Method and system for digital mammographic imaging

Abstract

Various methods and systems for reducing blur in diagnostic images are provided. In one example, a method includes reducing blur in a diagnostic image by applying a deconvolution filter to the diagnostic image, the deconvolution filter being generated by a point spread function (PSF) estimate of blur at each pixel of the diagnostic image, the PSF estimate being generated based on a motion vector field between the diagnostic image and a pre-image acquired prior to the diagnostic image.

Description

Technical Field

[0001] Embodiments of the subject matter disclosed herein relate to medical imaging, and more particularly to digital mammographic imaging. Background Art

[0002] Mammography is a medical imaging procedure that includes x-ray images used to detect the presence of one or more tumors or lesions in the breast. In digital mammography, a positioning or pre-image of the patient may be taken to determine the x-ray technique (e.g., x-ray tube current and voltage, exposure time) to acquire an image of the patient with sufficient brightness. Upon determining the x-ray technique, one or more x-ray images of the patient may be acquired. In some examples, multiple x-ray images may be acquired at different viewing angles and / or at different energy levels. Summary of the invention

[0003] In one embodiment, a method includes reducing blur in a diagnostic image by applying a deconvolution filter to the diagnostic image, the deconvolution filter generated by a point spread function (PSF) estimate of the blur at each pixel of the diagnostic image, the PSF estimate generated based on a motion vector field between the diagnostic image and a pre-image acquired prior to the diagnostic image.

[0004] It should be understood that the above brief description is provided to introduce in a simplified form selected concepts that are further described in the detailed description. It is not meant to identify key or essential features of the claimed subject matter, the scope of which is solely defined by the claims that follow the detailed description. Furthermore, the claimed subject matter is not limited to implementations that solve any disadvantages noted above or in any part of this disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0005] The present disclosure will be better understood by reading the following description of non-limiting embodiments with reference to the accompanying drawings, in which:

[0006] Figure 1 is a schematic diagram of a digital mammography system according to one embodiment;

[0007] Figure 2 is an image registration method according to an embodiment;

[0008] Figure 3 is a flow chart of a method for detecting and reducing the effects of patient motion-induced blur within images generated by digital mammography according to embodiments disclosed herein;

[0009] Figure 4 schematically illustrates a process for image registration; and

[0010] Figure 5The process for reducing blur is schematically shown. DETAILED DESCRIPTION

[0011] The following description relates to various embodiments for a digital mammographic imaging procedure. A digital mammographic imaging procedure may include acquiring two-dimensional (2D) or 3D digital images of a breast. For example, digital breast tomosynthesis (DBT) is an imaging technique for generating cross-sectional images of a breast with high in-plane resolution. During imaging using a digital mammography system, the breast is compressed and low-dose x-ray projection images of the breast at one or more x-ray tube angles may be obtained at a detector. The projection images are then reconstructed into a standard 2D image, or multiple images at different angles may be used to construct a 3D volume from which 2D slices may be obtained.

[0012] However, during x-ray exposure, patient motion may occur, which may cause blurring artifacts (e.g., blurring) within the reconstructed image. Blurring may obscure significant breast pathology and may require repeated imaging, thereby increasing the radiation dose received by the patient and causing patient anxiety. Several steps can be taken to reduce patient motion, such as improving patient positioning, limiting the potential for patient movement, and preventing breathing during the exposure duration, but blurring may still persist. Blurring may occur due to insufficient breast compression, patient muscle relaxation, compression paddle movement, and / or patient movement.

[0013] Thus, according to embodiments disclosed herein, a method is provided for estimating a motion vector at each image pixel by registering a pre-taken image (assuming no motion; very short acquisition) and a diagnostic full-dose mammography image. The motion vector field can generate a point spread function (PSF) of the blur at each image pixel. The estimated PSF can then be used to deconvolve the motion blur and improve spatial resolution. The image registration can be configured to estimate motion vectors in high-noise images and can therefore be robust even with pre-taken images, which are typically high-noise images. By utilizing this technique in both pre-taken (noisy) and full-dose mammography images, a motion kernel can be estimated that can be used to deconvolve the motion blur in the full-dose mammography image.

[0014] Figure 1 A schematic diagram of a digital mammography system that may be used to acquire diagnostic x-ray images of a patient. Figure 2 For use in Figure 1 Image registration method for images acquired by a digital mammography system, such as by Figure 4 The process is shown schematically. Figure 3 For use according to Figure 2 A flow chart of a method for generating a motion vector field to reduce blur within an x-ray image, such as Figure 5The process is shown schematically.

[0015] See also Figure 1 , a digital mammography system 100 including an x-ray system 10 for performing a mammography procedure is shown in accordance with an embodiment of the present disclosure. In some examples, the x-ray system 10 can be a tomosynthesis system, such as a digital breast tomosynthesis (DBT) system. In some examples, the x-ray system 10 can be configured to acquire dual energy images, which can be advantageous for increasing visualization of certain structures (e.g., vasculature) when contrast agents are injected into a patient. In addition, the x-ray system 10 can be used to perform one or more procedures, including digital tomosynthesis imaging and DBT-guided breast biopsy.

[0016] The x-ray system 10 includes a support structure 42 to which a radiation source 16, a radiation detector 18, and a collimator 20 are attached. The radiation source 16 is housed within a gantry 15 that is movably coupled to the support structure 42. Specifically, the gantry 15 may be mounted to the support structure 42 so that the gantry 15 including the radiation source 16 may rotate relative to the radiation detector 18 about an axis 58. The rotation angle range of the gantry 15 housing the radiation source 16 indicates rotation up to a desired angle in either direction about the axis 58. For example, the rotation angle range of the radiation source 16 may be -θ to +θ, where θ may make the angle range a limited angle range of less than 360 degrees. An exemplary x-ray system may have an angle range of ±11 degrees, which may allow the gantry to rotate from -11 degrees to +11 degrees (i.e., rotation of the radiation source) about the axis of rotation of the gantry. The angle range may vary according to manufacturing specifications. For example, according to manufacturing specifications, the angle range of a DBT system may be about ±11 degrees to ±60 degrees. In some examples, gantry 15 may be stationary and may not rotate.

[0017] The radiation source 16 is directed toward the volume or object to be imaged and is configured to emit radiation rays at a desired time to acquire one or more images. The radiation detector 18 is configured to receive the radiation rays via the surface 24. The detector 18 can be any of a variety of different detectors, such as an x-ray detector, a digital radiography detector, or a flat panel detector. The collimator 20 is disposed adjacent to the radiation source 16 and is configured to adjust the irradiation area of ​​the subject.

[0018] In some embodiments, the system 10 may also include a patient shield 36 mounted to the radiation source 16 via a mask rail 38 so that a body part of the patient (e.g., head) is not directly exposed to the radiation. The system 10 may also include a compression paddle 40 that is movable upward and downward relative to the support structure along a vertical axis 60. Thus, the compression paddle 40 may be adjusted to be positioned closer to the radiation detector 18 by moving the compression paddle 40 downward toward the detector 18, and the distance between the detector 18 and the compression paddle 40 may be increased by moving the compression paddle 40 upward away from the detector along the vertical axis 60. The movement of the compression paddle 40 may be adjusted by a user via a compression paddle actuator (not shown) included in the x-ray system 10. The compression paddle 40 may hold a body part, such as a breast, in position against the surface 24 of the radiation detector 18. The compression paddle 40 may compress the body part and hold the body part in position while optionally providing a hole to allow insertion of a biopsy needle, such as a core needle or a vacuum-assisted core needle. Thus, compression paddle 40 may be used to compress a body part to minimize the thickness through which x-rays pass and to help reduce movement of the body part due to patient movement. X-ray system 10 may also include an object support (not shown) on which a body part may be positioned.

[0019] The digital mammography system 100 may also include a workstation 43 including a controller 44 and a memory, the controller including at least one processor. The controller 44 may be communicatively coupled to one or more components of the x-ray system 10, including one or more of the radiation source 16, the radiation detector 18, the compression paddle 40, and the biopsy device. In one embodiment, communication between the controller and the x-ray system 10 may occur via a wireless communication system. In other embodiments, the controller 44 may be in electrical communication with one or more components of the x-ray system via a cable 47. Furthermore, in an exemplary embodiment, as shown in FIG. Figure 1 As shown, the controller 44 is integrated into the workstation 43. In other embodiments, the controller 44 may be integrated into one or more of the various components of the system 10 disclosed above. In addition, the controller 44 may include processing circuitry that executes stored program logic and may be any of a variety of computers, processors, controllers, or combinations thereof that are available and compatible with various types of equipment and devices used in the x-ray system 10.

[0020] Workstation 43 may include a radiation shield 48 that protects an operator of system 10 from radiation rays emitted by radiation source 16. Workstation 43 may also include a display 50, keyboard 52, mouse 54, and / or other suitable user input devices that facilitate control of system 10 via user interface 56.

[0021] The controller 44 may regulate the operation and functionality of the x-ray system 10. For example, the controller 44 may provide timing control regarding when the x-ray source 16 emits x-rays, and may further regulate how the detector 18 reads and transmits information or signals after the x-rays strike the detector 18, as well as how the x-ray source 16 and detector 18 move relative to each other and relative to the body part being imaged. The controller 44 may also control how information, including images 42 and data acquired during operation, is processed, displayed, stored, and manipulated. The operations performed by the controller 44 as described herein are described herein. Figure 2 and Figure 3 The various processing steps described may be provided by a set of instructions stored in a non-volatile memory of the controller 44 .

[0022] In addition, as described above, the radiation detector 18 receives the radiation rays 22 emitted by the radiation source 16. Specifically, during imaging using the x-ray system, a projection image of the imaged body part can be obtained at the detector 18. In some embodiments, data received by the radiation detector 18, such as projection image data, can be communicated electronically and / or wirelessly from the radiation detector 18 to the controller 44. The controller 44 can then reconstruct one or more x-ray images based on the projection image data, for example by implementing a reconstruction algorithm. The reconstructed image can be displayed to the user on the user interface 50 via the display screen 56.

[0023] The radiation source 16 together with the radiation detector 18 form part of the x-ray system 10, which provides x-ray images for the purpose of one or more of screening for abnormalities, diagnosis, dynamic imaging and image-guided biopsy. For example, the x-ray system 10 can be operated in a mammography mode to screen for abnormalities. During mammography, the patient's breast is positioned and compressed between the detector 18 and the compression paddle 40. Therefore, the volume of the x-ray system 10 between the compression paddle 40 and the detector 18 is the imaging volume. The radiation source 16 then emits radiation rays onto the compressed breast, and a projection image of the breast is formed on the detector 18. The projection image can then be reconstructed by the controller 44 and displayed on the interface 50. During mammography, the gantry 15 can be adjusted at different angles to obtain images of different orientations, such as head-tail (CC) images and medial-lateral oblique (MLO) images. In one example, the gantry 15 can rotate around the axis 58 while the compression paddle 40 and the detector 18 remain stationary. In other examples, gantry 15 , compression paddle 40 , and detector 18 may rotate about axis 58 as a single unit.

[0024] In addition, the x-ray system 10 can be operated in a tomosynthesis mode for performing digital breast tomosynthesis (DBT). During tomosynthesis, the x-ray system 10 can be operated to direct low-dose radiation to the imaging volume (between the compression paddle 40 and the detector 18) at various angles within the angular range of the x-ray system 10. Specifically, during tomosynthesis, similar to mammography, the breast is compressed between the compression paddle 40 and the detector 18. The radiation source 16 is then rotated from -θ to +θ, and multiple projection images of the compressed breast are obtained at regular angular intervals within the angular range. For example, if the angular range of the x-ray system is ±11 degrees, the detector can capture 22 projection images during the angular scan of the gantry at approximately every degree. The multiple projection images are then processed by the controller 44 to generate a plurality of DBT image slices. The processing may include applying one or more reconstruction algorithms to reconstruct a three-dimensional image of the breast. In addition, the x-ray system can be configured to perform a DBT-guided biopsy procedure. Thus, in some exemplary embodiments, system 10 may further include a biopsy device including a biopsy needle for extracting a tissue sample for further analysis.

[0025] In some examples, the digital mammography system 100 can be configured to perform contrast imaging, wherein a contrast agent, such as iodine, can be injected into a patient, which travels to a region of interest (ROI) (e.g., a lesion) within the breast. The contrast agent is absorbed into blood vessels surrounding a cancerous lesion in the ROI, thereby providing a contrast image over time relative to surrounding tissue, thereby enhancing the ability to locate the lesion.

[0026] The use of contrast agents can be combined with images of ROIs taken using dual-energy imaging processes and techniques. In dual-energy imaging, low-energy (LE) and high-energy (HE) images of the ROI are taken. Specifically, contrast-enhanced spectral mammography (CESM) (2D) and contrast-enhanced digital breast tomosynthesis (CE-DBT) (3D) imaging modes are performed using dual-energy techniques. For each view (a single view in CESM, multiple views in CE-DBT), a pair of images is acquired: a low-energy (LE) image and a high-energy (HE) image. In CE-DBT, unpaired HE and LE images can be acquired for each view, and HE volumes, LE volumes, and reconstructed CE volumes can be reconstructed for the ROI. For example, for each angled position of the x-ray tube, HE and LE views can be interlaced during a CE-DBT scan (or HE, LE, HE, LE, HE, LE, etc.) with switching from HE to LE and then switching to HE again. LE and HE images are usually obtained at the average energy above and below the contrast agent K edge. At x-ray energies just above the contrast agent k-edge, absorption of x-rays increases, resulting in increased contrast of the iodinated contrast agent in the HE image.

[0027] In a dual-energy 3D or stereotactic procedure, LE and HE image acquisition is performed, where the X-ray source has at least two different positions relative to the detector. The images are then reassembled to display material-specific information about the internal structure of the imaged tissue. In the case of 3D CESM, for example, after injection of contrast media, dual-energy images are acquired at two or more positions of the x-ray tube relative to the detector. For each of these tube angles, the low-energy image and the high-energy image are reassembled to produce an image of the surface concentration of the contrast medium at each pixel to provide an iodine equivalent or dual-energy (DE) image (for a single view in CESM, and for multiple views of CE-DBT), which is used in CE-DBT to reconstruct a 3D volume. Image reassembly can be performed based on a simulation of an X-ray image chain, via calibration of a reference dotted line, or any other suitable 3D reconstruction process. In addition, in a continuous acquisition mode, where the X-ray tube moves continuously and takes interlaced HE and LE images, the LE image is used to reconstruct the LE 3D volume, and the HE image is used to reconstruct the HE 3D volume, where both volumes are reassembled in a suitable manner to provide an iodine 3D volume. It is also possible to implement algorithms that combine 3D reconstruction and HE / LE reconstruction in a single step.

[0028] Figure 2 The image registration method 200 is applicable to images captured by a digital mammography system (e.g., Figure 1 The image registration may be used to compare or integrate data acquired in different images from the image set. In some examples, image registration may be used as a preliminary step in other image processing applications, such as a method for deblurring images generated from a digital mammography system described herein (see Figure 3 ). The method 200 may use a method stored in a digital mammography system (e.g., Figure 1 A computing device of the digital mammography system 100) or a controller communicatively coupled to the digital mammography system (e.g., Figure 1 The method 300 is executed by computer readable instructions in a non-transitory memory of the controller 44. In some embodiments, the method 300 may be executed by another computing device (e.g., an edge device, a picture archiving and communication system (PACS)) without departing from the scope of the present disclosure.

[0029] At 202, a reference image and a comparison image may be selected from a set of images acquired by a digital mammography system. In some examples, more than one comparison image may be selected. A reference image herein may be defined as an image that is aligned with one or more comparison images during image registration. A reference image may be a pre-taken image (when performing an image registration method to align the image with the comparison image). Figure 3The reference image may be a low energy image and the comparison image may be a high energy image, such as during dual energy imaging. The reference image and the comparison image may be images of the same anatomical feature / scan plane of the same patient.

[0030] At 204, image registration may be performed on the selected images. During image registration, the comparison image may be aligned with the reference image via a spatial domain method. The spatial domain method may include selecting control points within the reference image and the comparison image at 206. The control points may be individual pixels or groups of adjacent pixels. In one example, the control points may be randomly selected. In another example, the control points may be selected based on a predefined grid or other pattern. In another example, the control points may be selected based on which pixels / anatomical regions of the comparison image may exhibit motion-based blur (such as pixels at the edges of anatomical structures). The control points may be located at the same location in each of the reference image and the comparison image.

[0031] At 208, a local shift calculation may be performed between the control points of the two images. For each control point of the comparison image, the local shift calculation may indicate the magnitude and direction of the shift of the control point relative to the reference image. For example, the local shift calculation may generate a motion vector comprising the vector difference between the position x, y (for rows and columns) of the same clinical / anatomical feature (e.g., microcalcification or lesion) in the two images: dx=x1-x2, dy=y1-y2.

[0032] At 210, pixel-by-pixel interpolation may be performed based on the local shift calculations. The interpolation may include a first interpolation performed to transfer from the motion vector at each control point to a motion vector field (e.g., Figure 4 409). The first interpolation may include B-spline interpolation or another suitable interpolation. Thus, the first interpolation may include B-spline interpolation to generate a motion vector field, as shown in 212, wherein the motion vector field includes a corresponding motion vector at each pixel based on the motion vector at the control point, and can be used to reduce image blur, as described below. During image registration, a second interpolation may be performed, wherein for each pixel p(xp,yp) in a comparison image (e.g., the image being registered), the vector field value at pixel p(dx,dy) is used to retrieve the image pixel value at location (xp+dx,yp+dy) in the same image (because this is where the pixel should be based on the reference image). Since dx and dy are not integer values, interpolation is performed on the surrounding pixels using, for example, a linear or cubic function that can generate a registered image.

[0033] Figure 31 is a flow chart of a method 300 for reducing blur caused by patient motion in an x-ray image (e.g., a digital mammography image) according to embodiments disclosed herein. The method 300 may use a digital mammography system (e.g., Figure 1 A computing device of the digital mammography system 100) or a controller communicatively coupled to the digital mammography system (e.g., Figure 1 The method 300 is executed by computer readable instructions in a non-transitory memory of the controller 44. In some embodiments, the method 300 may be executed by another computing device (e.g., an edge device, a picture archiving and communication system (PACS)) without departing from the scope of the present disclosure.

[0034] At 302, a reference image and a diagnostic image may be acquired by a digital mammography system. The reference image may be a pre-taken image. The pre-taken image may be a short exposure, low dose image that may have a relatively high amount of noise and therefore may not be suitable for diagnostic imaging purposes, but may be used to ensure proper patient positioning, calculate a full dose required to acquire a target brightness image, etc. The diagnostic image may be a full dose diagnostic image taken after the pre-taken image. In this manner, the diagnostic image may be acquired at a higher radiation dose and / or with a longer exposure duration than the pre-taken image.

[0035] At 304, image registration may be performed on the acquired images to generate a motion vector field. Image registration may be performed according to the above explained Figure 2 method to perform (e.g., diagnostic images are relative to Figure 2 The image registration may output a motion vector field, which includes an estimated motion vector for each pixel of the diagnostic image relative to the pre-shot image.

[0036] At 306, a point spread function (PSF) estimate of blur at each pixel of the diagnostic image may be generated based on the motion vector field. The PSF may be estimated based on the motion vector field obtained from image registration between the reference image and the comparison image. For example, for each image pixel, a selected function f(p) may be fit using surrounding motion vector values ​​(from the motion field). The function is the PSF.

[0037] At 308, image deconvolution is performed to generate an image with reduced blur. For example, based on the PSF, a deconvolution filter may be generated and applied to the diagnostic image to produce an image with reduced blur. For example, the image may be convolved with a filter calculated from the inverse of the PSF. At 310, the image is output (e.g., after applying the deconvolution filter) for display on a display device (e.g., display 50) and / or stored in a memory of a computing device (e.g., a memory of controller 44 or a PACS or other suitable image storage device). The method 300 then ends.

[0038] In some examples, method 300 may be performed on all diagnostic images acquired using a digital mammography system. In other examples, method 300 may be performed only in response to a user's request to deblur an image. For example, after acquiring a diagnostic image, the diagnostic image may be displayed to a user (e.g., a technician or other clinician). The user may determine that there is an unacceptable amount of blur and may input (e.g., via a touch screen, keyboard, etc.) a request to apply the deblurring process of method 300 to reduce blur in the diagnostic image. In other examples, method 300 may be performed only in response to a determination (e.g., by a digital mammography system or other computing device) that the diagnostic image is blurry, which may be based on edge sharpness, an artificial intelligence-based model, or another suitable mechanism.

[0039] Furthermore, although method 300 is described above as being performed by a digital mammography system, and thus the diagnostic images described above may be images of breast tissue, method 300 may be performed on other types of x-ray images, such as lung images. In such examples, method 300 may be performed on different types of x-ray imaging systems, such as chest x-ray imaging systems.

[0040] Figure 4 An exemplary image registration process 400 according to an embodiment of the present disclosure is schematically illustrated. Figure 4 The image registration process 400 shown may be based on Figure 2 The image registration process 400 includes the registration of two images shown at 402. The two images include a reference image 401 and a comparison image 403. The reference image 401 may be acquired at an earlier time point than the comparison image 403. As described above, the reference image may be a pre-taken image, and the comparison image may be a full-dose diagnostic image.

[0041] At 404, the two images are registered by selecting control points, calculating the local shift at each control point, and performing pixel-by-pixel interpolation. Example control points 405 and example local shift vectors 407 are shown on the comparison image 403. Figure 4 As will be appreciated, the local shift calculation may include a vector that determines the direction and magnitude of the motion / shift of each control point of the comparison image relative to the corresponding control point of the reference image. The pixels of the comparison image are then interpolated on a pixel-by-pixel basis using an interpolation grid 409. As described above, each pixel may be interpolated based on the pixel values ​​and motion vectors of neighboring pixels. The output of the image registration process 400 is a registered image 406, which in some examples may be a comparison image 403 with some pixels adjusted to register (e.g., align) features of the comparison image 403 with the reference image 401.

[0042] Figure 5 An exemplary deblurring process 500 according to an embodiment of the present disclosure is shown. Figure 3 The method 300 of is used to perform a deblurring process 500 in order to reduce motion-based image blur that may occur due to patient movement during x-ray exposure. The deblurring process 500 includes inputting a pre-image 502 and a full-dose image 504 into an image registration method 506. The pre-image 502 may be acquired prior to the full-dose image 504 and may be acquired at a lower radiation dose and / or at a shorter exposure time. Therefore, it is assumed that no motion occurred during the acquisition of the pre-image, thereby allowing the pre-image to be a fixed image that can be compared to the full-dose image 504. The full-dose image 504 may be acquired at a longer exposure time and may therefore be prone to motion-based blur. In order to reduce blur in the full-dose image 504, the above-described method with respect to the pre-image is used. Figure 2 mentioned and Figure 4 The image registration method schematically shown in aligns the full-dose image 504 with the pre-taken image 502 .

[0043] The output from the image registration process 506 may be a motion vector field that may be used to estimate a point spread function (PSF) at each pixel, as shown at 508. Based on the PSF of each pixel, a deconvolution filter is generated, which is applied to the full dose image at 510. Deconvolution of the full dose image produces a deblurred image 512, which may be output for display and / or stored in memory as part of a patient examination.

[0044] The technical effect of using the pre-taken image as a reference image to deblur the full-dose diagnostic image is reduced motion-based image blur and more accurate imaging of the patient's anatomical features.

[0045] One embodiment relates to a method, the method comprising reducing blur in a diagnostic image by applying a deconvolution filter to the diagnostic image, the deconvolution filter being generated by a point spread function (PSF) estimate of blur at each pixel of the diagnostic image, the PSF estimate being generated based on a motion vector field between the diagnostic image and a pre-taken image acquired before the diagnostic image. In a first example of the method, the diagnostic image is an x-ray image acquired with a higher first x-ray radiation dose using an x-ray imaging system, and the pre-taken image is an x-ray image acquired with a lower second x-ray radiation dose using the x-ray imaging system. In a second example of the method (which optionally includes the first example), the diagnostic image is acquired with a longer first x-ray radiation exposure, and the pre-taken image is acquired with a shorter second x-ray radiation exposure. In a third example of the method (which optionally includes one or both of the first example and the second example), the first x-ray radiation dose is determined based on the brightness of the pre-taken image and the second x-ray radiation dose. In a fourth example of the method (which optionally includes one or more or each of the first to third examples), the method further comprises outputting the diagnostic image with reduced blur for display on a display device. In a fifth example of the method (which optionally includes one or more or each of the first to fourth examples), the method also includes generating a motion vector field by the following steps: selecting multiple control points in the pre-shot image, calculating a local shift vector of each control point relative to a corresponding control point in the diagnostic image, and interpolating each pixel of the diagnostic image based on each local shift vector to generate a motion vector field.

[0046] One embodiment of a method includes acquiring a pre-image of a patient and a diagnostic image of the patient using an x-ray imaging system; generating a motion vector field by registering the diagnostic image with the pre-image; applying a deconvolution filter to the diagnostic image to generate a diagnostic image with reduced blur, the deconvolution filter generated based on the motion field vector; and outputting the diagnostic image with reduced blur for display on a display device. In a first example of the method, the diagnostic image is acquired using the x-ray imaging system at a higher first x-ray radiation dose, and the pre-image is acquired using the x-ray imaging system at a lower second x-ray radiation dose. In a second example of the method (which optionally includes the first example), the diagnostic image is acquired with a longer first x-ray radiation exposure, and the pre-image is acquired with a shorter second x-ray radiation exposure. In a third example of the method (which optionally includes one or both of the first and second examples), the first x-ray radiation dose is determined based on the brightness of the pre-image. In a fourth example of the method (which optionally includes one or more or each of the first to third examples), a deconvolution filter is generated based on a motion vector field in the following manner: a point spread function of each pixel of the diagnostic image is estimated based on the motion vector field and a deconvolution filter is generated based on each point spread function. In a fifth example of the method (which optionally includes one or more or each of the first to fourth examples), generating a motion vector field includes selecting a plurality of control points in the pre-shot image, calculating a local shift vector of each control point relative to a corresponding control point in the diagnostic image, and interpolating each pixel of the diagnostic image based on each local shift vector to generate a motion vector field.

[0047] An embodiment of an imaging system includes an x-ray source in communication with a detector; a display device; and a computing device in communication with the display device and the detector and including a processor and a non-transitory memory storing instructions executable by the processor to: acquire a pre-image of a patient using the x-ray source and the detector at a first x-ray dose and for a first exposure duration; acquire a diagnostic image of the patient using the x-ray source and the detector at a second higher x-ray dose and for a second longer exposure duration; correct blur in the diagnostic image based on the pre-image to generate a diagnostic image with reduced blur; and output the diagnostic image with reduced blur for display on a display. In a first example of the system, correcting blur in the diagnostic image based on the pre-image includes estimating corresponding motion vectors for one or more pixels of the diagnostic image via a registration process with the pre-image; and applying a deconvolution filter to the diagnostic image to generate a diagnostic image with reduced blur, the deconvolution filter being generated based on each corresponding motion vector. In a second example of the system (which optionally includes the first example), generating the deconvolution filter includes generating a point spread function for each pixel of the diagnostic image based on each corresponding motion vector, and generating the deconvolution filter based on each point spread function. In a third example of the system, which optionally includes one or both of the first and second examples, the second x-ray dose is determined based on the brightness of the pre-image and the first x-ray dose.

[0048] As used herein, the elements or steps listed in the singular and beginning with the word "one" or "a kind of" should be understood as not excluding a plurality of the elements or steps, unless such exclusion is explicitly stated. In addition, the reference to "an embodiment" of the present invention is not intended to be interpreted as excluding the existence of additional embodiments that also include the cited features. In addition, unless explicitly stated to the contrary, the embodiment of "including", "comprising" or "having" an element or multiple elements with a specific characteristic may include additional such elements without the characteristic. The terms "including" and "in..." are used as the concise language equivalents of the corresponding terms "including" and "wherein". In addition, the terms "first", "second" and "third" etc. are only used as marks, and are not intended to impose numerical requirements or specific positional order on their objects.

[0049] This written description uses examples to disclose the invention, including the best mode, and also to enable a person of ordinary skill in the relevant art to practice the invention, including making and using any devices or systems and performing any included methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to a person of ordinary skill in the art. Such other examples are intended to fall within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insignificant differences from the literal language of the claims.

Claims

1. An imaging method, comprising: Blur in a diagnostic image is reduced by applying a deconvolution filter to the diagnostic image, the deconvolution filter being generated by a point spread function estimate of blur at each pixel of the diagnostic image, the point spread function estimate being generated based on a motion vector field between the diagnostic image and a pre-image acquired prior to the diagnostic image, wherein the diagnostic image is an x-ray image acquired using an x-ray imaging system at a first, higher, x-ray radiation dose, and the pre-image is an x-ray image acquired using the x-ray imaging system at a second, lower, x-ray radiation dose.

2. The imaging method of claim 1, wherein the diagnostic image is acquired with a first, longer x-ray radiation exposure and the pre-image is acquired with a second, shorter x-ray radiation exposure. 3 . The imaging method according to claim 1 , wherein the first x-ray radiation dose is determined based on brightness of the pre-image and the second x-ray radiation dose. 4 . The imaging method of claim 1 , further comprising outputting the diagnostic image with reduced blur for display on a display device.

5. The imaging method according to claim 1 further includes generating the motion vector field by the following steps: selecting multiple control points in the pre-captured image, calculating a local shift vector of each control point relative to a corresponding control point in the diagnostic image, and interpolating each pixel of the diagnostic image based on each local shift vector to generate the motion vector field.

6. An imaging method comprising: acquiring a pre-image of a patient and a diagnostic image of the patient using an x-ray imaging system; generating a motion vector field by registering the diagnostic image with the pre-captured image; applying a deconvolution filter to the diagnostic image to generate a diagnostic image with reduced blur, the deconvolution filter generated based on the motion vector field; as well as The diagnostic image with reduced blur is output for display on a display device, wherein the diagnostic image was acquired with the x-ray imaging system at a first, higher x-ray radiation dose, and the pre-image was acquired with the x-ray imaging system at a second, lower x-ray radiation dose.

7. The imaging method of claim 6, wherein the diagnostic image is acquired with a first, longer x-ray radiation exposure and the pre-image is acquired with a second, shorter x-ray radiation exposure. 8 . The imaging method according to claim 6 , wherein the first x-ray radiation dose is determined based on brightness of the pre-image.

9. The imaging method according to claim 6, wherein the deconvolution filter is generated based on the motion vector field by estimating a point spread function of each pixel of the diagnostic image based on the motion vector field and generating the deconvolution filter based on each point spread function.

10. The imaging method of claim 6, wherein generating the motion vector field comprises selecting a plurality of control points in the pre-captured image, calculating a local shift vector of each control point relative to a corresponding control point in the diagnostic image, and interpolating each pixel of the diagnostic image based on each local shift vector to generate the motion vector field.

11. An imaging system comprising: an x-ray source in communication with the detector; Display devices; and a computing device in communication with the display device and the detector, the computing device comprising a processor and a non-transitory memory storing instructions executable by the processor to: acquiring a pre-image of the patient using the x-ray source and the detector at a first x-ray dose and for a first exposure duration; acquiring a diagnostic image of the patient using the x-ray source and the detector at a second, higher x-ray dose and for a second, longer exposure duration; estimating corresponding motion vectors of one or more pixels of the diagnostic image via a registration process with the pre-captured image; applying a deconvolution filter to the diagnostic image to generate a diagnostic image with reduced blur, the deconvolution filter generated based on each respective motion vector; and The blur-reduced diagnostic image is output for display on the display device.

12. The imaging system of claim 11, wherein generating the deconvolution filter comprises generating a point spread function for each pixel of the diagnostic image based on each corresponding motion vector, and generating the deconvolution filter based on each point spread function.

Images