the feature representing the determination of the boundary, wherein the confidence level of the at least one region of the feature of interest is lower than a predetermined threshold May be sent to a system having means for displaying information representing a region having

2) Automatic determination of the boundary B of at least one region RI of the feature of interest FI in the sequence SQ of the image of the part of the body. Determining the position of B is typically allowed by a method called segmentation of the left ventricle LV. Such segmentations are, for example, literature, O. G´erard, A. Collet-Billon, J.-M. Rouet, M. Jacob, M. Hradkin (Fradkin), “Efficient Model-Based Quantification of Left Ventricular Function in 3-D Echocardiography”, IEEE Bulletin on Medical Imaging (IEEE Transactions on medical imaging), Volume 21, Issue 9, September 2002.

  Note that the region RI is composed of at least one voxel and may be composed of a plurality of voxels.

  The automatic determination may be based on, for example, measurement of left ventricular LV movement. In this case, the automatic determination may be based on feature characterization in the image such as edge based on gradient, density level, texture tracking. Good.

  Note that the type of feature characterization used is selected according to the anatomical model functions of the regions of the left ventricle LV found on the image sequence SQ.

  Of course, any method for automatic determination of the boundary B of the region RI of the feature FI of interest in the image I may be used.

  When the boundary B is estimated, the temporal evolution of the surface of the left ventricle LV can be determined, for example, by acquiring parametric images IP based on velocity information of various regions RI.

  Color is associated with the velocity information of the regions RI of the left ventricle LV in order to be displayed as a parametric image IP on the screen SCR. For example, red can be used when the region contracts, while blue can be used when the region relaxes. If the left ventricle LV is functioning correctly, the entire left ventricle LV should be displayed in red when contracted and blue when relaxed. Otherwise, the left ventricle LV is displayed partly in red and the other part in blue. The color is not uniform. This means that some regions RI contract or relax later than other regions RI because the velocity peak varies from region to region. Thus, surface development indicates whether there is any asynchrony in the left ventricle LV.

  Of course, information other than speed, such as deformation, displacement or acceleration information, can also be used for the parametric image IP.

  Parametric images can be acquired, for example, from documents, A. Stoylen, C. B. Inggul, H. Torp, "Strain and strain rate parametric imaging. From three standard apical planes. A new method for post processing to 3- / 4-dimensional images: A new method for post processing to 3- / 4-dimensional images from three standard apical planes. Preliminary data on feasibility, artefact and regional dyssynergy visualization ”,“ Cardiovascular Ultrasound 2003 ”, 1:11 doi: 10.1186 / 1476-7120-1-11, Trondheim, Norway , Well documented in the Department of Circulation and Medical Imaging, School of Medicine, Norwegian University of Science and Technology.

3) Calculation of the confidence level CL representing the determination of the boundary B of at least one region RI of the feature FI of interest. The quality of the ultrasound acquisition image is eg the patient's echogenicity, line density, limited field of view ... The confidence level CL is associated with the determination of the boundary B of the various regions RI of the left ventricle LV, depending on several factors such as. This confidence level is used to determine boundary B, as described above, such as gray level for density level, gradient level for gradient-based edges, and threshold for global / local statistics for texture tracking. Depends on local estimation of feature characterization.

  The calculation of the confidence level is performed for each image I of the acquired image sequence SQ.

  Such confidence levels associated with the measurement are, for example, document, R. Wang, H. J. Zhang, Y. Q. Zhang, "built for compressed areas A confidence measure based moving object extraction system built for compressed domain, IEEE International Symposium on Circuits and Systems, May 2000 It is well described in ISCAS2000, Geneva, Switzerland, 28-31.

4) Display of information representing a region that has at least one region RI of the feature FI of interest and the associated boundary B has a confidence level CL lower than a predetermined threshold TH. Even if the threshold TH is 60%, for example. Good. Of course, any other value of the threshold may be defined.

  The display is performed for each image I of the sequence of acquired images SQ. For example, the information IN is a 3D image of the left ventricle LV, and colors the regions RI as shown in FIG. Each color is associated with a value of confidence level CL. Regions RI1 and RI2 have a low confidence level CL. Of course, other colors may be used for other regions with an associated confidence level greater than the threshold TH.

  Thus, a map of confidence levels CL respectively associated with the boundaries B of the plurality of regions RI of the feature of interest FI having a high confidence level or a low confidence level can be displayed.

  Thus, using the displayed information IN, the user can manually verify or correct the boundary B having a low confidence level CL in the region RI.

  In order for the user to manually modify the boundary B, the user interface M_USER has a manual editing tool.

5) Automatic display of 2D slice view of low confidence region based on information IN To help the user manually correct the boundary of the low confidence region, the system SYS is based on the confidence map MP The 3D image may be automatically sliced at a low reliability position. For example, as shown in FIG. 6, an MPR “multi-section reconstruction” 2D slice view that passes through the unreliable part of the image, along with a color indicating the region to be reviewed again (eg, regions RI1, RI2) It may be automatically displayed to the user. More than one MPR view may be displayed. For example, three vertical planes slicing through the region of interest RI may be displayed.

  If the region RI indicated by the system SYS is of interest to the user, the user may correct the boundary. At that time, the system SYS automatically moves the region of interest RI to the region having the second lowest reliability. Otherwise, it indicates to the system that the user wants to move to the next area with low confidence. It will continue like that.

  In another embodiment, the user may himself choose an MPR view with the use of an orthoviewer P, as shown in FIG. The user may use the ortho viewer P to move it until it sees a 2D slice of the region of interest, such as a 2D slice for regions RI1 and RI2.

  Automatic alignment to the unreliable region RI allows the user to be guided in user corrections. This saves the user time.

6) Update Information IN and Display Whenever a user corrects boundary B, the information can be updated to indicate the user's correction and apply a reliable confidence level CL in such correction. Different colors may be used to indicate to the user which parts are effectively covered by their correction.

  Therefore, the original confidence information IN called intrinsic may always be displayed, and updated updated information INu called extrinsic is displayed in parallel. May be. Therefore, this exogenous reliability information INu stores all areas and degrees of user interaction along the history.

  Thus, the exogenous reliability information INu allows the user to display where the user has made corrections. With this information, changes in the density of interventions (for example, there are many interventions in one part of the image but none in other parts) can be a warning sign to explore unmodified areas. I will.

  Note that after the correction is performed by the user, the calculation of the local estimate of the confidence level in step 3) may be performed again. It allows the user to correct the estimation by incorporating user corrections.

7) Merging the parametric image IP with the reliability information of the original IN and the exogenous INu As a final result, as shown in FIG. 7 and FIG. And a final parametric image IF that is a merge between the original IN and the exogenous INu reliability information.

  FIG. 7 is a 2D representation of the final parametric image IF. Regions with low confidence levels have been deleted from the parametric image IP. Thus, the user can see which segments SG of the parametric representation are covered by, for example, a region with a low confidence level or a plurality of regions RI.

  FIG. 8 is a 3D representation of the final parametric image IF in which the low confidence level region has been erased from the parametric image IP.

  Thus, the resulting parametric image IF allows to identify and show areas where the final measurement (wall dyssynchrony) is truly reliable.

  Note that the intrinsic and exogenous reliability information here is a combination of all intrinsic and exogenous information for each image I.

  In order for the user to obtain the final parametric image IF, the user interface M_USER has sufficient means, for example a button.

  FIG. 9 illustrates a method for medical imaging according to an embodiment of the present invention, illustrating various operations controlled by the system SYS.

  The above-described embodiments are illustrative rather than limiting of the invention, and those skilled in the art can design many alternative embodiments without departing from the scope of the invention as defined by the appended claims. It should be noted that it will be. The example used has been described for an ultrasound echocardiographic sequence of images, but of course can be extended to any image obtained for other imaging modalities.

  In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word “comprising” and “including” does not exclude the presence of elements or steps other than those listed in any claim or specification as a whole. Reference to an element in the singular does not exclude a plurality of references to such elements, and conversely, a reference to an element in the singular does not exclude singular references to such elements.

  The present invention may be implemented by hardware having several different elements and by a suitably programmed computer. In the device claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

Claims (6)

A medical imaging system having control means, wherein the control means operates as follows:
Automatic determination of the boundaries of at least one region of a feature of interest in a sequence of images of a body part,
A calculation of a confidence level representing the determination of the boundary of at least one region of the feature of interest;
Display of information representing at least one region of the feature of interest, the associated boundary having a confidence level lower than a predetermined threshold;
To control the system.   The system of claim 1, wherein the displayed information is a map of confidence levels each associated with a boundary of a plurality of regions of a feature of interest.   The system according to claim 1, wherein the control means allows control of the display of second information representing at least one region of the feature of interest, the boundary of which has been corrected.   The system according to claim 1, wherein the control means allows control of automatic display of a 2D slice view of a region of low confidence based on the information (IN). A medical imaging method:
Automatically determining the boundaries of at least one region of a feature of interest in a sequence of images of a body part;
Calculating a confidence level representing a determination of the boundary of at least one region of the feature of interest;
Displaying information representing at least one region of the feature of interest and an associated boundary having a confidence level lower than a predetermined threshold;
Method.   A computer program comprising program instructions for performing the method of claim 5 when said program is executed by a processor.

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