CN113658161B

CN113658161B - Method for correcting time-signal intensity curve of eye socket region

Info

Publication number: CN113658161B
Application number: CN202110975170.1A
Authority: CN
Inventors: 鲜军舫; 曲晓霞; 王倩
Original assignee: Beijing Tongren Hospital
Current assignee: Beijing Tongren Hospital
Priority date: 2021-08-24
Filing date: 2021-08-24
Publication date: 2023-09-26
Anticipated expiration: 2041-08-24
Also published as: CN113658161A

Abstract

The present application provides a method for correcting a TIC curve of an orbital region, the method may include: in the case where the eye moves with time, based on the three-dimensional segmented image for the eyeball area segmented from the original three-dimensional magnetic resonance image at the reference time point among the plurality of time points as a reference image, the three-dimensional segmented image for the eyeball area segmented from each of the original three-dimensional magnetic resonance images at the time point after the self-reference time point among the plurality of time points is rigidly registered to obtain a registered three-dimensional segmented image for the eyeball area at the time point after the reference time point; and selecting a region of interest including the lesion region at the same coordinate position from each of the three-dimensional segmented image at the reference time and the registered three-dimensional segmented image at a time point subsequent to the reference time point, and obtaining a corrected time-signal intensity curve according to gray value information within the region of interest.

Description

Method for correcting time-signal intensity curve of eye socket region

Technical Field

The present application relates to magnetic resonance image processing and, more particularly, to a method for correcting a time-signal intensity curve of magnetic resonance dynamics enhancement of an orbital region.

Background

Magnetic resonance imaging plays a very important and irreplaceable role in the diagnosis of orbital tumors and tumor-like lesions, and is a major basis for the formulation of treatment protocols and surgical designs.

The magnetic resonance dynamic enhancement scan is performed once again after intravenous injection of contrast agent. The contrast agent is injected into veins and then distributed to normal or abnormal tissues of a human body along with blood, and the blood supply amount and supply source of various tissues are different, so that the distribution amount, the distribution time and the removal speed of the contrast agent are different. The magnetic resonance contrast agent contains paramagnetic substance gadolinium, so that the time of the tissue T1 can be shortened, the signal is enhanced, the amount of gadolinium absorbed by the tissue is different, and the degree of signal enhancement is different. Some neoplastic lesions are not clearly defined during the translation and are indistinguishable from surrounding oedema, inflammatory lesions, surgical or radiation lesions, and therefore the extent of tumor invasion and post-treatment effects cannot be determined. The enhancement of the scanned tumor tissue is different from the enhancement of the inflammatory lesions and injuries of the tumor tissue, and the edema is not enhanced, so that the range, the size and the shape of the tumor can be clearly displayed.

Dynamic enhanced magnetic resonance scanning mainly reflects the distribution amount, distribution time and removal speed of contrast agent in a focus area through a time-signal intensity curve (time of intensity curve, TIC) type of dynamic-enhanced (DCE) of magnetic resonance. The TIC curve type is mainly divided into a continuous enhancement type, a platform type and an outflow type. Studies have shown that in benign lesions, 47% of the TIC curve in the focal area is continuously enhanced, 30% is plateau-type, 23% is outflow-type; 83% of malignant lesions are outflow and 17% are plateau lesions. Therefore, TIC curves play an important role in the application of identifying benign and malignant tumors of the orbit and tumor-like lesions.

Eye tumors and tumor-like lesions requiring orbital magnetic resonance scanning mainly include: melanoma, choroidal hemangioma, choroidal metastasis, retinoblastoma, choroidal osteoma, scleral choriocapillaris, intraocular ossification, intraocular lymphoma, pigment-free malignant melanoma of the choroid, uveal metastasis cancer, and uveal neurogenic tumors.

In the magnetic resonance scanning process, due to the particularity of the lesion position of the orbit, the focus area generally changes along with the eyeball movement, which causes the focus position corresponding to the selected region of interest to change, so that the TIC curve can oscillate up and down, and the type is difficult to judge.

It should be understood that this background section is provided only for enhancement of understanding of the technical content of the present application and thus the information discussed in this background section does not necessarily constitute prior art.

Disclosure of Invention

In order to solve the problem that the TIC curve is drawn incorrectly due to eyeball movement in the magnetic resonance scanning process, the application provides a correction method of the TIC curve based on the magnetic resonance dynamic enhancement of the orbit tumor and the tumor-like lesion, and the method can improve the accuracy of TIC curve type judgment.

According to an aspect of the application, a method for correcting a time-signal intensity curve of an orbital region may include: acquiring raw three-dimensional magnetic resonance images of the same eye at a plurality of time points; determining whether the eye moves over time by comparing the positions of the eye in the raw three-dimensional magnetic resonance image at a plurality of time points; in response to determining that the eye moves over time, rigidly registering the three-dimensional segmented images for the eye region segmented in the form of a rectangular cylinder in each of the original three-dimensional magnetic resonance images at a time point subsequent to the reference time point in the plurality of time points based on the three-dimensional segmented images for the eye region segmented in the form of a rectangular cylinder from the original three-dimensional magnetic resonance images at the reference time point in the plurality of time points as reference images to obtain registered three-dimensional segmented images for the eye region at a time point subsequent to the reference time point; and selecting a region of interest including the lesion region at the same coordinate position from each of the three-dimensional segmented image at the reference time and the registered three-dimensional segmented image at a time point subsequent to the reference time point, and obtaining a corrected time-signal intensity curve according to gray value information within the region of interest.

The raw three-dimensional magnetic resonance image at each point in time may comprise a two-dimensional transverse bit image comprising a first number of layers scanned perpendicular to the human body in a height direction of the human body.

Each of the three-dimensional divided image at the reference time point and the three-dimensional divided image at a time point subsequent to the reference time point may be a three-dimensional image in the form of a rectangular columnar body obtained by selecting a rectangular region corresponding to the eyeball region from two-dimensional transverse bit images having the largest eyeball shape in the two-dimensional transverse bit images of the first number of layers at the corresponding time point and then expanding the rectangular region in the height direction in the two-dimensional transverse bit images of the first number of layers.

According to another aspect of the application, a method for correcting a time-signal intensity curve for an orbital region may include: acquiring raw three-dimensional magnetic resonance images of the same eye at a plurality of time points; selecting first interested areas which comprise focus areas and are positioned at the same coordinate position from each of the original three-dimensional magnetic resonance images at a plurality of time points, and obtaining a first time-signal intensity curve according to gray value information in each first interested area; determining whether the eye moves over time based on the first time-signal strength curve; in response to determining that the eye moves over time, rigidly registering the three-dimensional segmented images for the eye region segmented in the form of a rectangular cylinder in each of the original three-dimensional magnetic resonance images at a time point subsequent to the reference time point in the plurality of time points based on the three-dimensional segmented images for the eye region segmented in the form of a rectangular cylinder from the original three-dimensional magnetic resonance images at the reference time point in the plurality of time points as reference images to obtain registered three-dimensional segmented images for the eye region at a time point subsequent to the reference time point; and selecting a second region of interest including the lesion area at the same coordinate position from each of the three-dimensional segmented image at the reference time and the registered three-dimensional segmented image at a time point subsequent to the reference time point, and obtaining a corrected time-signal intensity curve according to gray value information within the second region of interest.

Determining whether the eye is moving over time based on the first time-signal strength curve may include: determining whether the type of the first time-signal intensity curve belongs to a continuous enhancement type, a plateau type or an outflow type, if the type of the first time-signal intensity curve does not belong to the continuous enhancement type, the plateau type or the outflow type, determining that the eye moves along with time, and if the type of the first time-signal intensity curve belongs to the continuous enhancement type, the plateau type or the outflow type, determining that the eyeball does not move along with time.

According to the method of the embodiment of the application, after the eye magnetic resonance image in which the eye ball moves is corrected, the time-signal intensity curve of the dynamic enhancement of the magnetic resonance can be corrected from the nondeterminable type to the continuously enhanced type, the platform type or the outflow type.

Effects according to the embodiments are not limited to the above-exemplified matters, and further various effects are included in the present disclosure. The present disclosure will be described in detail below with reference to the attached drawings and detailed description.

Drawings

Fig. 1 shows a schematic illustration of a comparative example in the case of eye movement during a magnetic resonance scan.

Fig. 2 shows a flow chart of a method according to the application for correcting a time-signal intensity curve in the event of a movement of the eye.

Fig. 3 shows a schematic view of a segmentation process of an eyeball according to the present application.

Figure 4 shows a schematic diagram of an eye magnetic resonance image rigid registration procedure according to the application.

Fig. 5 shows a schematic diagram of a comparison of the rigid registration before and after, according to various embodiments of the application.

Fig. 6 shows a schematic diagram of the type of TIC curve before and after correction with the correction method according to the application in case of eye movement during a magnetic resonance scan.

Fig. 7 shows TIC curves before and after correction according to one specific example of an embodiment of the present application.

Fig. 8 shows a flowchart of a method for correcting a TIC curve of an orbital region according to one embodiment of the application.

Fig. 9 shows a flowchart of a method for correcting a TIC curve of an orbital region according to another embodiment of the application.

Detailed Description

Various embodiments and aspects of the application will be described with reference to details discussed below, which are illustrated in the accompanying drawings. The following description and drawings are illustrative of the application and are not to be construed as limiting the application. Numerous specific details are described to provide a thorough understanding of various embodiments of the application. In some instances, however, well-known or conventional details are not described in order to provide a concise discussion of embodiments of the present applications.

Reference in the specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment.

It should be understood that the detailed description and specific examples, while indicating the application, are intended for purposes of illustration only and are not intended to limit the scope of the application. It should be noted that the embodiments of the present application and the features of the embodiments may be combined with each other without conflict. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the various embodiments described herein can be made without departing from the scope and spirit of the disclosure.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and/or the present specification and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

As shown in fig. 1 (a), the patient's eyeball moves at different times (such as t1 and t 2) (this can be seen from the gray solid line at time t1 and the black solid line at time t 2), and the focal region moves following it, so that the TIC curve type cannot be determined. Fig. 1 (B) shows an original eye magnetic resonance image, and it should be understood that only a two-dimensional transverse position image of a certain layer is shown in the figure, but in reality, the original eye magnetic resonance image includes two-dimensional transverse position images of a plurality of layers. Fig. 1 (C) and (D) correspond to rectangular boxes of fig. 1 (B), which are enlarged images of eyeball areas at different times on the same plane, and it can be seen that the lower left corner lesion area is displaced.

As described above, since the lesion area is displaced with time, the lesion position corresponding to the selected region of interest (for example, the dotted circle box shown in (a) of fig. 1) is changed, so that the TIC curve may oscillate up and down and thus it is difficult to determine the type.

In order to solve the problem that the TIC curve is drawn incorrectly due to eyeball movement in the magnetic resonance scanning process, the application provides a correction method of the TIC curve based on the magnetic resonance dynamic enhancement of the orbit tumor and the tumor-like lesion, and the method can improve the accuracy of TIC curve type judgment. Embodiments of the present application will be described in detail below with reference to fig. 2 to 9.

In an embodiment according to the present application, the method 200 shown in fig. 2 may be performed in case it is determined that an eye movement occurs. The method 200 may include: step S210 of segmenting an eyeball area for each of the original ocular tumor magnetic resonance images (also referred to as "original three-dimensional magnetic resonance images") at all time points to obtain three-dimensional segmented images at the corresponding time points; step S220 of performing three-dimensional image registration (specifically, performing rigid registration) on the three-dimensional segmented image (also referred to as "floating image") at a time point after the reference time point based on the three-dimensional segmented image (also referred to as "reference image" or "fixed image") at the reference time point to obtain a registered three-dimensional segmented image at the time point after the reference time point; step S230, selecting a region of interest including a lesion area at the same coordinate position from each of the three-dimensional segmented image at the reference time and the registered three-dimensional segmented image at a time point subsequent to the reference time point, and obtaining a corrected time-signal intensity TIC curve according to gray value information within the region of interest.

In the above method, the reference time point indicates a time point at which the drug starts to enter the lesion area, and it appears on the image that the lesion area starts to be highlighted at the reference time point.

It should also be appreciated that although the method 200 described above is performed after the occurrence of eye movement is determined, the conditions under which the method 200 according to the present application is performed are not limited thereto. It should be appreciated that performing the method 200 after determining that an eye is moving is merely a preferred embodiment, and those skilled in the art may also increase the amount of data processing to perform the method 200 directly without determining whether an eye is moving.

The method 200 will be described in detail below in conjunction with fig. 3-7.

Fig. 3 shows a schematic view of a process of dividing an eyeball area according to the present application. The upper part of fig. 3 shows a raw three-dimensional magnetic resonance image at a certain point in time, comprising a multi-slice transverse two-dimensional image of a human body scanned perpendicularly to the height direction (z-axis direction) of the human body. The left view of the lower part of fig. 3 shows the one layer of the multi-layer cross-sectional two-dimensional images having the largest eyeball shape, in which the two-dimensional image of the eyeball area is divided in the form of a rectangular frame, that is, the right view of the lower part of fig. 3.

In the embodiment according to the present application, in the case where an eyeball of a scanned object moves while performing magnetic resonance scanning, correction of an original three-dimensional magnetic resonance image is required. However, if the original three-dimensional magnetic resonance image is directly registered, it is difficult to correct the movement of the eyeball area, and only the whole head image is corrected. In fact, since the entire head of the scanned object can be kept almost stationary (the head movement is less than 1 mm) when performing the magnetic resonance scan, in the correction method according to the embodiment of the present application, the image of the entire head is not corrected. In the correction method according to the embodiment of the present application, only the eyeball portion where the movement occurs is locally corrected.

In the embodiment according to the present application, in order to locally correct the eyeball portion, it is necessary to perform a segmentation process on the eyeball region in the original three-dimensional magnetic resonance image. In an embodiment according to the present application, a rectangular segmentation method is used to segment an eyeball area in an original three-dimensional magnetic resonance image.

Firstly, selecting a layer of transverse two-dimensional image with the maximum eyeball shape from the included layers of transverse two-dimensional images according to the original three-dimensional magnetic resonance image at each time point, selecting a rectangular area corresponding to the eyeball area, and placing a rectangular frame to obtain the coordinates of xyz in three directions. As shown in fig. 3, [ x1: x2, y1: y2,1: z_max ] in the image is selected as a new matrix, which is saved as a new gray-scale image, that is, an image after eyeball segmentation, wherein x1 and x2 are x-axis direction start-stop coordinate values, y1 and y2 are y-axis direction start-stop coordinate values, z_max represents the total number of slices in the z-axis direction (total number of layers of transverse bit two-dimensional images) and 1 and z_max represent the number of start-stop layers in the z-axis direction (height direction of the human body). For example, if there are 12 transverse bit two-dimensional images, the z-direction range is 1:12, z_max=12.

In general, the following 6 parameter values are known for the segmented eye region: 1) 2 parameters of the x-axis direction start-stop coordinate values x1 and x 2; 2) 2 parameters of the start and stop coordinate values y1 and y2 in the y-axis direction; 3) How many slices (how many layers of transverse bit two-dimensional images) are shared in the z-axis direction, namely z_max; and 4) how many phases (i.e., how many points in time) are in common.

In one specific application, the obtained DCE-MRI sequence has 32 phases; each time phase is a 12-layer transverse two-dimensional image, the acquisition Matrix (acquisition Matrix) is 200×200, and the voxels are 0.4688mm× 0.4688mm×1.8mm.

By the above-described segmentation, for the original three-dimensional magnetic resonance image at each time point, a three-dimensional segmented image in the form of a rectangular columnar body having x-axis coordinate values in the range of x1 to x2, y-axis coordinate values in the range of y1 to y2, and z-axis coordinate values in the range of 1 to z_max can be obtained.

Figure 4 shows a schematic diagram of an ocular magnetic resonance image rigid registration procedure according to the application and figure 5 shows a comparative schematic diagram before and after rigid registration according to different examples of the application.

According to an embodiment of the application, image registration is a process of spatially one-to-one mapping between voxels in one image and voxels in another image. In embodiments of the present application, rigid registration is employed considering that images at different times are of the same subject (the same eye of the same person). The elastic tool in python (a simple medical image registration tool (https:// pypi. Org/project/pyelastix /)) is used, i.e. python loads the tool at the beginning, code is importpyelastix. Rigid registration is mainly to align a floating image (moving image) onto a fixed image (fixed image) by calculating contour or gray information in both images. In one example according to the application, the function pyelastix. Register is used, the parameter settings are as follows:

params＝pyelastix.get_default_params('RIGID')

params.FixedInternalImagePixelType＝"float"

params.MovingInternalImagePixelType＝"float"

params.ResultImagePixelType＝"float"

params.MaximumNumberOfIterations＝iter_num

outputImageTMP,fieldImageTMP＝pyelastix.Register(movingImageFile,fixedImageFile,params)

as shown in fig. 4, a time point t needs to be selected in the registration process ₀ Data of (i.e., reference time point) as a reference image, i.e., fixed image, other time points (t) ₁ 、t ₂ 、…t _n-1 、t _n ) As an image to be registered, i.e., a floating image (moving image). In the upper part of fig. 4, the leftmost view is a schematic view of an eyeball image with a focus as a reference image, and the subsequent view is a view of other time points (t ₁ 、t ₂ 、…t _n-1 、t _n ) As a floating image. In the lower part of fig. 4, the diagram after the reference image shows other points in time (t ₁ 、t ₂ 、…t _n-1 、t _n ) Before and after registration, can seeThe registered position is rotated towards the eyeball position in the reference image. The process is illustrated here by using a two-dimensional map as a schematic diagram, and the actual registration process is based on three-dimensional image (three-dimensional segmented image) registration because the direction of movement of the eyeball is three-dimensional.

Rigid registration (rib) is used in the deformation method (Transform) during registration. Scaling of the affine matrix employs automatic estimation scaling, namely AutomaticScalesEstimation. The initial value of the deformation matrix uses the geometric centers of the aligned floating image and the fixed image as the initial value. Resolution parameters at registration: numberOfResolutions (int) =4. The maximum number of iterations is set to 100, iter_num=100. It should be understood that these parameters are described by way of example only and the application is not limited thereto.

Interpolation methods (interpolators) use first order B-spline interpolation (i.e., linear interpolation) (BSpline) during registration. The similarity measure (Metric) is calculated using mutual information (mutual information). The rigidly registered images are shown in fig. 5, in examples 1 and 2: the first image is an image of 3 time points before registration, and the leftmost image is a reference image; the third behavior registered image; the second row shows the difference in position change before and after registration.

It should be appreciated that the above example illustrates the process with a two-dimensional map as a schematic, and that the actual registration process is based on three-dimensional images (three-dimensional segmented images).

Fig. 6 shows a schematic diagram of the type of TIC curves before and after correction with the correction method according to the application in case of eye movement during a magnetic resonance scan, and fig. 7 shows TIC curves before and after correction according to a specific example of the application.

Fig. 6 (a) is a schematic diagram of an original TIC curve (i.e., an uncorrected TIC curve) in the case where the eyeball moves. Fig. 6 (B), (C) and (D) show that the corrected TIC curve types are continuous enhancement type, flat type and outflow type, respectively.

The region of interest (ROI) is typically placed manually when drawing the TIC curve, the placement of the ROI typically being within the focal region. In the two-dimensional plane, the ROI may be rectangular or elliptical, and the shape of the ROI is not particularly limited by the present application. It should be understood that in a three-dimensional segmented image, the ROI may be in the form of a rectangular cylinder, an ellipsoid, or may be simply a planar rectangular form.

In the left part of the diagram of fig. 7, the ROI is a rectangular region of the gray border on the lower side. In the right part of the diagram of fig. 7, the TIC curve before correction is represented by a gray curve, the curve type of which cannot be judged, and the TIC curve after correction is represented by a black curve, which belongs to the outflow type. In the TIC curve, the abscissa is time, i.e., time phase, and the ordinate is the average value of the gray values of the image in the ROI area at different time phases.

According to the embodiment of the application, after the eye magnetic resonance image is corrected, the TIC curve type is easier to judge, and the distribution quantity, the distribution time and the flow velocity of the contrast agent in the tumor area can be better analyzed, thereby being beneficial to more accurately diagnosing the eye tumor lesions.

Fig. 8 shows a flowchart of a method for correcting a TIC curve of an orbit region according to one embodiment of the present application, and fig. 9 shows a flowchart of a method for correcting a TIC curve of an orbit region according to another embodiment of the present application.

As shown in fig. 8, a method 800 for correcting a TIC curve of an orbital region according to one embodiment of the application includes: step S810, acquiring original three-dimensional magnetic resonance images of the same eye at a plurality of time points; and step S820, determining whether the eyes move with time by comparing the positions of the eyes in the original three-dimensional magnetic resonance images at a plurality of time points, if the eyes are determined to move with time, performing step S831 and step S840, otherwise performing step S832. At step S831, based on the three-dimensional segmented image segmented from the original three-dimensional resonance image at the reference time point (i.e., taking the three-dimensional image at the reference time point as the reference image), the three-dimensional segmented image segmented from the original three-dimensional resonance image at the time point after the reference time point is rigidly registered (i.e., the three-dimensional images at other time points are registered to the reference image) to obtain a registered three-dimensional segmented image at the time point after the reference time point. At step S840, a corrected TIC curve is obtained from each selected region of interest in the three-dimensional segmented image at the reference time and the registered three-dimensional segmented image at a point in time subsequent to the reference time, in accordance with gray value information within the region of interest. At step S832, first regions of interest including the lesion area at the same coordinate position are selected from each of the original three-dimensional magnetic resonance images at a plurality of time points, and a first TIC curve is obtained according to gray value information in each of the first regions of interest. It should be appreciated that in step S832, the first region of interest may be selected directly from the original three-dimensional magnetic resonance image, or may be selected from a three-dimensional segmented image segmented from the original three-dimensional magnetic resonance image using the image segmentation process described above with reference to fig. 3, which is not particularly limited in the present application.

In the embodiment shown in fig. 8, the raw three-dimensional magnetic resonance image at each point in time may comprise a two-dimensional transverse bit image comprising a first number of layers scanned perpendicular to the human body in the height direction of the human body.

In the embodiment shown in fig. 8, each of the three-dimensional divided image at the reference time point and the three-dimensional divided image at the time point subsequent to the reference time point may be, for example, a three-dimensional image in the form of a rectangular columnar body obtained by selecting a rectangular region corresponding to an eyeball region from two-dimensional cross-sectional bit images having the largest eyeball shape in the two-dimensional cross-sectional bit images of the first number of layers at the corresponding time point and then expanding the rectangular region in the height direction in the two-dimensional cross-sectional bit images of the first number of layers. The segmentation process performed to obtain a three-dimensional segmented image has been described above in connection with fig. 3 and will not be repeated here.

In the embodiment shown in fig. 8, the rigid registration may include establishing a one-to-one mapping of voxels of each of the three-dimensional segmented images at a point in time subsequent to the reference point in time with voxels in the three-dimensional segmented image at the reference point in time. In the embodiment shown in fig. 8, the rigid registration may align the three-dimensional divided image at the time point after the reference time point to the three-dimensional divided image at the reference time point according to the contour or gray-scale information of the three-dimensional divided image at the time point after the reference time point and the contour or gray-scale information of the three-dimensional divided image at the reference time point. In the embodiment shown in fig. 8, the alignment may include aligning the geometric center of the three-dimensional segmented image at a time point subsequent to the reference time point with the geometric center of the three-dimensional segmented image at the reference time point. The rigid registration has been described above in connection with fig. 4 and 5 and is not repeated here.

In the embodiment shown in fig. 8, the reference time point may be a time point indicating that the drug starts to enter the lesion area. On the image, the lesion area is highlighted starting at the reference point in time.

In the embodiment shown in fig. 8, as shown in fig. 6 and 7, the ordinate of the TIC curve represents the average gray value within the region of interest, and the abscissa of the TIC curve represents the time point. For example, in the corrected TIC curve, the ordinate represents the three-dimensional divided image at the reference time point and the average gray value within the region of interest of the registered three-dimensional divided image at the time point after the reference time point, and the abscissa represents the reference time point and the time point after the reference time point.

In the embodiment shown in fig. 8, whether or not the eyeball moves with time can be judged by the image observation position, but the present application is not limited thereto. In another embodiment of the present application, whether the eyeball moves with time can be judged through a preliminary TIC curve.

As shown in fig. 9, a method 900 for correcting a TIC curve of an orbital region according to one embodiment of the application includes: step S910, acquiring original three-dimensional magnetic resonance images of the same eye at a plurality of time points; step S920, selecting a first region of interest including a focus region at the same coordinate position from each of the original three-dimensional magnetic resonance images at a plurality of time points, and obtaining a first TIC curve according to gray value information in each first region of interest; and step S930, determining whether the eyes move with time based on the first TIC curve, if it is determined that the eyes move with time, performing step S941 and step S950, otherwise, ending the method. At step S941, based on the three-dimensional segmented image segmented from the original three-dimensional resonance image at the reference time point (i.e., taking the three-dimensional image at the reference time point as the reference image), the three-dimensional segmented image segmented from the original three-dimensional resonance image at the time point after the reference time point is rigidly registered (i.e., the three-dimensional images at other time points are registered to the reference image) to obtain a registered three-dimensional segmented image at the time point after the reference time point. At step S950, a corrected TIC curve is obtained from each selected region of interest in the three-dimensional segmented image at the reference time and the registered three-dimensional segmented image at a time point subsequent to the reference time point, in accordance with gray value information within the region of interest. It should be appreciated that in step S920, the first region of interest may be selected directly from the original three-dimensional magnetic resonance image, or may be selected from a three-dimensional segmented image segmented from the original three-dimensional magnetic resonance image using the image segmentation process described above with reference to fig. 3, which is not particularly limited in the present application.

In the embodiment shown in fig. 9, determining whether the eye is moving over time based on the first TIC curve may include: determining whether the type of the first TIC curve belongs to a continuous enhancement type, a plateau type or an outflow type; if the type of the first TIC curve does not belong to the continuous enhancement type, the platform type or the outflow type, the eye movement along with time is determined, and if the type of the first TIC curve belongs to the continuous enhancement type, the platform type or the outflow type, the eyeball does not move along with time.

Similar to the embodiment shown in fig. 8, in the embodiment shown in fig. 9, the raw three-dimensional magnetic resonance image at each point in time may comprise a two-dimensional transverse bit image comprising a first number of layers scanned perpendicular to the human body in the height direction of the human body. Each of the three-dimensional divided image at the reference time point and the three-dimensional divided image at a time point subsequent to the reference time point may be, for example, a three-dimensional image in the form of a rectangular columnar body obtained by selecting a rectangular region corresponding to an eyeball region from two-dimensional transverse bit images having the largest eyeball shape in the two-dimensional transverse bit images of the first number of layers at the corresponding time point and then expanding the rectangular region in the height direction in the two-dimensional transverse bit images of the first number of layers.

The segmentation process, rigid registration, and TIC curves have been described above in connection with fig. 3-7 and are not repeated here.

By using the method for correcting the time-signal intensity curve of the orbit region according to the embodiment of the present application, the accuracy of TIC curve type determination can be improved.

At the conclusion of the detailed description, those skilled in the art will understand that many variations and modifications may be made to the preferred embodiments without substantially departing from the principles of the present application. Accordingly, the disclosed preferred embodiments are used in an illustrative and descriptive sense only and not for purposes of limitation.

Claims

1. A method for correcting a time-signal intensity curve of an orbital region, comprising:

acquiring raw three-dimensional magnetic resonance images of the same eye at a plurality of time points;

determining whether movement of the eye occurs over time by comparing the positions of the eye in the raw three-dimensional magnetic resonance images at the plurality of time points;

in response to determining that the eye moves over time, rigidly registering the three-dimensional segmented images for the eye region segmented in rectangular columns in each of the original three-dimensional magnetic resonance images at time points subsequent to the reference time point in the plurality of time points based on the three-dimensional segmented images for the eye region segmented in rectangular columns from the original three-dimensional magnetic resonance images at reference time points in the plurality of time points as reference images to obtain registered three-dimensional segmented images for the eye region at time points subsequent to the reference time point; and

and selecting a region of interest including a focus region at the same coordinate position from each of the three-dimensional segmented image at the reference time and the registered three-dimensional segmented image at a time point after the reference time point, and obtaining a corrected time-signal intensity curve according to gray value information in the region of interest.

2. The method according to claim 1,

wherein the raw three-dimensional magnetic resonance image at each point in time comprises a two-dimensional transverse bit image comprising a first number of layers scanned perpendicular to the human body in the height direction of the human body, and

wherein each of the three-dimensional divided image at the reference time point and the three-dimensional divided image at a time point subsequent to the reference time point is a three-dimensional image in the form of the rectangular columnar body obtained by selecting a rectangular region corresponding to the eyeball region from two-dimensional transverse bit images having a maximum eyeball shape in the two-dimensional transverse bit images of the first number of layers at the corresponding time point and then expanding the rectangular region in the height direction in the two-dimensional transverse bit images of the first number of layers.

3. The method of claim 1, wherein the rigid registration comprises establishing a one-to-one mapping of voxels of each of the three-dimensional segmented images at a point in time subsequent to the reference point in time with voxels in the three-dimensional segmented image at the reference point in time.

4. The method of claim 1, wherein the rigid registration aligns the three-dimensional segmented image at a point in time after the reference point in time to the three-dimensional segmented image at the reference point in time according to contour or grayscale information of the three-dimensional segmented image at the point in time after the reference point in time and contour or grayscale information of the three-dimensional segmented image at the reference point in time.

5. The method of claim 4, wherein the aligning comprises aligning a geometric center of the three-dimensional segmented image at a point in time subsequent to the reference point in time with a geometric center of the three-dimensional segmented image at the reference point in time.

6. The method of claim 1, wherein the reference time point represents a time point at which a drug starts entering a focal region, and the focal region appears graphically highlighted starting at the reference time point.

7. The method of claim 1, wherein an ordinate of the corrected time-signal intensity curve represents a three-dimensional segmented image at the reference point in time and an average gray value within the region of interest of the registered three-dimensional segmented image at a point in time subsequent to the reference point in time, and an abscissa of the corrected time-signal intensity curve represents the reference point in time and a point in time subsequent to the reference point in time.

8. A method for correcting a time-signal intensity curve of an orbital region, comprising:

selecting first regions of interest including focus regions at the same coordinate positions from each of the original three-dimensional magnetic resonance images at the plurality of time points, and obtaining a first time-signal intensity curve according to gray value information in each first region of interest;

determining whether the eye moves over time based on the first time-signal strength curve;

and selecting a second region of interest including a focus region at the same coordinate position from each of the three-dimensional segmented image at the reference time and the registered three-dimensional segmented image at a time point after the reference time point, and obtaining a corrected time-signal intensity curve according to gray value information in the second region of interest.

9. The method of claim 8, wherein determining whether the eye is moving over time based on the first time-signal strength TIC curve comprises:

determining whether the type of the first time-signal strength curve belongs to a continuously enhanced, plateau or outflow type,

if the type of the first time-signal intensity curve does not belong to the continuously enhanced, plateau or outflow type, it is determined that the eye moves with time,

if the type of the first time-signal intensity curve belongs to the continuous enhancement type, the plateau type or the outflow type, determining that the eyeball does not move along with time.

10. The method according to claim 8, wherein the method comprises,