CN111161369A - Image reconstruction storage method and device, computer equipment and storage medium - Google Patents
Image reconstruction storage method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to an image reconstruction storage method, an image reconstruction storage device, a computer device and a storage medium. The method comprises the following steps: acquiring scanning data and two different reconstruction parameters of an object to be detected; respectively reconstructing the data of the scanning data by adopting the two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, the first sequence of images and the second sequence of images each including a region of interest; fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes the region of interest. By adopting the method, the problems of image reconstruction precision and data storage space can be considered.
Description
Technical Field
The present application relates to the field of image storage technologies, and in particular, to an image reconstruction storage method and apparatus, a computer device, and a storage medium.
Background
The CT imaging of computed tomography is widely used for fine detection of various parts of a patient's body because of its high image resolution, and after the patient is scanned by a CT apparatus, an image can be reconstructed according to the scanned data.
In general, although a smaller reconstruction interval is used to reconstruct an image and a finer information representation of a scanned region can be obtained, a data storage space is also increased during storage, and a larger reconstruction interval is used to reconstruct an image and the data storage space can be reduced during storage, but when a patient is diagnosed at a later stage using the stored image, missed diagnosis and misdiagnosis of a lesion region are likely to be performed.
Therefore, the technology has the problem that the image reconstruction precision and the data storage space are difficult to be considered simultaneously.
Disclosure of Invention
In view of the foregoing, it is desirable to provide an image reconstruction storage method, an image reconstruction storage apparatus, a computer device, and a storage medium that can achieve both image reconstruction accuracy and data storage space.
An image reconstruction storage method, the method comprising:
acquiring scanning data and two different reconstruction parameters of an object to be detected;
respectively reconstructing data of the scanning data by adopting two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than that of the second sequence of images, and the first sequence of images and the second sequence of images both comprise a region of interest;
fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes a region of interest.
An image reconstruction storage apparatus, the apparatus comprising:
the acquisition module is used for acquiring the scanning data of the object to be detected and two different reconstruction parameters;
the reconstruction module is used for respectively reconstructing the data of the scanning data by adopting the two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, the first sequence of images and the second sequence of images each including a region of interest;
the fusion module is used for fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes the region of interest.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring scanning data and two different reconstruction parameters of an object to be detected;
respectively reconstructing the data of the scanning data by adopting the two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, the first sequence of images and the second sequence of images each including a region of interest;
fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes the region of interest.
A readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring scanning data and two different reconstruction parameters of an object to be detected;
respectively reconstructing the data of the scanning data by adopting the two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, the first sequence of images and the second sequence of images each including a region of interest;
fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes the region of interest.
According to the image reconstruction storage method, the image reconstruction storage device, the computer equipment and the storage medium, the scanning data and two different reconstruction parameters of the object to be detected are obtained, the scanning data are respectively subjected to data reconstruction by adopting the two different reconstruction parameters, a first sequence image and a second sequence image are obtained, the resolution of the first sequence image is higher than that of the second sequence image, both the first sequence image and the second sequence image comprise the region of interest, a part of slice images in the first sequence image and a part of slice images in the second sequence image are subjected to fusion processing, a third sequence image is obtained, and the third sequence image is stored and comprises the region of interest. In the method, the finally stored third sequence image is obtained by fusing a part of slice images in the high-resolution sequence image and a part of slice images in the low-resolution sequence image, so that the third sequence image can retain high-resolution information about a focus region, that is, the reconstruction accuracy of the focus region of the image can be ensured to be higher, the focus region of a patient can be analyzed and processed in the later period, and the low-resolution information except the focus region can be retained, that is, a part of data storage space can be saved, and therefore, the method can take account of the problems of the image reconstruction accuracy and the data storage space to a certain extent.
Drawings
FIG. 1 is a diagram illustrating an internal structure of a computer device according to an embodiment;
FIG. 2 is a flow chart illustrating an exemplary method for storing reconstructed images;
FIG. 3 is a flowchart illustrating an image reconstruction and storage method according to another embodiment;
FIG. 4a is a flowchart illustrating an image reconstruction and storage method according to another embodiment;
FIG. 4b is a diagram illustrating an image fusion process, according to an embodiment;
FIG. 5 is a flowchart illustrating an image reconstruction and storage method according to another embodiment;
FIG. 6 is a block diagram of an image reconstruction storage apparatus according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
At present, the incidence of lung cancer is higher and higher, the threat to human health is also higher and higher, and most of the lung cancer is difficult to find malignant lung nodules in the lung, so that more and more hospitals adopt Computed Tomography (CT) to detect lung nodules of patients so as to improve the detection accuracy and speed of the patients. When utilizing CT to detect the patient at present, mostly adopt multilayer spiral CT to scan the patient, after the scanning, generally can set for fixed reconstruction interval and rebuild data, but to a lung CT scan, every patient's thin layer data all has several hundred broken sheets formation of image basically, if whole-body CT scans, the data bulk will be bigger, just so need have great data storage space and visit bandwidth, if for practicing thrift storage space, carry out the great layer thickness of low resolution setting to CT data, the interlamellar spacing (be great reconstruction interval) is rebuild, little focus detail information on patient CT data is lost easily or expresses unclear, will lead to the doctor when examining the focus like this, the condition of missed diagnosis or misdiagnosis appears. Therefore, embodiments of the present application provide an image reconstruction storage method, an image reconstruction storage apparatus, a computer device, and a storage medium, which are intended to solve some of the above problems.
The image reconstruction and storage method provided by the embodiment of the application can be applied to a computer device, the computer device can be a part of a medical imaging device, and can also be an external computer device matched with the medical imaging device, the computer device can be a terminal, such as a notebook computer, a desktop computer, an industrial computer, and the like, and the internal structure diagram of the computer device can be as shown in fig. 1. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement an image reconstruction storage method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 1 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
The execution subject of the embodiments of the present application may be an image reconstruction storage device or a computer device, and the following embodiments will be described with the computer device as the execution subject.
In an embodiment, an image reconstruction storage method is provided, and the embodiment relates to a specific process of reconstructing two images with different resolutions according to different reconstruction parameters and fusing partial slice images in the two images with different resolutions for storage. As shown in fig. 2, the method may include the steps of:
s202, scanning data of the object to be detected and two different reconstruction parameters are obtained.
The reconstruction parameters may include a reconstruction interval and other parameters, such as a reconstruction layer thickness, a reconstruction resolution, and the like; the two different reconstruction parameters may include a first reconstruction parameter and a second reconstruction parameter, where the first reconstruction parameter and the second reconstruction parameter are different reconstruction parameters. In addition, the scan data may be data obtained after scanning the object to be detected with a scanning apparatus, and the scanning apparatus may be a Computed Tomography (CT) apparatus.
Specifically, when or before the object to be detected is detected, the scanning device may be used to scan the object to be detected to obtain the scanning data, and then the scanning data is transmitted to the computer device, so that the computer device may obtain the scanning data of the object to be detected. Meanwhile, before the computer device reconstructs the scanning data, different reconstruction parameters can be preset.
S204, respectively carrying out data reconstruction on the scanning data by adopting two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, both the first sequence of images and the second sequence of images comprising a region of interest.
The region of interest may be a focal region, such as a lung of a human body, a lung nodule, a heart of a human body, a heart disease focus of a human body, a kidney stone, and the like; in addition, there may be one or more regions of interest.
Specifically, after obtaining the scan data and two different reconstruction parameters (including a first reconstruction parameter and a second reconstruction parameter), the computer device may reconstruct the scan data by using the first reconstruction parameter to obtain a first sequence of images, and reconstruct the scan data by using the second reconstruction parameter to obtain a second sequence of images, where each sequence of images includes at least one slice image; meanwhile, the resolution of the first sequence of images obtained here is higher than that of the second sequence of images; here, the first reconstruction parameter may be considered as a reconstruction parameter corresponding to the first sequence image, and the second reconstruction parameter may be considered as a reconstruction parameter corresponding to the second sequence image. Secondly, here both the first sequence of images and the second sequence of images comprise a region of interest.
For example, when the helical CT scan is finished, the two-dimensional image can be reconstructed from any point on the Z-axis, and the scan data can be used repeatedly, and a plurality of sequences can be reconstructed according to the reconstruction interval (the distance between the centers of the adjacent images reconstructed by the helical CT in the direction of the longitudinal axis), for example: the scanning range is 100mm, the collimation width is 10mm, if the reconstruction interval is 10mm, 10 images similar to the conventional tomography scanning are obtained, if the reconstruction interval is 5mm, 20 images with the thickness of 10mm layers are obtained, and in the same scanning range, the smaller the reconstruction interval is, the larger the number of reconstructed slice images is, and the higher the resolution is. Therefore, two sequence images can be reconstructed by setting two different reconstruction intervals according to the scan data, for example, a first sequence image can be set to be a smaller reconstruction interval to reconstruct a higher resolution sequence image, and a second sequence image can be set to be a larger reconstruction interval to reconstruct a lower resolution sequence image.
S206, fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes a region of interest.
Optionally, the certain rule may be that a part of the slice image corresponding to the region of interest in the first sequence image and a part of the slice image except for the region of interest in the second sequence image are fused to obtain a third sequence image; optionally, a part of slice images in the first sequence image except the region of interest and a part of slice images in the second sequence image corresponding to the region of interest may be fused to obtain a third sequence image; optionally, a part of the slice images corresponding to the region of interest in the first sequence of images and a part of the slice images corresponding to the region of interest in the second sequence of images may be fused to obtain a third sequence of images, which may be other cases, and this embodiment is not particularly limited to this. However, the embodiment mainly adopts that the partial slice images corresponding to the region of interest in the first sequence image and the partial slice images except for the region of interest in the second sequence image are fused to obtain the third sequence image.
In addition, the fusion processing here may be to place the partial slice images in the first sequence of images and the partial slice images in the second sequence of images in a null sequence according to their respective positional correspondences, so as to form a new sequence of images, i.e., a third sequence of images. The third sequence image obtained here includes both a partial slice image of the high-resolution first sequence image and a partial slice image of the low-resolution second sequence image, so that when the third sequence image is stored, the first sequence image and the second sequence image do not need to be stored completely, and only a partial image of the high-resolution sequence image and a partial image of the low-resolution sequence image are needed, so that on one hand, the data storage space can be reduced, and on the other hand, when data is analyzed in the future, not only can an accurate analysis result be obtained through the stored partial high-resolution information, but also more comprehensive analysis can be performed through the stored low-resolution information, that is, the reconstruction accuracy of the data can also be ensured.
Specifically, after obtaining the first sequence image and the second sequence image, the computer device may select a part of slice images in the first sequence image and a part of slice images in the second sequence image according to a certain rule, and fuse the two images to obtain a third sequence image, and store the third sequence image, so as to subsequently call the third sequence image to perform analysis processing on data of the region of interest, and the like.
In the image reconstruction storage method, scanning data and two different reconstruction parameters of an object to be detected are obtained, data reconstruction is respectively carried out on the scanning data by adopting the two different reconstruction parameters to obtain a first sequence image and a second sequence image, the resolution of the first sequence image is higher than that of the second sequence image, both the first sequence image and the second sequence image comprise an interested region, a part of slice images in the first sequence image and a part of slice images in the second sequence image are fused to obtain a third sequence image, and the third sequence image is stored and comprises the interested region. In the method, the finally stored third sequence image is obtained by fusing a part of slice images in the high-resolution sequence image and a part of slice images in the low-resolution sequence image, so that the third sequence image can retain high-resolution information about a focus region, that is, the reconstruction accuracy of the focus region of the image can be ensured to be higher, the focus region of a patient can be analyzed and processed in the later period, and the low-resolution information except the focus region can be retained, that is, a part of data storage space can be saved, and therefore, the method can take account of the problems of the image reconstruction accuracy and the data storage space to a certain extent.
In an embodiment, another image reconstruction storage method is provided, and the embodiment relates to a specific process of performing fusion processing on a high-resolution region of interest and a low-resolution region of non-interest to obtain a third sequence of images. On the basis of the above embodiment, the above S206 may include the following step a:
and step A, fusing a part of slice images corresponding to the region of interest in the first sequence image and a part of slice images except the region of interest in the second sequence image to obtain a third sequence image.
In this step, the region of interest may be a lesion region, and the number of the regions of interest may be one or more.
Specifically, a machine learning algorithm, a neural network algorithm and the like can be adopted to process the first sequence image and the second sequence image respectively to obtain the position of a voxel point of the region of interest in the first sequence image and the position of a voxel point of the region of interest in the second sequence image, and then a slice image of the region of interest on the first sequence image is obtained according to the position of the voxel point of the region of interest in the first sequence image, and a slice image of the region of interest on the second sequence image is obtained according to the position of the voxel point of the region of interest in the second sequence image; then, during the fusion, the slice images of the region of interest on the first sequence image may be retained, and the slice images of the first sequence image except the region of interest are replaced with the corresponding slice images of the second sequence image except the region of interest, so as to finally form a third sequence image.
The image reconstruction storage method provided by this embodiment can perform fusion processing on the partial slice images corresponding to the region of interest in the first sequence image and the partial slice images except for the region of interest in the second sequence image, so as to obtain a third sequence image. In this embodiment, since the region of interest is reserved with the high-resolution slice image, that is, the region of interest can be ensured to be an image with high reconstruction accuracy, so that a more accurate analysis result can be obtained when the region of interest is analyzed subsequently, and meanwhile, since the region of non-interest is reserved with the low-resolution slice image, a part of data storage space can be saved.
In an embodiment, another image reconstruction storage method is provided, and the embodiment relates to a specific process of how to calculate the position of the region of interest according to the reconstruction parameters and other parameters, and perform fusion processing on the first sequence image and the second sequence image according to the position of the region of interest. On the basis of the above embodiment, as shown in fig. 3, the step a may include the following steps:
s302, calculating the first region position coordinate of the region of interest according to the reconstruction parameter corresponding to the first sequence image.
The first area position coordinate may be position coordinates of a plurality of points, and certainly may also be position coordinates of one point, but this embodiment mainly refers to position coordinates of a plurality of points; the first region position coordinates refer to position coordinates of the region of interest on the first sequence of images, and may be coordinates of the region of interest in an image coordinate system (or a voxel coordinate system, which may also be referred to as a voxel coordinate system). In calculating the first region position coordinates, the following steps a1 and a2 may be optionally employed, as follows:
step A1, acquiring the position coordinates of the physical region of the region of interest in the world coordinate system.
Step A2, calculating the first region position coordinate of the region of interest in the image coordinate system according to the physical region position coordinate and the corresponding reconstruction parameter of the first sequence image.
Specifically, the first sequence of images may be detected by a machine learning algorithm or the like, and position coordinates of each point on the bounding box of the region of interest in a world coordinate system (may also be referred to as a physical coordinate system) may be obtained and recorded as physical region position coordinates of the region of interest. After obtaining the physical region position coordinates of the region of interest, the physical region position coordinates may be converted to region position coordinates in an image coordinate system, in the conversion, the parameters according to may include reconstruction parameters corresponding to the first sequence image, origin-related parameters in a world coordinate system, and the like, and in the specific conversion, the conversion may be performed according to a relation (1), where the relation (1) is as follows:
image area position coordinate (physical area position coordinate-origin coordinate)/reconstruction parameter (1)
In the relational expression (1), the image region position coordinate refers to a first region position coordinate of the region of interest in an image coordinate system, which may also be referred to as a voxel coordinate, the origin coordinate refers to an origin coordinate in a world coordinate system, which may be preset before reconstructing the first sequence image, that is, a known quantity, and the reconstruction parameter refers to a reconstruction parameter corresponding to the first sequence image, which may be a reconstruction interval.
And substituting the physical region position coordinates and the origin coordinates of each point of the region of interest and the reconstruction parameters corresponding to the first sequence image into the relational expression (1), so as to obtain the position coordinates of each point of the region of interest in the image coordinate system, and marking the position coordinates as the first region position coordinates.
By way of example, assuming that the size of the first sequence of images is 512 × 506, the world coordinates of a point on the region of interest are (-107.61, -108.47, -273.49), the origin coordinates are (-183.17, -304.67, -404.50), and the reconstruction parameters are (0.67,0.67,0.7), then:
the x-axis element coordinate of the point is (-107.61- (-183.17))/0.67 is 112.78;
the y-axis element coordinate of the point is (-108.47- (-304.67))/0.67 is 292.84;
the z-axis coordinate of the point is (-273.49- (-404.50))/0.7 is 187.16;
the voxel coordinate of this point is therefore (112.78,292.84,187.16).
S304, according to the first area position coordinates, slice images where the first area position coordinates are located are determined on the first sequence images.
Specifically, the computer device may find out the voxel coordinate of the top point and the voxel coordinate of the bottom point of the region of interest along the Z-axis direction in the first region position coordinate, and find out a corresponding slice range on the first sequence of images according to the voxel coordinate of the top point and the voxel coordinate of the bottom point, so that slices corresponding to all points of the region of interest between the top and the bottom are also in the found slice range, and a slice image where the first region position coordinate is located may be obtained.
Illustratively, continuing with the data of S302 above as an example, if the coordinates of the voxel points at the top and bottom points of the region of interest are calculated as (112.78,292.84,187.16) and (112.78,292.84,207.16), then the slice range of the region of interest can be determined to be from the 187 th layer to the 207 th layer on the first sequence of images.
S306, carrying out fusion processing on the slice image of the position coordinates of the first region and the partial slice images except the region of interest in the second sequence image to obtain a third sequence image.
Before the fusion, the slice range of the non-interesting region on the second sequence image can be calculated, and then the non-interesting region is fused with the interesting region slice of the first sequence image. Optionally, the process of calculating and fusing may be as shown in fig. 4a, and as shown in fig. 4a, S306 may include the following steps S402-S408:
s402, calculating the second region position coordinate of the region of interest according to the reconstruction parameter and/or the first region position coordinate corresponding to the second sequence.
The second area position coordinates may be position coordinates of a plurality of points, or may be position coordinates of one point, as with the first area position coordinates, but this embodiment mainly refers to position coordinates of a plurality of points; the second region position coordinates refer to position coordinates of the region of interest on the second sequence of images, and may be coordinates of the region of interest in an image coordinate system (or a voxel coordinate system). In calculating the second region position coordinates, the following steps B1 and B2 may be optionally employed, as follows:
and B1, acquiring the position coordinates of the physical region of the region of interest in the world coordinate system.
And B2, calculating the second region position coordinate of the region of interest in the image coordinate system according to the physical region position coordinate and the reconstruction parameter and/or the first region position coordinate corresponding to the second sequence image.
In this step, the world coordinate systems of the first sequence image and the second sequence image are consistent during reconstruction (in this world coordinate system, the position of the entire model is determined to be unchanged, such as the positions of parts of the scanning apparatus, the position of the patient, and the like), so that the position of the region of interest in the scanning data based on the reconstructed first sequence image and the reconstructed second sequence image is unchanged in the world coordinate system, that is, the coordinate position of the physical region of the region of interest in the world coordinate system is the same regardless of whether the first sequence image or the second sequence image is reconstructed.
In this embodiment, two methods may be used to calculate the second region position coordinate, one is obtained by calculating the physical region position coordinate and the reconstruction parameter corresponding to the second sequence, and the other is obtained by calculating the physical region position coordinate, the first region position coordinate, and the reconstruction parameter corresponding to the second sequence. The specific processes of the two calculation methods are respectively given as follows:
in the first calculation method, since the positions of the regions of interest in the first sequence image and the second sequence image in the world coordinate system are the same, the physical region position coordinates of the region of interest on the first sequence image obtained in the above step S302, which are also the physical region position coordinates of the region of interest on the second sequence image, can be both recorded as the physical region position coordinates of the region of interest. After obtaining the physical region position coordinates of the region of interest, the physical region position coordinates may be converted to region position coordinates in the image coordinate system, during the transformation, the parameters to be used for the transformation may include reconstruction parameters corresponding to the second sequence image, origin-related parameters in the world coordinate system, and the like, and during the specific transformation, the transformation may be continued according to the relation (1), except that in the relation (1), the image region position coordinates here refer to the second region position coordinates of the region of interest in the image coordinate system, which may also be referred to as voxel coordinates, the origin coordinates refer to the origin coordinates in the world coordinate system, which may be set in advance before reconstructing the second sequence of images, i.e. the known quantity, the reconstruction parameter refers to the reconstruction parameter corresponding to the second sequence of images, which may be the reconstruction interval, as in the first region position coordinate.
And substituting the physical region position coordinates and the origin coordinates of each point of the region of interest and the reconstruction parameters corresponding to the second sequence image into the relational expression (1), so as to obtain the position coordinates of each point of the region of interest in the image coordinate system, and marking the position coordinates as the second region position coordinates.
In the second calculation method, since the positions of the regions of interest in the first sequence of images and the second sequence of images in the world coordinate system are the same and the coordinates of the origin are also the same, as can be seen from the relational expression (1), the product of the first region position coordinates and the first reconstruction parameters is equal to the product of the second region position coordinates and the second reconstruction parameters, and the first reconstruction parameters, i.e., the first region position coordinates and the first reconstruction parameters and the second reconstruction parameters of the respective points of the regions of interest can be obtained from the physical region position coordinates and the first region position coordinates, which are known, the second region position coordinates of the respective points of the regions of interest can be calculated from the equal relational expression.
And S404, determining a slice image in which the second area position coordinate is located on the second sequence image according to the second area position coordinate.
Specifically, the computer device may find out the voxel coordinate of the top point and the voxel coordinate of the bottom point of the region of interest along the Z-axis direction in the second region position coordinate, and find out a corresponding slice range on the second sequence image according to the voxel coordinate of the top point and the voxel coordinate of the bottom point, so that slices corresponding to all points of the region of interest between the top and the bottom are also within the found slice range, i.e., a slice image in which the second region position coordinate is located may be obtained.
And S406, determining the rest slice images except the slice image in which the second area position coordinate is positioned on the second sequence image according to the slice image in which the second area position coordinate is positioned.
Specifically, when the second sequence image is reconstructed, the total slice range can be obtained synchronously, after the slice range corresponding to the region of interest on the second sequence image is obtained, the slice range corresponding to the region of interest can be subtracted from the total slice range, so that the slice range corresponding to the region of non-interest on the second sequence image can be obtained, and the slice of the region of non-interest on the slice range corresponding to the second sequence image can be recorded as the remaining slice image.
For example, if the second sequence of images has 100 slice images, and the slice range of the region of interest calculated on the second sequence of images is 29-35 slices, the slice images of the region of non-interest are 1-28 slices and 36-100 slices.
And S408, carrying out fusion processing on the slice image with the first area position coordinate and the residual slice images.
Specifically, referring to fig. 4b, the graph (a) in fig. 4b is a first sequence image, the graph (b) in fig. 4b is a second sequence image, and the graph (c) in fig. 4b is a third sequence image, a slice image in which the region of interest is located is detected on the first sequence image in the graph (a) in fig. 4b, a position of a frame in the graph (a), that is, a slice image in which the first region position coordinate is located, may also be detected on the second sequence image in the graph (b) in fig. 4b, a position of a frame in the graph (b), that is, a slice image in which the second region position coordinate is located, may be obtained later on the second sequence image, a remaining slice image other than the slice image in which the second region position coordinate is located may be obtained, and during fusion, the slice image in which the first region position coordinate is located may be retained, filling the residual slice images of the non-interested regions on the second sequence images to the positions of the non-interested regions in the first sequence correspondingly to obtain a third sequence image; or filling the slice in the range of the region of interest with the slice corresponding to the first sequence image, and filling the slice in the range of the region of non-interest with the slice corresponding to the second sequence image to obtain the third sequence image.
According to the image reconstruction and storage method provided by the embodiment, the slice image in which the region of interest in the first sequence image is located and the slice image in which the region of non-interest in the second sequence image is located can be calculated according to the reconstruction parameters of the first sequence image, the reconstruction parameters of the second sequence image and some physical parameters, and the slice images are fused to obtain the third sequence image. In this embodiment, since the process of calculating the slice range in which the region of interest is located on the first sequence image and the process of calculating the slice range in which the region of non-interest is located on the second sequence image are both simple and accurate, the method can quickly obtain the third sequence image, improve the efficiency of reconstructing and storing the whole image, and simultaneously make the obtained third sequence image more accurate.
In one embodiment, another image reconstruction storage method is provided, and the embodiment relates to a specific process of performing weighted superposition on medical images of different modalities. On the basis of the above embodiment, as shown in fig. 5, the method may further include the following steps:
s502, acquiring at least one medical image of an object to be detected; the modality of the at least one medical image is different from the modality of the third sequence of images, the at least one medical image including a region of interest.
S504, carrying out weighted fusion or weighted superposition processing on at least one medical image and the third sequence image, and displaying the processed images.
The modality of the third sequence of images may be a CT modality, and the modality of the at least one medical image may be any one of a CT modality, a PET modality, an MR modality, and the like, but in the present embodiment, the modality of the at least one medical image cannot be the same as the modality of the third sequence of images, for example, the modality of the third sequence of images is CT, and then the modality of the at least one medical image cannot be CT, and may be any one of an MR modality, a PET modality, and the like.
In this embodiment, since the medical images of different modalities can provide different information about organs and tissues related to the human body, when the medical devices of different modalities detect the human body, the information of different modalities, which is obtained by detecting the same organ of the human body, can be different from each other or be complementary to each other, so that the information of different modalities can be integrated to detect the human body, and more information can be provided to the doctor, so that the doctor can make a more accurate detection result. For example, the PET modality image can provide detailed molecular information such as functions and metabolism of a lesion, the CT modality image can provide precise anatomical localization of the lesion, and tomographic images of all directions of the whole body can be obtained through one-time imaging.
In addition, the weighted fusion or weighted superposition may be performed by setting a weighting coefficient for each of the at least one medical image and the third sequence image, multiplying each layer image of each modality image by the corresponding weighting coefficient, and then displaying the weighted modality images in a superposed manner. For example, assuming that the third sequence image is a, at least one medical image is B, and the fused image is F, the manner of performing weighted fusion processing on A, B images of two modalities can be expressed as the following formula (2):
F(i,j)＝αA(i,j)+βB(i,j) (2)
in formula (2), i denotes a row of image pixels, j denotes a column of image pixels, α denotes a weighting coefficient 1, β denotes a weighting coefficient 2, and generally α + β is 1.
Specifically, the computer device may scan the object to be detected by using the scanning device and perform data reconstruction on the scan data to obtain at least one medical image, or may obtain at least one medical image by using a pre-stored medical image of the object to be detected, and of course, there may be other manners. Then, the third sequence image and the at least one medical image may be multiplied by their corresponding weighting coefficients, and the weighted images of the modalities may be displayed in an overlapping manner.
In the image reconstruction storage method provided by this embodiment, at least one medical image of the object to be detected is acquired, a modality of the at least one medical image is different from a modality of the third sequence image, the at least one medical image includes a region of interest, the at least one medical image and the third sequence image are subjected to weighted fusion or weighted superposition, and the processed images are displayed. In this embodiment, since medical images of different modalities have advantages and disadvantages, after performing appropriate weighted fusion on different medical image information, information of multiple images can be simultaneously expressed on one image, so that more information about regions of interest or lesions can be provided for a doctor, and thus, when the doctor detects the regions of interest or the lesions, an obtained detection result is more accurate, and further, the detection accuracy is improved.
It should be understood that although the various steps in the flow charts of fig. 2-3, 4a, 5 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-3, 4a, and 5 may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternatingly with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 6, there is provided an image reconstruction storage apparatus including: an acquisition module 10, a reconstruction module 11 and a fusion module 12, wherein:
an obtaining module 10, configured to obtain scan data of an object to be detected and two different reconstruction parameters;
the reconstruction module 11 is configured to perform data reconstruction on the scan data respectively by using the two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, the first sequence of images and the second sequence of images each including a region of interest;
a fusion module 12, configured to perform fusion processing on a part of slice images in the first sequence of images and a part of slice images in the second sequence of images to obtain a third sequence of images, and store the third sequence of images; the third sequence of images includes the region of interest.
For specific limitations of the image reconstruction storage device, reference may be made to the above limitations of the image reconstruction storage method, which are not described herein again.
In another embodiment, the fusion module 12 is further configured to perform fusion processing on the partial slice images corresponding to the region of interest in the first sequence image and the partial slice images except for the region of interest in the second sequence image, so as to obtain the third sequence image.
In another embodiment, another image reconstruction storage apparatus is provided, and on the basis of the above embodiment, the above fusion module 12 may include a calculation unit, a determination unit, and a fusion unit, where:
the calculation unit is used for calculating first region position coordinates of the region of interest according to the reconstruction parameters corresponding to the first sequence images;
a determining unit, configured to determine, according to the first region position coordinate, a slice image in which the first region position coordinate is located on the first sequence image;
and the fusion unit is used for fusing the slice image of the first region position coordinate and the partial slice images except the region of interest in the second sequence image to obtain the third sequence image.
Optionally, the computing unit is further configured to obtain a physical region position coordinate of the region of interest in a world coordinate system; and calculating the first region position coordinate of the region of interest under an image coordinate system according to the physical region position coordinate and the reconstruction parameter corresponding to the first sequence image.
In another embodiment, another image reconstruction storage apparatus is provided, and on the basis of the above embodiment, the fusion unit may include: a calculation subunit, a first determination subunit, a second determination subunit, and a fusion subunit, wherein:
a calculating subunit, configured to calculate a second region position coordinate of the region of interest according to the reconstruction parameter corresponding to the second sequence and/or the first region position coordinate;
a first determining subunit, configured to determine, according to the second region position coordinate, a slice image in which the second region position coordinate is located on the second sequence image;
a second determining subunit, configured to determine, on the second sequence image, a remaining slice image other than the slice image at which the second region position coordinate is located, according to the slice image at which the second region position coordinate is located;
and the fusion subunit is used for carrying out fusion processing on the slice image where the first area position coordinate is located and the residual slice image.
Optionally, the computing subunit is further configured to obtain a physical region position coordinate of the region of interest in a world coordinate system; and calculating the second region position coordinate of the region of interest under an image coordinate system according to the physical region position coordinate and the reconstruction parameter corresponding to the second sequence image and/or the first region position coordinate.
In another embodiment, another image reconstruction storage apparatus is provided, and on the basis of the above embodiment, the apparatus may further include a weighted fusion module, configured to acquire at least one medical image of the object to be detected; a modality of the at least one medical image and a modality of the third sequence of images are different, the at least one medical image including the region of interest; and performing weighted fusion or weighted superposition processing on the at least one medical image and the third sequence image, and displaying the processed images.
For specific limitations of the image reconstruction storage device, reference may be made to the above limitations of the image reconstruction storage method, which are not described herein again.
The modules in the image reconstruction storage device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring scanning data and two different reconstruction parameters of an object to be detected;
respectively reconstructing the data of the scanning data by adopting the two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, the first sequence of images and the second sequence of images each including a region of interest;
fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes the region of interest.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
and fusing the partial slice images corresponding to the region of interest in the first sequence image and the partial slice images except the region of interest in the second sequence image to obtain the third sequence image.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
calculating a first region position coordinate of the region of interest according to the reconstruction parameter corresponding to the first sequence image;
determining a slice image in which the first region position coordinate is located on the first sequence image according to the first region position coordinate;
and fusing the slice image of the position coordinate of the first region and the partial slice images except the region of interest in the second sequence image to obtain the third sequence image.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
calculating a second region position coordinate of the region of interest according to the reconstruction parameter corresponding to the second sequence and/or the first region position coordinate;
determining a slice image in which the second region position coordinate is located on the second sequence image according to the second region position coordinate;
determining the rest slice images except the slice image in which the second area position coordinate is located on the second sequence image according to the slice image in which the second area position coordinate is located;
and carrying out fusion processing on the slice image where the first area position coordinate is located and the residual slice image.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring the position coordinates of the physical region of the region of interest in a world coordinate system;
and calculating the first region position coordinate of the region of interest under an image coordinate system according to the physical region position coordinate and the reconstruction parameter corresponding to the first sequence image.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring the position coordinates of the physical region of the region of interest in a world coordinate system;
and calculating the second region position coordinate of the region of interest under an image coordinate system according to the physical region position coordinate and the reconstruction parameter corresponding to the second sequence image and/or the first region position coordinate.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring at least one medical image of the object to be detected; a modality of the at least one medical image and a modality of the third sequence of images are different, the at least one medical image including the region of interest;
and performing weighted fusion or weighted superposition processing on the at least one medical image and the third sequence image, and displaying the processed images.
In one embodiment, a readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring scanning data and two different reconstruction parameters of an object to be detected;
respectively reconstructing the data of the scanning data by adopting the two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, the first sequence of images and the second sequence of images each including a region of interest;
fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes the region of interest.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and fusing the partial slice images corresponding to the region of interest in the first sequence image and the partial slice images except the region of interest in the second sequence image to obtain the third sequence image.
In one embodiment, the computer program when executed by the processor further performs the steps of:
calculating a first region position coordinate of the region of interest according to the reconstruction parameter corresponding to the first sequence image;
determining a slice image in which the first region position coordinate is located on the first sequence image according to the first region position coordinate;
and fusing the slice image of the position coordinate of the first region and the partial slice images except the region of interest in the second sequence image to obtain the third sequence image.
In one embodiment, the computer program when executed by the processor further performs the steps of:
calculating a second region position coordinate of the region of interest according to the reconstruction parameter corresponding to the second sequence and/or the first region position coordinate;
determining a slice image in which the second region position coordinate is located on the second sequence image according to the second region position coordinate;
determining the rest slice images except the slice image in which the second area position coordinate is located on the second sequence image according to the slice image in which the second area position coordinate is located;
and carrying out fusion processing on the slice image where the first area position coordinate is located and the residual slice image.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring the position coordinates of the physical region of the region of interest in a world coordinate system;
and calculating the first region position coordinate of the region of interest under an image coordinate system according to the physical region position coordinate and the reconstruction parameter corresponding to the first sequence image.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring the position coordinates of the physical region of the region of interest in a world coordinate system;
and calculating the second region position coordinate of the region of interest under an image coordinate system according to the physical region position coordinate and the reconstruction parameter corresponding to the second sequence image and/or the first region position coordinate.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring at least one medical image of the object to be detected; a modality of the at least one medical image and a modality of the third sequence of images are different, the at least one medical image including the region of interest;
and performing weighted fusion or weighted superposition processing on the at least one medical image and the third sequence image, and displaying the processed images.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. An image reconstruction storage method, characterized in that the method comprises:
acquiring scanning data and two different reconstruction parameters of an object to be detected;
respectively reconstructing the data of the scanning data by adopting the two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, the first sequence of images and the second sequence of images each including a region of interest;
fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes the region of interest.
2. The method according to claim 1, wherein the fusing the partial slice images in the first sequence of images and the partial slice images in the second sequence of images to obtain a third sequence of images comprises:
and fusing the partial slice images corresponding to the region of interest in the first sequence image and the partial slice images except the region of interest in the second sequence image to obtain the third sequence image.
3. The method according to claim 2, wherein the fusing the partial slice images corresponding to the region of interest in the first sequence of images and the partial slice images except the region of interest in the second sequence of images to obtain a third sequence of images comprises:
calculating a first region position coordinate of the region of interest according to the reconstruction parameter corresponding to the first sequence image;
determining a slice image in which the first region position coordinate is located on the first sequence image according to the first region position coordinate;
and fusing the slice image of the position coordinate of the first region and the partial slice images except the region of interest in the second sequence image to obtain the third sequence image.
4. The method according to claim 3, wherein the fusing the slice image in which the first region position coordinates are located and the partial slice images of the second sequence of images except for the region of interest comprises:
calculating a second region position coordinate of the region of interest according to the reconstruction parameter corresponding to the second sequence and/or the first region position coordinate;
determining a slice image in which the second region position coordinate is located on the second sequence image according to the second region position coordinate;
determining the rest slice images except the slice image in which the second area position coordinate is located on the second sequence image according to the slice image in which the second area position coordinate is located;
and carrying out fusion processing on the slice image where the first area position coordinate is located and the residual slice image.
5. The method according to claim 3 or 4, wherein the calculating the first region position coordinates of the region of interest according to the corresponding reconstruction parameters of the first sequence of images comprises:
acquiring the position coordinates of the physical region of the region of interest in a world coordinate system;
and calculating the first region position coordinate of the region of interest under an image coordinate system according to the physical region position coordinate and the reconstruction parameter corresponding to the first sequence image.
6. The method according to claim 4, wherein the calculating the second region position coordinates of the region of interest according to the corresponding reconstruction parameters of the second sequence and/or the first region position coordinates comprises:
acquiring the position coordinates of the physical region of the region of interest in a world coordinate system;
and calculating the second region position coordinate of the region of interest under an image coordinate system according to the physical region position coordinate and the reconstruction parameter corresponding to the second sequence image and/or the first region position coordinate.
7. The method of claim 1, further comprising:
acquiring at least one medical image of the object to be detected; a modality of the at least one medical image and a modality of the third sequence of images are different, the at least one medical image including the region of interest;
and performing weighted fusion or weighted superposition processing on the at least one medical image and the third sequence image, and displaying the processed images.
8. An image reconstruction storage apparatus, comprising:
the acquisition module is used for acquiring the scanning data of the object to be detected and two different reconstruction parameters;
the reconstruction module is used for respectively reconstructing the data of the scanning data by adopting the two different reconstruction parameters to obtain a first sequence image and a second sequence image; the resolution of the first sequence of images is higher than the resolution of the second sequence of images, the first sequence of images and the second sequence of images each including a region of interest;
the fusion module is used for fusing part of slice images in the first sequence images and part of slice images in the second sequence images to obtain third sequence images, and storing the third sequence images; the third sequence of images includes the region of interest.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| CN113724177A (en) * | 2021-09-07 | 2021-11-30 | 北京大学深圳医院 | Pulmonary nodule information fusion method, device, equipment and storage medium thereof |
| CN113724177B (en) * | 2021-09-07 | 2023-12-15 | 北京大学深圳医院 | Lung nodule information fusion method, device, equipment and storage medium thereof |
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