Motion detection using high contrast features

Abstract

A method for detecting motion of a patient's breast tissue during medical imaging, the method including: acquiring image data of the patient's breast tissue; processing the image data to generate a set of image slices that collectively depict the patient's breast tissue; detecting a high-contrast object on one or more image slices of the set of image slices; identifying an artifact associated with the high-contrast object on the one or more image slices of the set of image slices; measuring physical attributes of the artifact; measuring a deviation of the physical attribute from a baseline; determining that the deviation exceeds a predetermined threshold; and generating a motion indicator in response to determining that the deviation exceeds the predetermined threshold.

Description

[Background technology]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application has been filed as a PCT International Patent Application and claims priority to U.S. Provisional Patent Application No. 63 / 491,769, filed March 23, 2023, entitled "MOTION DETECTION USING HIGH CONTRAST FEATURES," which is incorporated herein by reference in its entirety.

[0002] A major challenge faced in medical imaging is ensuring the usability of the images produced. Patient movement during the course of an imaging sequence, for example due to discomfort from the length of the sequence or the alignment of the imaging device, is a frequent source of distortion and artifacts that can render images unusable. Distorted images often fail to accurately depict diagnostically relevant structures. Summary of the Invention [Means for solving the problem]

[0003] Examples presented herein are directed to a method for detecting motion of a patient's breast tissue during medical imaging, the method including acquiring image data of the patient's breast tissue, processing the image data to generate a set of image slices that collectively depict the patient's breast tissue, detecting a high-contrast object on one or more image slices of the set of image slices, identifying an artifact associated with the high-contrast object on the one or more image slices of the set of image slices, measuring physical attributes of the artifact, measuring a deviation of the physical attribute from a baseline, determining that the deviation exceeds a predetermined threshold, and generating a motion indicator in response to determining that the deviation exceeds the predetermined threshold.

[0004] In other examples presented herein, the baseline is a straight line. In further examples, the baseline includes a baseline range. In further examples, the baseline range is determined according to a set of physical attributes associated with one or more artifacts. In further examples, the one or more artifacts are associated with an absence of patient movement. In further examples, the predetermined threshold is determined according to the baseline range. In further examples, the baseline range is measured using coefficient of determination analysis.

[0005] In other examples presented herein, the high-contrast objects are identified on the in-focus image slices and the artifacts are projections of the high-contrast objects identified on the out-of-focus image slices. In other examples, detecting the high-contrast objects includes identifying at least one high-contrast object in a first image slice and, in response, scanning a second image slice one or more slices away from the first image slice for the artifacts.

[0006] In other embodiments, the physical attribute includes one or more of width, length, height, trajectory, and opacity. In a further embodiment, determining that the deviation exceeds a predetermined threshold is based on measuring a physical attribute associated with the artifact and measuring at least one high-contrast object.

[0007] In other examples presented herein, measuring the deviation from the baseline includes applying a fitting algorithm, and inputs to the fitting algorithm include one or more of: a size of the artifact, a size of an associated high-contrast object, and a contrast of the artifact. In other examples, the high-contrast object is a naturally occurring object in the breast including one or more of a calcification or a ligament. In other examples, the high-contrast object is an implanted object. In other examples, the motion indicator includes an indicator on at least one image of the one or more image slices. In other examples, the motion indicator includes a request for immediate review of at least one image of the one or more images. In other examples, measuring the deviation from the baseline associated with the artifact includes using a coefficient of determination analysis.

[0008] Other examples presented herein are directed to a system including a computer-readable memory storing executable instructions and one or more processors in communication with the computer-readable memory, wherein when the one or more processors execute the executable instructions, the one or more processors perform the following operations: acquire image data of a patient's breast tissue; process the image data to generate a set of image slices that collectively depict the patient's breast tissue; detect high-contrast objects on one or more image slices of the set of image slices; identify artifacts associated with the high-contrast objects on one or more image slices of the set of image slices; measure physical attributes of the artifacts; measure deviations of the physical attributes from a baseline; determine that the deviation exceeds a predetermined threshold; and generate a motion indicator in response to determining that the deviation exceeds the predetermined threshold.

[0009] Other examples presented herein are directed to a non-transitory computer-readable medium having stored thereon one or more sequences of instructions to cause one or more processors to acquire image data of a patient's breast tissue, process the image data to generate a set of image slices that collectively depict the patient's breast tissue, detect a high-contrast object on one or more image slices of the set of image slices, identify an artifact associated with the high-contrast object on one or more image slices of the set of image slices, measure physical attributes of the artifact, measure a deviation of the physical attribute from a baseline, determine that the deviation exceeds a predetermined threshold, and generate a motion indicator in response to determining that the deviation exceeds the predetermined threshold.

[0010] Examples presented herein are directed to a method for detecting motion of a patient's breast tissue during medical imaging, the method including receiving image data of the patient's breast tissue, processing the image data to generate a set of image slices that collectively depict the patient's breast tissue, detecting a high-contrast object on one or more image slices of the set of image slices, identifying an artifact associated with the high-contrast object on one or more image slices of the set of image slices, measuring physical attributes of the artifact, measuring a deviation of the physical attribute from a baseline, determining that the deviation exceeds a predetermined threshold, and generating a motion indicator in response to determining that the deviation exceeds the predetermined threshold.

[0011] Various additional inventive aspects will be set forth in the description that follows. Inventive aspects can relate to individual features and combinations of features. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the broad inventive concept on which the embodiments disclosed herein are based. [Brief explanation of the drawings]

[0012] The accompanying drawings, which are incorporated in and constitute a part of the description, illustrate several aspects of the present disclosure. A brief description of the drawings follows:

[0013] [Figure 1A] FIG. 1A is a schematic diagram of an exemplary imaging system.

[0014] [Figure 1B] FIG. 1B is a perspective view of the imaging system of FIG. 1A.

[0015] [Figure 2] FIG. 2 illustrates an exemplary baseline of an artifact and an exemplary deviation of the artifact.

[0016] [Figure 3] FIG. 3 is an example of an artifact in an image.

[0017] [Figure 4] FIG. 4 is an example of an artifact in an image acquired during patient motion.

[0018] [Figure 5] FIG. 5 is an exemplary workflow for detecting patient motion based on image artifacts.

[0019] [Figure 6] FIG. 6 depicts an example of a suitable operating environment in which one or more of the present embodiments can be implemented. DETAILED DESCRIPTION OF THE INVENTION

[0020] Detailed Description Described herein are systems and methods for detecting and identifying images affected by patient motion. Medical imaging frequently requires patients to maintain uncomfortable positions for a period of time to ensure that imaging devices are properly aligned to have an unobstructed view of internal body structures. The combination of patient discomfort and the time required for an image capture sequence often results in patients moving during the imaging process. Such movement can distort structures in the image and therefore produce images without diagnostic utility or relevance. Such images can result in a situation in which a radiologist or other clinician is unable to timely identify cancerous or otherwise significant structures of interest and can further lead to increased cost and inconvenience as images must be recaptured. Aspects of the present disclosure may be particularly applicable to imaging modalities performed over a range of motion measured by projection angle, such as tomosynthesis.

[0021] In X-ray-based medical imaging, such as of the breast, the density of various structures within the breast tissue produces image objects with different contrasts against the relatively low-density background of the overall breast tissue volume. Objects with high relative densities, such as calcifications, embedded clips or wires, or other structures, appear as high-contrast objects. High-contrast objects generally appear as relatively sharp or bright white objects against the darker background of the overall breast tissue. As used herein, "object" refers to a shape or structure that appears in focus in a particular image or image slice within a set or stack of images that together depict the entire breast tissue volume. An object is generally considered to be a true representation of a structure within the breast tissue.

[0022] For example, in imaging modalities defined by projection angles less than 180 degrees, these high-contrast objects can cast shadows that may appear in the reconstructed image as artifacts that track the plane of travel of the x-ray source. As used herein, "artifact" refers to an effect produced by the imaging system, but not to a true depiction of structures within the breast. An artifact is generally associated with an object. An object may be associated with one or more artifacts. The term "artifact" may encompass any feature that appears in an image but is not present in the original imaged object. In examples, an artifact may be an object that appears out of focus in a particular image or image slice, or a shadow cast by an object on a particular image slice due to the geographic shape of the breast or the projection angle of the imaging system.

[0023] The artifact will generally track the movement of the x-ray source and appear with a linear characteristic in the direction of x-ray tube movement. As used herein, "baseline" refers to this linear characteristic associated with the artifact indicative of x-ray tube movement. The baseline may include, for example, a set of characteristics including a center point, width, measurements in one or more directions starting from the center point, etc.

[0024] The present inventors have identified the innovative insight that these artifacts may also track patient motion during an image capture sequence and become visibly distorted thereby. Therefore, the systems and methods disclosed herein enable these artifact distortions to be utilized as motion indicators. By training or programming a system to identify artifact deviations as those associated with patient motion, distorted images can be quickly identified and assessed for usefulness, potentially saving the patient and imaging team the cost, time, and inconvenience associated with arranging another appointment to recapture breast images. As used herein, "deviation" refers to one or more characteristics of an artifact that differ from a set of baseline characteristics, e.g., a set of characteristics defining a straight line.

[0025] 2 illustrates an exemplary baseline 150 of an artifact and an exemplary deviation 160 of an artifact 160. The exemplary baseline 150 appears as a straight line in the direction of travel of the x-ray tube (the y-axis direction in FIG. 2). The baseline 150 may include a center point 152. The baseline 150 may be identified as a baseline by extending from the center point 152 only along the y-axis or in the direction of travel of the x-ray source.

[0026] Example artifact 162 shows an example deviation 160 from baseline 150. In addition to extending away from center point 152 in the direction of x-ray source motion (Y-axis in FIG. 2), artifact 162 also deviates and extends away from center point 152 in a direction perpendicular to the x-ray source travel (X-axis in FIG. 2). This additional motion is captured by deviation 160 and is not due to x-ray source motion. Deviation 160 can be due to motion of the patient or other object being imaged.

[0027] Other motion detection systems for tracking motion typically determine the location and distance to anatomical structures, such as the nipple or the distance to the pectoral muscle, and whether that distance has changed. Unlike the high-contrast objects described herein, such anatomical structures are typically not high-contrast. In still other systems, motion may be detected using artificial markers positioned on the external skin line or on a part of the imaging system, such as a compression paddle. Instead, current high-contrast objects are located inside the breast and either occur naturally or are placed inside the breast as a result of an interventional procedure. Additionally, the systems and methods described herein do not determine the location of the high-contrast object itself, but instead use the appearance of artifacts produced by the high-contrast object in the resulting image.

[0028] FIG. 1A is a schematic diagram of an exemplary imaging system 100 that produces the artifact described in connection with FIG. 2. FIG. 1B is a perspective view of the imaging system 100. Referring concurrently to FIGS. 1A and 1B, the imaging system 100 immobilizes a patient's breast 102 for X-ray imaging (either or both mammography and tomosynthesis) via a breast compression immobilizer unit 104 that includes a static breast support platform 106 and a movable compression paddle 108. The breast support platform 106 and the compression paddle 108 each have compression surfaces 110 and 112, respectively, that move toward each other to compress and immobilize the breast 102. In known systems, the compression surfaces 110, 112 are exposed for direct contact with the breast 102. The platform 106 also houses an image receptor 116, optionally a tilt mechanism 118, and optionally an anti-scatter grid. The immobilizer unit 104 is in the path of an imaging beam 120 emanating from an X-ray source 122 , causing the beam 120 to impinge on the image receptor 116 .

[0029] The immobilizer unit 104 is supported on a first support arm 124, and the X-ray source 122 is supported on a second support arm 126. For mammography, the support arms 124 and 126 can rotate as a unit about an axis 128 between different imaging orientations, such as CC and MLO, allowing the system 100 to capture mammogram projection images in each orientation. In operation, the image receptor 116 remains in a fixed position relative to the platform 106 while images are captured. The immobilizer unit 104 releases the breast 102 for movement of the arms 124, 126 to different imaging orientations. For tomosynthesis, the support arm 124 remains in a fixed position with the breast 102 fixed and in a fixed position, while at least the second support arm 126 rotates the X-ray source 122 about the axis 128 relative to the immobilizer unit 104 and compressed breast 102. System 100 captures multiple tomosynthesis projection images of breast 102 at distinct angles of beam 120 relative to breast 102. The imaging system may include an acquisition workstation or technician workstation, which may control the acquisition of the images and may include a display and a user interface for review of the images by a technician. The acquisition workstation may further include a networked computing system that may be connected to a communications network. The technician operating the imaging system may review any acquired images on the display. In addition, the computing system may receive and process the acquired images. Alternatively, the acquired images may be transmitted over a network to another computing system for processing. The acquisition system may then receive and display results of the processing, such as an alert, indicator, or signal.

[0030] Concurrently, and optionally, the image receptor 116 may be tilted relative to the breast support platform 106 and synchronized with the rotation of the second support arm 126. The tilting may be through the same angle as the rotation of the x-ray source 122, or through a different angle selected so that the beam 120 remains in substantially the same position on the image receptor 116 for each of the multiple images. The tilting may be about an axis 130, which may, but need not, be within the imaging plane of the image receptor 116. A tilting mechanism 118 coupled to the image receptor 116 may drive the image receptor 116 in a tilting motion. For tomosynthesis and / or CT imaging, the breast support platform 106 may be horizontal or at an angle to the horizontal, for example, in an orientation similar to that for conventional MLO imaging in mammography. System 100 can be a dedicated mammography system, a dedicated CT system, or a dedicated tomosynthesis system, or a "combo" system capable of performing multiple forms of imaging. An example of such a combo system is promoted by the assignee herein under the trademark Selenia Dimensions.

[0031] When the system is operated, image receptor 116 produces imaging information in response to illumination by imaging beam 120 and provides the imaging information to image processor 132 for processing and generating mammograms. A system control and workstation unit 138, including software, controls the operation of the system and interacts with an operator to receive commands and deliver information, including processed light images.

[0032] Images may be acquired as multiple projections at different angles and thicknesses. Data associated with the multiple projection images may be processed or reconstructed to produce multiple reconstructed images, or "slices." This reconstruction may generally be performed immediately after the image capture sequence. The multiple reconstructed image slices (or data associated with the projection images) may be combined into a single composite image that shows the most relevant clinical information and location of the object of interest. Individual pixels in the final composite image may be mapped to specific image slices. The images may be stored in a data store and can be retrieved for review by a radiologist. The images are then presented to a radiologist who re-identifies objects of interest within the breast, which may require additional analysis to determine whether the identified objects are potentially cancerous or require biopsy or surveillance.

[0033] One challenge with imaging systems 100 is how to immobilize or compress the breast 102 for the desired or required imaging. A medical professional, typically an x-ray technician, generally adjusts the breast 102 within the immobilizer unit 104 while drawing tissue toward the imaging area and moving the compression paddles 108 toward the breast support platform 106 to immobilize the breast 102 and hold it in place with as much breast tissue as practical between the compression surfaces 110, 112. This can cause discomfort to the patient, which can be exacerbated by factors such as the length of time it takes for the x-ray source to sweep to complete the imaging sequence.

[0034] Such discomfort is a frequent cause of patient movement during imaging sequences, potentially resulting in distorted or unusable images. By quickly identifying distorted or potentially distorted images, the usefulness of the images can be immediately assessed. If the sequence needs to be performed again, this can be done immediately before the patient leaves the imaging facility.

[0035] 3 is an example of an artifact 204 in an image 200. Image 200 may be acquired on imaging system 100. Exemplary image 200 may be a reconstructed image slice from a tomosynthesis imaging sequence. In an example, image 200 may be a photographed image of a patient's breast tissue. Image 200 may be a composite or reconstructed image output by image processing of tomosynthesis projection images.

[0036] Image 200 also contains an exemplary high-contrast object 202. High-contrast object 202 appears in focus in exemplary image 200. A high-contrast object is an object that appears against a background of patient tissue with relatively high contrast compared to the background tissue and other objects in the image. The "total contrast" of an image refers to the spectrum of brightness of elements in an image, while "high contrast," as used herein, refers to an image that contains high-brightness elements adjacent to elements with low brightness. In comparison, an image characterized as medium contrast would have a wide range of tones with little variation in brightness between adjacent elements.

[0037] Brightness may be determined according to pixel values ​​associated with a particular element of an image, e.g., an object, compared to pixel values ​​associated with neighboring elements of the image, e.g., the background. Contrast may be understood as the degree of difference between pixel values ​​associated with an object and pixel values ​​associated with the background. High contrast may be understood as the degree of difference meeting or exceeding a predetermined threshold. For example, many computer color palettes contain pixel values ​​ranging from 0 (black) to maximum (white). The predetermined threshold may be a fixed value or a percentage of the entire range. In embodiments, the predetermined threshold may also include a predetermined distance between contrasting pixels. In embodiments, contrast may be evaluated based on a histogram to calculate the distance between the maximum and minimum pixel values. In embodiments, contrast analysis may be limited to a portion of the image, such as a portion of the image nearest a candidate high-contrast object.

[0038] High-contrast objects are generally relatively denser objects within the tissue of the breast. In an embodiment, high-contrast objects may appear in the image due to the presence of naturally occurring objects within the breast, such as calcifications, ligaments, etc. High-contrast objects may appear in the image due to the presence of artificial objects within the breast, such as metal clips or wires that may be implanted following a biopsy or similar procedure. Object 202 may appear as an artifact in other out-of-focus image slices.

[0039] Artifact 204 may represent a different high-contrast object in image 200 than out-of-focus object 202. Artifact 204 may be a shadow cast by a high-contrast object located anywhere within the breast. For example, as discussed above, in tomosynthesis, several images are taken at different projection angles, and these images are then processed to reconstruct an image slice, such as image 200. Therefore, objects in other areas of the breast that are out-of-focus in a particular slice may still cast a shadow and therefore produce an artifact on that particular slice due to the projection angle.

[0040] Artifact 204 appears as an out-of-focus, high-contrast object that extends linearly in the direction of motion of the X-ray source (the Y direction in FIG. 3 ). This extension of the artifact is a function of the angle of projection, which, in some cases, produces different resolution in some directions. For example, artifact 204 may result from a particular projection angle that has relatively lower resolution in the Z direction compared to the X and Y directions. The length of these artifacts may therefore vary with imaging modality. For example, conventional tomosynthesis may use a 15-degree sweep and produce artifacts such as artifact 204, while imaging modalities with wider angles, such as at 20 degrees, 30 degrees, 40 degrees, 50 degrees, 60 degrees, etc., may produce artifacts with smaller, shorter, or otherwise reduced appearance compared to the artifact appearing at 15 degrees. Imaging systems with projection angles of 180 degrees or greater may completely eliminate such artifacts.

[0041] In an embodiment, the physical attributes of the artifact 204 can be identified by evaluating the extension of the artifact 204 away from the center point 206 in each of the X and Y directions. The artifact 204 appears as a straight line extending away from the center point 206 in the direction of the x-ray source motion (the Y direction in FIG. 3). An artifact that appears as a straight line, for example, the absence of artifact deviation in the X direction in FIG. 3, is consistent with the baseline characteristics and indicates no patient movement during image capture.

[0042] 4 is an example image 300 of an artifact 304 in an instance where patient motion is detected. The example image 300 may be a reconstructed image slice from a tomosynthesis imaging sequence. In an example, the image 300 may be a captured image of a patient's breast tissue. The image 300 may be a composite or reconstructed image output by image processing of the tomosynthesis image slice.

[0043] Artifact 304 exhibits significant deviations 308, 310 in the X direction compared to artifact 204 of FIG. 3 , indicating that image capture of this artifact was affected by motion other than that of the X-ray source. Because the X-ray source motion is in the Y direction, as identified in FIG. 4 , any distortion of artifact 304 away from a line parallel to the Y axis indicates motion of the image subject, e.g., the patient or the portion of the patient being imaged. The present disclosure provides systems and methods for performing a comparison between one or more measured attributes associated with an identified artifact and one or more baseline characteristics, and making a determination based on the comparison whether patient motion has occurred. Furthermore, the present disclosure provides systems and methods for determining whether any motion exceeds a threshold beyond which the resulting image may be diagnostically invalid.

[0044] In embodiments, the deviation may be measured as a number of angles, a number of pixels, a unit of length measuring the width of the artifact (e.g., millimeters), the center point of the artifact, the edge of the artifact, the opacity of the artifact, etc. The deviation may be assessed based on the level of contrast between the artifact and the background, or a comparison with an associated high contrast object, e.g., a high contrast object that casts a shadow that results in the artifact.

[0045] 5 illustrates an example workflow or method 400 for detecting motion in an image based on a comparison of detected artifacts to an artifact baseline. Workflow 400 may be implemented by a single integrated system executing one or more models or algorithms, or by a distributed system providing communication between discrete modules. For example, the workflow may be implemented on imaging system 100.

[0046] At 402, image data is acquired. The image data may be acquired using a breast imaging system, for example, by mammography, tomosynthesis, or a combined mammography and tomosynthesis system. Acquiring the image data may include emitting x-ray energy from an x-ray source. The x-ray energy is emitted toward the breast, which is immobilized or compressed by flexible or rigid paddles. Examples of flexible paddles may include those manufactured in part using foam compression element(s), air-filled bladders, etc. The x-ray energy is emitted over a predetermined time period, for example, less than about 0.5 seconds, about 0.4 seconds, or about 0.3 seconds, passes through the paddles, breast, etc., and is received at a detector where the x-ray energy is detected. From this x-ray energy, an x-ray image may be generated. The x-ray image includes objects within the breast and includes at least the imaged breast and artifacts resulting from those objects and tube or patient motion. The image may be acquired as multiple projections at different angles and thicknesses.

[0047] At 404, the image data is processed. Multiple images may be processed or reconstructed to produce multiple reconstructed images, or "slices." This reconstruction may generally be performed immediately after the image capture sequence.

[0048] At 406, a high-contrast object, such as high-contrast object 202 of FIG. 3, is detected. Brightness and contrast may be evaluated according to pixel values ​​associated with the object compared to pixel values ​​associated with the entire background. A background pixel value or range of values ​​may be determined to be the most common pixel value among all pixels of the image. An object may be identified as an image element that deviates from the background pixel value by a predetermined number of pixel values ​​or a percentage of the entire pixel range. A high-contrast object may be identified as an object that deviates from the background pixel value by a greater number of pixel values ​​or a greater percentage of the entire range. In an exemplary pixel range of 0 (black) to 255 (white), background pixel values ​​may range from 0 to 50, and objects may be identified as elements defined by pixels with values ​​above 160, and high-contrast objects may be identified as elements defined by pixels with values ​​above 200.

[0049] In an embodiment, the contrast may be evaluated based on a histogram and the distance between the maximum and minimum pixel values ​​may be calculated. In an embodiment, the contrast analysis may be limited to a portion of the image, such as a portion of the image nearest a candidate high-contrast object.

[0050] Following or as part of the reconstruction, the reconstructed image slices are scanned for the presence of one or more high-contrast objects, such as through the use of image processing algorithms. Some non-limiting examples of image processing algorithms include computer-aided detection (CAD) algorithms, neural network or deep neural network-based image processing algorithms, contrast enhancement algorithms, difference map algorithms, feature and edge detection algorithms, or segmentation algorithms. In embodiments, one or more physical attributes of the high-contrast objects may be cataloged and stored to identify and distinguish the high-contrast object from one or more other high-contrast objects in the image data. Physical attributes may include the size of the high-contrast object, such as length, width, circumference, or diameter; the center point of the high-contrast object; the brightness or sharpness of the high-contrast object; the opacity of the high-contrast object; etc. In some cases, no high-contrast objects may be located. If no high-contrast objects are present in the image set, an alert or indicator may be generated indicating that movement cannot be assessed due to insufficient presence of high-contrast objects. In such a system, breast movement may be detected via other motion detection systems, such as the motion detection system described above.

[0051] At 408, an artifact, such as artifact 204 of FIG. 3 or artifact 304 of FIG. 4, is identified. The artifact may be identified in response to detecting a high-contrast object. For example, when a high-contrast object is located in a particular image slice, it may trigger a scan of the image one or more slices (such as slices in a tomosynthesis stack of images) away from the high-contrast object to find artifacts associated with the high-contrast object, such as shadows cast by the high-contrast object. In an embodiment, the artifact may be identified independently of the high-contrast object.

[0052] At 410, physical attributes of the artifact are measured. The physical attributes may be size, shape, length, width, center point, brightness, definition, etc. For example, artifact 204 of FIG. 3 and artifact 304 of FIG. 4 each have center points 206, 306, and may be measured in the direction of tube movement (Y direction) and in a direction perpendicular to tube movement (X direction) based on the determined center points. In an embodiment, one or more physical attributes of the artifact are measured. In an embodiment, the physical attributes of the artifact may be measured to match the physical attributes of the measured high-contrast object, e.g., the same attributes, the same units, etc.

[0053] At 412, the physical attributes of the artifact are compared to baseline characteristics, and deviations are measured. The baseline characteristics may generally be determined according to a known data set. For example, one or more images may be identified by a radiologist or other clinician as containing an artifact associated with the absence of patient motion. Artifact 204 in FIG. 3 may represent one artifact identified as suitable for inclusion in a data set for determining baseline characteristics. One or more images may be used to form a training set for determining baseline shapes, sizes, etc. of artifacts associated with the absence of patient motion. Baseline values ​​or ranges for one or more baseline characteristics may be determined from the training set.

[0054] In an embodiment, determining the baseline may include performing a coefficient of determination or another fitting analysis to determine a baseline range, e.g., a range of deviations occurring between artifacts that do not indicate patient motion. Some differences between artifacts that do not indicate patient motion may exist due to, for example, high-contrast objects of different sizes and orientations producing artifacts with similarly different sizes and orientations. Therefore, in an embodiment, the baseline characteristics may incorporate a range to encompass deviations from a straight line in the direction of x-ray source motion.

[0055] The baseline characteristics may be determined according to a relationship between a physical attribute of the artifact and a physical attribute of the corresponding high-contrast object, for example, a measure of the difference in width between the high-contrast object and the artifact.

[0056] Once determined, the baseline characteristics may be stored and used as a reference for comparison. The detected artifact is compared to the baseline, and a deviation of the detected artifact from the baseline is measured. The deviation may be measured using a coefficient of determination or another fitting analysis to determine a measure of deviation from the baseline due to the detected artifact. Measuring the deviation from the baseline may include applying a fitting algorithm. The fitting algorithm may accept and consider as input one or more of the size of the artifact, the size of the associated high-contrast object, and the contrast of the artifact.

[0057] At 414, the deviation is evaluated against a predetermined threshold. The predetermined threshold may be determined according to the baseline and one or more alert or indicator training images. For example, in addition to the baseline determination discussed above, threshold determination may also be performed. The threshold determination may include evaluation of one or more training images with artifacts identified as indicative of patient motion. Thus, both a baseline range, i.e., an amount of deviation below which indicates an absence of patient movement, and a threshold deviation above which indicates patient motion, may be identified.

[0058] In an example, the threshold deviation may be set to a value immediately adjacent to the baseline range so that all images evaluated are determined to have either patient motion or the absence of patient motion. In an example, the threshold deviation may be offset from the baseline range. For example, one or more deviation values ​​may lie between the baseline range and the threshold deviation so that images may be evaluated as having motion, having the absence of motion, or being unclear.

[0059] In examples, the predetermined threshold may be dynamic and based on feedback from a radiologist or other technician evaluating the image data. For example, the workflow may further include receiving one or more indications of a false positive. One or both of the baseline range and the threshold deviation may be adjusted according to the feedback to require more deviation to trigger a determination that the image exhibits patient motion.

[0060] For example, artifact 204 of FIG. 3 and artifact 304 of FIG. 4 each have a center point 206, 306, and based on the determined center point, measurements can be taken in the direction of tube movement (Y direction) and in a direction perpendicular to tube movement (X direction). In an embodiment, measurements in the Y direction can be used to determine two or more locations for measurements in the X direction. Taking two or more measurements in the X direction on artifact 204 reveals that a uniform distance from center point 206 along the length of artifact 204 falls within a baseline range, indicating an absence of movement. Taking two or more measurements in the X direction on artifact 304 reveals deviations 308, 310 indicating movement. In an embodiment, either or both deviations 308, 310 can be compared to a threshold deviation. A difference can be determined between deviations 308, 310, and the difference can be compared to the threshold deviation. At 416, if the deviation exceeds a predetermined threshold, a motion indicator is generated. In examples, the motion indicator may be generated in conjunction with image reconstruction so that the radiologist or technologist is alerted to immediately evaluate the image for usefulness. In examples, the motion indicator may be a flag or other indicator on the image, or a visual, auditory, tactile, etc., alert on a technologist or operator panel. The motion indicator may be displayed to the technician on a display. The technician may evaluate the acquired images and determine whether a retake is required. In other cases, the motion indicator may be stored with the generated images and can be viewed or processed at a later time. In other cases, the motion indicator may interrupt the imaging sequence and indicate to the technician to initiate a retake. In still other cases, the imaging system may determine whether to remove images that exhibit excess motion.

[0061] At 418, if the deviation does not exceed a predetermined threshold, an indication of absence of motion may be generated. In embodiments, the indicator of absence of motion may be a visual or audible indicator that the image is acceptable. The indicator of absence of motion may include the system processing and storing the image without an explicit alert to the operator. In these cases, an indicator that no motion has occurred may be stored in association with the image(s) to be viewed or processed at a later time.

[0062] In an embodiment, workflow 400 may be implemented as one or more algorithms or modules. For example, a first algorithm may be implemented to detect high-contrast objects. A second algorithm, which may be informed by the first algorithm, may identify artifacts associated with the high-contrast objects. Execution of a third algorithm may be performed to evaluate artifact deviations compared to predetermined thresholds and generate appropriate alerts.

[0063] 6 illustrates one example of a suitable operating environment 500 in which one or more of the present embodiments can be implemented. This operating environment may be incorporated directly into the imaging system disclosed herein, or may be incorporated into a computer system that is separate from the imaging and compression systems described herein but is used to control those systems. This is only one example of a suitable operating environment and is not intended to suggest any limitations on the scope of use or functionality. Other well-known computing systems, environments, and / or configurations that may be suitable for use include, but are not limited to, imaging systems, personal computers, server computers, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, programmable consumer electronics devices such as smartphones, network PCs, minicomputers, mainframe computers, tablets, distributed computing environments that include any of the above systems or devices, and the like.

[0064] In its most basic configuration, operating environment 500 typically includes at least one processing unit 502 and memory 504. Depending on the exact configuration and type of computing device, memory 504 (which stores instructions for, among other things, identifying high-contrast objects and artifacts, associating artifacts with corresponding high-contrast objects (or vice versa), measuring one or more attributes of the high-contrast objects and / or artifacts, determining baseline characteristics of the artifacts, measuring artifact deviations, or performing other methods disclosed herein) can be volatile (such as RAM), non-volatile (such as ROM, flash memory), or some combination of the two. This most basic configuration is illustrated in FIG. 6 by dashed line 506. Additionally, environment 500 can also include storage devices (removable 508 and / or non-removable 510), including, without limitation, magnetic or optical disks or tape. Similarly, the environment 500 may also have input device(s) 514, such as a touch screen, keyboard, mouse, pen, voice input, etc., and / or output device(s) 516, such as a display, speakers, printer, etc. Also included within the environment may be one or more communication connections 512, such as a LAN, WAN, point-to-point, Bluetooth, RF, etc.

[0065] The operating environment 500 typically includes at least some form of computer-readable media. Computer-readable media can be any available media that can be accessed by the processing unit 502 or other devices having the operating environment. By way of example, and not limitation, computer-readable media can include computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVDs) or other optical storage devices, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, solid-state storage devices, or any other tangible medium that can be used to store the desired information. Communication media embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery media. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. Combinations of any of the above should also be included within the scope of computer-readable media. A computer-readable device is a hardware device that incorporates a computer storage medium.

[0066] Operating environment 500 can be a single computer operating in a networked environment using logical connections to one or more remote computers. The remote computers can be personal computers, servers, routers, network PCs, peer devices, or other common network nodes, and typically include many or all of the elements described above, as well as others not so mentioned. The logical connections can include any method supported by available communications media. Such networked environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet.

[0067] In some embodiments, the components described herein include such modules or instructions executable by computer system 500, which can be stored on computer storage media and other tangible media and transmitted within communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for the storage of information such as computer-readable instructions, data structures, program modules, or other data. Combinations of any of the above should also be included within the scope of readable media. In some embodiments, computer system 500 is part of a network that stores data in remote storage media for use by computer system 500.

[0068] In embodiments, the various systems and methods disclosed herein may be implemented by one or more server devices. For example, in one embodiment, a single server may be employed to implement the systems and methods disclosed herein, such as the methods for imaging discussed herein. The client device 502 may interact with the server over a network. In further embodiments, the client device 502 may also perform functions disclosed herein, such as scanning and image processing, which may then be provided to one or more servers. [Example]

[0069] Example

[0070] Illustrative examples of the systems and methods described herein are provided below. Embodiments of the systems or methods described herein may include any one or more of the following notes, and any combination thereof:

[0071] Supplementary Note 1. A method for detecting motion of a patient's breast tissue during medical imaging, the method including: acquiring image data of the patient's breast tissue; processing the image data to generate a set of image slices that collectively depict the patient's breast tissue; detecting a high contrast object on one or more image slices of the set of image slices; identifying an artifact associated with the high contrast object on the one or more image slices of the set of image slices; measuring physical attributes of the artifact; measuring a deviation of the physical attribute from a baseline; determining that the deviation exceeds a predetermined threshold; and generating a motion indicator in response to determining that the deviation exceeds the predetermined threshold.

[0072] Appendix 2. The method of Appendix 1, wherein the baseline is a straight line.

[0073] Appendix 3. The method of Appendix 1 or 2, wherein the baseline further comprises a baseline range.

[0074] Appendix 4. The method of any of Appendixes 1-3, wherein the baseline range is determined according to a set of physical attributes associated with one or more artifacts.

[0075] Clause 5. The method of clause 4, wherein the one or more artifacts are associated with an absence of patient movement.

[0076] Appendix 6. The method of any of Appendixes 1-5, wherein the predetermined threshold is determined according to a baseline range.

[0077] Appendix 7. The method of any of Appendixes 1-6, wherein the baseline range is measured using coefficient of determination analysis.

[0078] Appendix 8. The method of any of Appendixes 1-7, wherein the high contrast object is identified on an in-focus image slice and the artifact is a projection of the high contrast object identified on an out-of-focus image slice.

[0079] Appendix 9. The method of any of Appendixes 1-8, wherein detecting the high contrast object includes identifying at least one high contrast object in a first image slice and, in response, scanning a second image slice one or more slices away from the first image slice for artifacts.

[0080] Addendum 10. The method of any of Addendums 1-9, wherein the physical attributes include one or more of width, length, height, trajectory, and opacity.

[0081] Appendix 11. The method of Appendix 10, wherein determining that the deviation exceeds a predetermined threshold is based on measuring a physical attribute associated with the artifact and measuring at least one high-contrast object.

[0082] Appendix 12. The method of any of Appendixes 1-11, wherein measuring deviation from the baseline includes applying a fitting algorithm, and inputs to the fitting algorithm include one or more of: size of the artifact, size of an associated high-contrast object, and contrast of the artifact.

[0083] Appendix 13. The method of any of Appendixes 1-12, wherein the high contrast object is a naturally occurring object in the breast, including one or more of a calcification or a ligament.

[0084] Addendum 14. The method of any of Addendums 1-13, wherein the high-contrast object is an embedded object.

[0085] Addendum 15. The method of any of Addendums 1-14, wherein the motion indicator includes an indicator on at least one image of the one or more image slices.

[0086] Addendum 16. The method of any of Addendums 1-15, wherein the motion indicator includes a request for immediate review of at least one image of the one or more images.

[0087] Clause 17. The method of any of clauses 1-16, wherein measuring deviations from baseline associated with artifacts includes using coefficient of determination analysis.

[0088] Appendix 18. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein, when the one or more processors execute the executable instructions, the one or more processors perform the following actions: acquire image data of a patient's breast tissue; process the image data to generate a set of image slices that collectively depict the patient's breast tissue; detect high-contrast objects on one or more image slices of the set of image slices; identify artifacts associated with the high-contrast objects on the one or more image slices of the set of image slices; measure physical attributes of the artifacts; measure a deviation of the physical attributes from a baseline; determine that the deviation exceeds a predetermined threshold; and generate a motion indicator in response to determining that the deviation exceeds the predetermined threshold.

[0089] Appendix 19. A non-transitory computer-readable medium having stored thereon one or more sequences of instructions to cause one or more processors to acquire image data of a patient's breast tissue; process the image data to generate a set of image slices that collectively depict the patient's breast tissue; detect a high contrast object on one or more image slices of the set of image slices; identify an artifact associated with the high contrast object on the one or more image slices of the set of image slices; measure a physical attribute of the artifact; measure a deviation of the physical attribute from a baseline; determine that the deviation exceeds a predetermined threshold; and generate a motion indicator in response to determining that the deviation exceeds the predetermined threshold.

[0090] This disclosure has described several embodiments of the present technology with reference to the accompanying drawings, which illustrate only a few of the possible embodiments. However, other aspects may be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of possible embodiments to those skilled in the art.

[0091] While various embodiments and examples are described herein, those skilled in the art will understand that many modifications may be made thereto within the scope of the present disclosure. Therefore, specific structures, acts, or mediums are disclosed only as illustrative examples. Examples in accordance with the present technology may also combine elements or components that are generally disclosed but not explicitly illustrated in combination, unless otherwise stated herein. Therefore, it is not intended that the scope of the present disclosure be limited in any way by the examples provided.

Claims

1. 1. A method for detecting breast tissue motion in a patient during medical imaging, the method comprising: acquiring image data of breast tissue of the patient; processing the image data to generate a set of image slices that collectively depict breast tissue of the patient; detecting a high contrast object on one or more image slices of the set of image slices; identifying an artifact associated with the high contrast object on one or more image slices of the set of image slices; measuring a physical attribute of the artifact; measuring deviations of said physical attributes from a baseline; determining that the deviation exceeds a predetermined threshold; generating a motion indicator in response to determining that the deviation exceeds the predetermined threshold; and A method comprising:

2. The method of claim 1 , wherein the baseline is a straight line.

3. The method of claim 1 or 2, wherein the baseline further comprises a baseline range.

4. The method of any of claims 1-3, wherein the baseline range is determined according to a set of physical attributes associated with one or more artifacts.

5. The method of claim 4 , wherein the one or more artifacts are associated with an absence of patient movement.

6. The method according to any one of claims 1 to 5, wherein the predetermined threshold is determined according to the baseline range.

7. The method of any of claims 1-6, wherein the baseline range is determined using coefficient of determination analysis.

8. The method of any of claims 1-7, wherein the high contrast object is identified on an in-focus image slice and the artifact is a projection of the high contrast object identified on an out-of-focus image slice.

9. 9. The method of claim 1, wherein detecting a high-contrast object comprises identifying at least one high-contrast object in a first image slice, and in response, scanning a second image slice one or more slices away from the first image slice for the artifact.

10. The method of any of claims 1-9, wherein the physical attributes include one or more of width, length, height, trajectory, and opacity.

11. The method of claim 10 , wherein determining that the deviation exceeds a predetermined threshold is based on measuring the physical attribute associated with the artifact and measuring the at least one high-contrast object.

12. 12. The method of claim 1, wherein measuring the deviation from the baseline comprises applying a fitting algorithm, and inputs to the fitting algorithm include one or more of the size of the artifact, the size of the associated high-contrast object, and the contrast of the artifact.

13. The method of any of claims 1-12, wherein the high contrast objects are naturally occurring objects within the breast including one or more of the following: calcifications or ligaments.

14. The method of any of claims 1-13, wherein the high contrast object is an embedded object.

15. The method of any preceding claim, wherein the motion indicator comprises an indicator on at least one image of the one or more image slices.

16. The method of any preceding claim, wherein the motion indicator comprises a request for immediate review of at least one of the one or more images.

17. The method of any preceding claim, wherein determining the deviation from the baseline associated with the artifact comprises using a coefficient of determination analysis.

18. 1. A system comprising: a computer-readable memory storing executable instructions; one or more processors in communication with the computer-readable memory; Equipped with When the one or more processors execute the executable instructions, the one or more processors: acquiring image data of breast tissue of the patient; processing the image data to generate a set of image slices that collectively depict breast tissue of the patient; detecting a high contrast object on one or more image slices of the set of image slices; identifying an artifact associated with the high contrast object on one or more image slices of the set of image slices; measuring a physical attribute of the artifact; measuring deviations of said physical attributes from a baseline; determining that the deviation exceeds a predetermined threshold; generating a motion indicator in response to determining that the deviation exceeds the predetermined threshold; and A system that implements the above.

19. A non-transitory computer-readable medium, the non-transitory computer-readable medium configured to: acquiring image data of breast tissue of the patient; processing the image data to generate a set of image slices that collectively depict breast tissue of the patient; detecting a high contrast object on one or more image slices of the set of image slices; identifying an artifact associated with the high contrast object on one or more image slices of the set of image slices; measuring a physical attribute of the artifact; measuring deviations of said physical attributes from a baseline; determining that the deviation exceeds a predetermined threshold; generating a motion indicator in response to determining that the deviation exceeds the predetermined threshold; and 10. A non-transitory computer-readable medium having stored thereon one or more sequences of instructions for carrying out the method of claim 10.

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