Patent Description:
The field generally relates to techniques for reconstructing cardiac frequency phenomena within an angiographic study, and in particular, to techniques that utilize bandpass filters and/or amplification to isolate and/or magnify the cardiac frequency phenomena within an angiographic study.

To obtain an angiogram, a bolus of a chemical contrast agent is injected intravascularly into a patient, and a sequence or time series of x-rays is obtained. Two-dimensional projections of the anatomy of the vascular system are captured as the chemical contrast agent, which blocks the passage of x-rays, passes through the vascular system in the x-ray projection path. The aggregation of these images sequenced according to time of acquisition comprises an angiogram.

As described in <CIT> (hereinafter "the '<NUM> patent"), fluoroscopic angiographic imaging captures and quantifies cardiac frequency phenomena allowing spatiotemporal reconstruction of a moving vascular pulse wave in the brain and other organs using wavelets for processing the angiographic data. This technique allows for visualization of blood flow as a sequence of arterial stroke volumes, through the capillary bed and as a sequence of venous pulse volumes of reciprocal cardiac phase. Thus, the spatial and temporal distribution of cardiac frequency phenomena in blood flow provides physiological, diagnostic and medical information that may be shown in cine images of an angiogram.

While the above described technique provides a spatiotemporal reconstruction of a moving vascular pulse wave in the brain and other organs, it is desirable to develop other methods for reconstructing the cardiac frequency phenomena within an angiographic study so as to provide for greater flexibility to existing techniques.

Attention is drawn to <CIT>, describing a method of extracting a spatiotemporal reconstruction of the cardiac frequency phenomena present in an angiogram obtained at faster than cardiac frequency and applying a wavelet transform to each of the pixel-wise time signals of the angiogram. If there is motion alias then instead a high frequency resolution wavelet transform of the overall angiographic time intensity curve is cross-correlated to high temporal resolution wavelet transforms of the pixel-wise time signals. The result is filtered for cardiac wavelet scale then pixel-wise inverse wavelet transformed, giving a complex-valued spatiotemporal grid of cardiac frequency angiographic phenomena.

Further attention is drawn to <CIT>, describing a method for visualization of electrophysiology information that can include storing electroanatomic data in memory, the electroanatomic data representing electrical activity on an anatomic region within a patient's body over a time period. An interval within the time period is selected in response to a user selection. A visual representation of physiological information for the user selected interval can be generated by applying at least one analysis method to the electroanatomic data. The visual representation can spatially represented on a graphical representation of the anatomic region within the patient's body.

Further attention is drawn to <CIT>, describing a method of extracting a spatiotemporal reconstruction of the cardiac frequency phenomena present in an angiogram obtained at faster than cardiac frequency. A wavelet transform is applied to each of the pixel-wise time signals of the angiogram. If there is motion alias then instead a high frequency resolution wavelet transform of the overall angiographic time intensity curve is cross-correlated to high temporal resolution wavelet transforms of the pixel-wise time signals. The result is filtered for cardiac wavelet scale then pixel-wise inverse wavelet transformed. This gives a complex-valued spatiotemporal grid of cardiac frequency angiographic phenomena.

In accordance with the present invention a method, an angiographic system and a computer program, as set forth in the independent claims, respectively, are provided. Embodiments of the invention are directed to methods, systems, and computer readable media for reconstructing cardiac frequency phenomena in angiographic data that do not utilize wavelets, and in particular Gabor wavelets, for processing angiographic data.

A system, method, and computer readable for extracting cardiac frequency angiographic phenomena from an angiographic study obtained at a rate faster than cardiac frequency is provided. Angiographic data is obtained or received from an angiographic study obtained at a rate faster than cardiac frequency and a cardiac frequency bandpass filter is applied to the angiographic data to output a spatiotemporal reconstruction of cardiac frequency angiographic phenomena, which may then be displayed in one or more images.

In accordance with another aspect, a Eulerian magnification may be applied to the angiographic data in order to yield an amplified effect. The Eulerian magnification may be applied to angiographic images in order to select for those with temporal and spatial phenomena of interest, including temporal phenomena corresponding to the cardiac frequency band.

In accordance with another aspect, applying the cardiac frequency bandpass filter extracts the cardiac frequency angiographic phenomena from a cine sequence of angiographic images.

In accordance with another aspect, applying the cardiac frequency bandpass filter further comprises processing time samples of each pixel in the angiographic images as a separate signal, and applying the cardiac frequency bandpass filter to the pixel-wise signals.

In accordance with another aspect, a contemporaneously measured cardiac signal is obtained and the contemporaneously measured cardiac signal is used as a cross correlation target to provide a bandpass cardiac frequency filter limited in range by the frequency of the measured cardiac signal.

In accordance with another aspect, the cardiac frequency band pass filter comprises one of a real valued filter that is rendered in image form using grayscale, or a complex valued filter that is rendered in image form based on a cardiac frequency magnitude and a cardiac frequency phase.

In accordance with another aspect, applying the Eulerian magnification comprises applying a spatial decomposition to a sequence of angiographic images, applying a temporal filter to the spatially decomposed sequence of angiographic images, selectively magnifying one or more of the dual spatially decomposed and temporally filtered sequence of angiographic images, and reassembling the selectively magnified sequence of angiographic images with the sequence of angiographic images into a combined sequence of angiographic images to allow visualization of an amplified spatiotemporal reconstruction.

In accordance with another aspect, applying the spatial decomposition further comprises performing multiscale anisotropic filtering or applying a spatial transformation comprising one of shearlets or ridgelets.

In accordance with another aspect, angiographic images with temporal and spatial phenomena of interest are selected, including temporal phenomena corresponding to a cardiac frequency band.

In accordance with another aspect, applying the spatial decomposition comprises performing a spatial decomposition of an angiographic image into several images each with different spatial characteristics, including filtering for spatial structures of specific spatial frequencies.

In accordance with another aspect, the cardiac frequency bandpass filter is applied with a value of zero for temporal phenomena outside of the cardiac frequency band, and angiographic images are reconstructed including the cardiac frequency phenomena with magnified spatial translations.

Still other objects and advantages of these techniques will be apparent from the specification and drawings.

The drawings illustrate preferred embodiments presently contemplated for carrying out aspects of the invention. In the drawings:.

Methods, systems and computer readable media for reconstructing cardiac frequency phenomena in angiographic data that do not rely on wavelets for spatiotemporal reconstruction are provided. A sequence of angiographic images (i.e., two dimensional projection images) is acquired at faster than cardiac rate and processed to provide a spatiotemporal reconstruction of moving vascular pulse waves. To generate the spatiotemporal reconstruction of moving vascular pulse waves, a cardiac frequency bandpass filter may be applied to the angiographic data, in some aspects with Eulerian magnification and amplification, to generate a spatiotemporal reconstruction of cardiac frequency angiographic phenomena. These techniques are described in additional detail below.

Referring to <FIG>, exemplary systems or devices that may be employed for carrying out embodiments of the invention are illustrated. It is understood that such systems and devices are only exemplary of representative systems and devices and that other hardware and software configurations are suitable for use with present techniques.

For reconstructing a moving vascular pulse wave, raw data is acquired via a fluoroscopic angiogram imaging system at a rate higher than cardiac frequency (e.g., images may be acquired at a rate up to <NUM>). In aspects, and according to the Nyqvist Sampling Theorem, images are acquired by the system at over twice as fast as the highest frequency component of the cardiac signal. Given an angiogram obtained at faster than cardiac rate, the images may be processed according to the techniques provided herein to generate a time varying spatial reconstruction of the cardiac frequency angiographic phenomena.

Referring first to <FIG> and <FIG>, a rotational x-ray system <NUM> is illustrated that may be employed for obtaining an angiogram at faster than cardiac rate, such as via fluoroscopic angiography. As previously described, in acquiring an angiogram, a chemical contrast agent is injected into the patient positioned between an x-ray source and detector, and x-ray projections are captured by the x-ray detector as a two-dimensional image. A sequence of two dimensional projection images comprises an angiographic study, with the angiographic image frames acquired at faster than cardiac frequency to allow spatiotemporal reconstruction of the cardiac frequency phenomena into a cardiac space angiogram.

As shown in <FIG>, an example of an angiogram imaging system is shown in the form of a rotational x-ray system <NUM> including a gantry having a C-arm <NUM> which carries an x-ray source assembly <NUM> on one of its ends and an x-ray detector array assembly <NUM> at its other end. The gantry enables the x-ray source <NUM> and detector <NUM> to be oriented in different positions and angles around a patient disposed on a table <NUM>, while providing to a physician access to the patient. The gantry includes a pedestal <NUM> which has a horizontal leg <NUM> that extends beneath the table <NUM> and a vertical leg <NUM> that extends upward at the end of the horizontal leg <NUM> that is spaced apart from table <NUM>. A support arm <NUM> is rotatably fastened to the upper end of vertical leg <NUM> for rotation about a horizontal pivot axis <NUM>.

The pivot axis <NUM> is aligned with the centerline of the table <NUM>, and the arm <NUM> extends radially outward from the pivot axis <NUM> to support a C-arm drive assembly <NUM> on its outer end. The C-arm <NUM> is slidably fastened to the drive assembly <NUM> and is coupled to a drive motor (not shown) which slides the C-arm <NUM> to revolve about a C-axis <NUM> as indicated by arrows <NUM>. The pivot axis <NUM> and C-axis <NUM> intersect each other, at an isocenter <NUM> located above the table <NUM>, and are perpendicular to each other.

The x-ray source assembly <NUM> is mounted to one end of the C-arm <NUM> and the detector array assembly <NUM> is mounted to its other end. The x-ray source assembly <NUM> emits a beam of x-rays which are directed at the detector array assembly <NUM>. Both assemblies <NUM> and <NUM> extend radially inward to the pivot axis <NUM> such that the center ray of this beam passes through the system isocenter <NUM>. The center ray of the beam thus can be rotated about the system isocenter around either the pivot axis <NUM> or the C-axis <NUM>, or both, during the acquisition of x-ray attenuation data from a subject placed on the table <NUM>.

The x-ray source assembly <NUM> contains an x-ray source which emits a beam of x-rays when energized. The center ray passes through the system isocenter <NUM> and impinges on a two-dimensional flat panel digital detector <NUM> housed in the detector assembly <NUM>. The detector <NUM> may be, for example, a <NUM> x <NUM> element two- dimensional array of detector elements. Each element produces an electrical signal that represents the intensity of an impinging x-ray and hence the attenuation of the x-ray as it passes through the patient. During a scan, the x-ray source assembly <NUM> and detector array assembly <NUM> are rotated about the system isocenter <NUM> to acquire x-ray attenuation projection data from different angles. In some aspects, the detector array is able to acquire <NUM> projections, or views, per second which is the limiting factor that determines how many views can be acquired for a prescribed scan path and speed.

Referring to <FIG>, the rotation of the assemblies <NUM> and <NUM> and the operation of the x-ray source are governed by a control mechanism <NUM> of the x-ray system. The control mechanism <NUM> includes an x-ray controller <NUM> that provides power and timing signals to the x-ray source <NUM>. A data acquisition system (DAS) <NUM> in the control mechanism <NUM> samples data from detector elements and passes the data to an image reconstructor <NUM>. The image reconstructor <NUM> receives digitized x-ray data from the DAS <NUM> and performs high speed image reconstruction according to the methods of the present disclosure. The reconstructed image is applied as an input to a computer <NUM> which stores the image in a mass storage device <NUM> or processes the image further.

The control mechanism <NUM> also includes gantry motor controller <NUM> and a C-axis motor controller <NUM>. In response to motion commands from the computer <NUM>, the motor controllers <NUM> and <NUM> provide power to motors in the x-ray system that produce the rotations about respective pivot axis <NUM> and C-axis <NUM>. The computer <NUM> also receives commands and scanning parameters from an operator via console <NUM> that has a keyboard and other manually operable controls. An associated display <NUM> allows the operator to observe the reconstructed image and other data from the computer <NUM>. The operator supplied commands are used by the computer <NUM> under the direction of stored programs to provide control signals and information to the DAS <NUM>, the x-ray controller <NUM> and the motor controllers <NUM> and <NUM>. In addition, computer <NUM> operates a table motor controller <NUM> which controls the motorized table <NUM> to position the patient with respect to the system isocenter <NUM>.

Referring now to <FIG>, a block diagram of a computer system or information processing device <NUM> (e.g., computer <NUM> in <FIG>) is illustrated that may be incorporated into an angiographic imaging system, such as the rotational x-ray system <NUM> of <FIG> and <FIG>, to provide enhanced functionality or used as a standalone device for the extraction of cardiac frequency phenomena from angiographic data according to an embodiment of the present invention. In one embodiment, computer system <NUM> includes monitor or display <NUM>, computer <NUM> (which includes processor(s) <NUM>, bus subsystem <NUM>, memory subsystem <NUM>, and disk subsystem <NUM>), user output devices <NUM>, user input devices <NUM>, and communications interface <NUM>. Monitor <NUM> can include hardware and/or software elements configured to generate visual representations or displays of information. Some examples of monitor <NUM> may include familiar display devices, such as a television monitor, a cathode ray tube (CRT), a liquid crystal display (LCD), or the like. In some embodiments, monitor <NUM> may provide an input interface, such as incorporating touch screen technologies.

Computer <NUM> can include familiar computer components, such as one or more central processing units (CPUs), memories or storage devices, graphics processing units (GPUs), communication systems, interface cards, or the like. As shown in <FIG>, computer <NUM> may include one or more processor(s) <NUM> that communicate with a number of peripheral devices via bus subsystem <NUM>. Processor(s) <NUM> may include commercially available central processing units or the like. Bus subsystem <NUM> can include mechanisms for letting the various components and subsystems of computer <NUM> communicate with each other as intended. Although bus subsystem <NUM> is shown schematically as a single bus, alternative embodiments of the bus subsystem may utilize multiple bus subsystems. Peripheral devices that communicate with processor(s) <NUM> may include memory subsystem <NUM>, disk subsystem <NUM>, user output devices <NUM>, user input devices <NUM>, communications interface <NUM>, or the like.

Memory subsystem <NUM> and disk subsystem <NUM> are examples of physical storage media configured to store data. Memory subsystem <NUM> may include a number of memories including random access memory (RAM) for volatile storage of program code, instructions, and data during program execution and read only memory (ROM) in which fixed program code, instructions, and data are stored. Disk subsystem <NUM> may include a number of file storage systems providing persistent (non-volatile) storage for programs and data. Other types of physical storage media include floppy disks, removable hard disks, optical storage media such as CD-ROMS, DVDs and bar codes, semiconductor memories such as flash memories, read-only-memories (ROMS), battery-backed volatile memories, networked storage devices, or the like. Memory subsystem <NUM> and disk subsystem <NUM> may be configured to store programming and data constructs that provide functionality or features of techniques discussed herein. Software code modules and/or processor instructions that when executed by processor(s) <NUM> implement or otherwise provide the functionality may be stored in memory subsystem <NUM> and disk subsystem <NUM>.

User input devices <NUM> can include hardware and/or software elements configured to receive input from a user for processing by components of computer system <NUM>. User input devices can include all possible types of devices and mechanisms for inputting information to computer system <NUM>. These may include a keyboard, a keypad, a touch screen, a touch interface incorporated into a display, audio input devices such as microphones and voice recognition systems, and other types of input devices. In various embodiments, user input devices <NUM> can be embodied as a computer mouse, a trackball, a track pad, a joystick, a wireless remote, a drawing tablet, a voice command system, an eye tracking system, or the like. In some embodiments, user input devices <NUM> are configured to allow a user to select or otherwise interact with objects, icons, text, or the like that may appear on monitor <NUM> via a command, motions, or gestures, such as a click of a button or the like.

User output devices <NUM> can include hardware and/or software elements configured to output information to a user from components of computer system <NUM>. User output devices can include all possible types of devices and mechanisms for outputting information from computer <NUM>. These may include a display (e.g., monitor <NUM>), a printer, a touch or force-feedback device, audio output devices, or the like.

Communications interface <NUM> can include hardware and/or software elements configured to provide unidirectional or bidirectional communication with other devices.

For example, communications interface <NUM> may provide an interface between computer <NUM> and other communication networks and devices, such as via an internet connection.

According to embodiments of the invention, it is recognized that, in addition to acquiring angiographic images, additional cardiac signals/data may be contemporaneously acquired to serve as a cross correlation target, for purposes of performing the spatiotemporal reconstruction of the vascular pulse waves based on the techniques provided herein. For example, the cardiac signals/data may serve as a reference cardiac signal for phase indexing pixels in the angiographic projections. <FIG> and <FIG> illustrate exemplary devices for acquiring/providing a reference cardiac signal with such devices/systems in the form of a pulse oximetry system and/or an echocardiogram (EKG) system or device.

<FIG> is a perspective view of an example of a suitable pulse oximetry system <NUM> that includes a sensor <NUM> and a pulse oximetry monitor <NUM>. The sensor <NUM> includes an emitter <NUM> for emitting light at certain wavelengths into a patient's tissue and a detector <NUM> for detecting the light after it is reflected and/or absorbed by the patient's tissue. The monitor <NUM> may be capable of calculating physiological characteristics received from the sensor <NUM> relating to light emission and detection. Further, the monitor <NUM> includes a display <NUM> capable of displaying the physiological characteristics and/or other information about the system. The sensor <NUM> is shown communicatively coupled to the monitor <NUM> via a cable <NUM>, but alternatively may be communicatively coupled via a wireless transmission device or the like. In the illustrated embodiment the pulse oximetry system <NUM> also includes a multi-parameter patient monitor <NUM>. In addition to the monitor <NUM>, or alternatively, the multi-parameter patient monitor <NUM> may be capable of calculating physiological characteristics and providing a central display <NUM> for information from the monitor <NUM> and from other medical monitoring devices or systems. For example, the multi-parameter patient monitor <NUM> may display a patient's SpO<NUM> and pulse rate information from the monitor <NUM> and blood pressure from a blood pressure monitor on the display <NUM>. In another embodiment, computer system <NUM> may be configured to include hardware and software for communicating with a pulse oximetry sensor, such as the sensor <NUM> shown in <FIG>, as well as hardware and software to calculate physiological characteristics received from the pulse oximetry sensor and utilize such characteristics to extract cardiac frequency phenomena, and display the same, in accordance with the techniques described herein.

<FIG> is a schematic diagram of an electrocardiogram ("EKG") device <NUM> shown optionally connected to an information management system <NUM> through a communications link <NUM>. A commonly used device for acquiring an EKG is a <NUM>-lead electrocardiograph. The EKG device <NUM> and the information management system <NUM> receives power <NUM> from an external source. Among other things, the information management system <NUM> includes a central processing unit <NUM> connected to a memory unit, or database <NUM>, via a data link <NUM>. The CPU <NUM> processes data and is connected to an output, such as printer <NUM> and/or display <NUM>. Alternatively, the electrocardiogram (EKG) device <NUM> can be connected directly to a printer <NUM> or display <NUM> through communications link <NUM>, if the optional information management system <NUM> is not utilized. The software program according to embodiments provided herein may reside in either the EKG device <NUM>, the information management system <NUM>, or another device associated to receive signals from the EKG device <NUM>. The EKG device <NUM> is connected to a plurality of patient lead wires <NUM>, each having an electrode <NUM> to receive EKG signals from a patient <NUM> in a known manner. The EKG device <NUM> has a signal conditioner <NUM> that receives the EKG signals and filters noise, sets thresholds, segregates signals, and provides the appropriate number of EKG signals for the number of leads <NUM> to an A/D converter <NUM> which converts the analog signals to digital signals for processing by a microcontroller <NUM>, or any other type of processing unit. Microcontroller <NUM> is connected to a memory unit <NUM>, similar to memory unit <NUM>, or any other computer readable storage medium. In another embodiment, computer system <NUM> may be configured to include hardware and software for communicating with EKG electrodes, such as electrodes <NUM> shown in <FIG>, as well as hardware and software to calculate physiological characteristics received from the electrodes and utilize such characteristics to extract cardiac frequency phenomena, and display the same, in accordance with the techniques described herein.

As previously indicated, present embodiments are directed to systems, methods, and computer readable media for reconstructing cardiac frequency phenomena in angiographic data. A sequence of angiographic images (i.e., two dimensional projection images) is acquired at faster than cardiac rate (such as via the system of <FIG>, <FIG>) and analyzed (such as via the system of <FIG>) to provide a spatiotemporal reconstruction (e.g., as described in the '<NUM> patent) of moving vascular pulse waves utilizing the bandpass filtering and amplification techniques provided herein.

In some aspects, the spatiotemporal reconstructions are complex valued data of the same dimensionality as the projection, and each pixel at each time point has a complex valued datum. It may be represented as a real number and an imaginary number. For physiological interpretation, however, it is represented in polar form with magnitude and a phase. In aspects, the magnitude represents the variation of contrast in a given pixel at cardiac frequency, and the phase represents the phase relative to the cardiac cycle.

While the '<NUM> patent uses a wavelet transform for yielding a time varying extraction of the cardiac frequency angiographic phenomena (i.e., the wavelet transform being applied to each of the pixel-wise time signals of the angiogram), it will be appreciated that other methods could be utilized for yielding the time varying extraction of the cardiac frequency angiographic phenomena.

<FIG> are flowcharts corresponding to operations of the techniques provided herein. It will be appreciated that the operations described herein may be implemented in an angiographic imaging system or a standalone computer system to improve angiographic image processing and display technologies. According to an embodiment, a cardiac frequency bandpass filter may be applied to the angiographic data taken at greater than cardiac frequency to output the spatiotemporal reconstruction of cardiac frequency angiographic phenomena (e.g., moving vascular pulse waves). To extract the cardiac frequency phenomena from a cine sequence of angiographic images, a cardiac frequency bandpass filter is applied to the angiogram. In aspects, a contemporaneously measured cardiac signal (such as acquired from the pulse oximetry system of <FIG> or the electrocardiogram device of <FIG>) may serve as a reference cardiac signal for phase indexing.

<FIG> shows a high level implementation of the techniques provided herein. While the operations are shown separately, it should be understood that certain operations (e.g., temporal processing, bandpass filtering, and amplification) may be combined and/or performed in a different order than as shown in this figure. At operation <NUM>, the image is spatially decomposed. In an embodiment, the image may be decomposed into pixels, and subsequent computations performed pixel-wise. In other aspects, pixels may be grouped into different frequency bands, and computation may be performed band-wise.

Spatial decomposition is the separation of an image into several images each with different spatial characteristics. For example, images may be separated into groups corresponding to spatial structures of specific spatial frequencies. Examples of methods for generating a spatial decomposition include but are not limited to a Laplacian pyramid, a complex steerable pyramid, and a Reisz pyramid. In other aspects, spatial decomposition may include multiscale anisotropic filtering, or transformation based on shearlets or ridgelets. Any of these may be selected for extracting the cardiac frequency phenomena in a sequence of angiographic images, since cardiac frequency organization may occur in one or more specific scales of spatial structure. In aspects, the spatial frequency decomposition may be real-valued or complex-valued.

At operation <NUM>, temporal processing may be performed to correlate observed intensities of pixels as a function of time to a translational motion signal. As the vascular pulse wave travels through the vascular system, temporal processing allows this translational motion signal to be extracted. At operation <NUM>, the translational motion signal may be bandpass filtered, e.g., at cardiac frequency. In aspects, each pixel in an angiographic image may be treated as a separate signal as a function of time, and the cardiac frequency bandpass filter may be applied pixel-wise. In other aspects, the cardiac frequency bandpass filter may be applied to groups corresponding to spatial structures. In the limit, instead of a frequency bandpass filter, a contemporaneously measured cardiac signal (e.g., acquired from the pulse oximetry system of <FIG> or the electrocardiogram device of <FIG>) may serve as a cross correlation target, furnishing a type of ultra-narrow bandpass cardiac frequency filter. In aspects, the contemporaneously measured cardiac signal serves as a reference cardiac signal for phase indexing.

At operation <NUM>, the signal (e.g., extracted from the image using bandpass filtering, which corresponds to motion at cardiac scale) may undergo amplification. In aspects, amplification may be achieved by multiplying the signal by a constant. In other aspects, Eulerian magnification may be used. In some aspects, the amplification may be performed by isolating and then amplifying the cardiac frequency signal. In this case, the amplification signal may be recombined with the original signal, for example, by aligning the amplified signal with the original signal (e.g., based on time varying intensities, based on a timestamp, etc.). In some aspects, the amplified signal may be additively combined to the original signal. In other aspects, the amplified signal may be superimposed onto the original signal. Thus, at operation <NUM>, the original signal may be combined or superimposed with the amplified bandpass signal to form a reconstructed signal. For example, Optionally, at operation <NUM>, the reconstructed signal may undergo noise suppression (e.g., bilateral filtering or other suitable technique). These techniques provide a spatiotemporal reconstruction of cardiac frequency angiographic phenomena as output, shown as moving vascular pulse waves which may be amplified.

In other aspects, the cardiac frequency bandpass filter may be real valued or complex valued, according to embodiments. If the cardiac frequency bandpass filter is real valued, then the resulting cardiac frequency phenomena will be reevaluated, and may be rendered in image form using any suitable visualization format including grayscale, colorscale, and/or brightness. Alternately, if the cardiac frequency bandpass filter is complex valued, having a real component and an imaginary component, it may be represented in a polar form comprising a magnitude and a phase. After passage through a cardiac frequency bandpass filter, the magnitude may be interpreted as cardiac frequency magnitude, as in a "strength of the heart action. " The phase may be interpreted as the temporal location within a cardiac cycle. The magnitude and the phase may be rendered using a brightness-hue color model, where the brightness of a pixel represents a cardiac frequency magnitude and the hue represents a cardiac frequency phase.

The cardiac frequency bandpass filter and amplified images may be rendered in gray scale or in a color scale (referring back to <FIG>), where optionally color brightness may represent cardiac frequency magnitude or spatial motion speed, and color hue may represent cardiac frequency phase or spatial motion direction, depending on the user's choice of whether to emphasize the temporal or spatial properties in the cardiac frequency band of the reconstructed result. Although the image is submitted as grayscale, one of ordinary skill in the art would recognize that this grayscale image includes a spectrum of hues. The color model for rendering a complex valued number in a pixel is depicted in <FIG> may show a spectrum of color hues including a green region, a yellow region, a red region, and a blue region. A sequence of such images may be animated across the time indices to represent a cine video sequence of the motions of a train of vascular pulse waves, such as in the brain or heart or other vascular regions, for example.

With reference now to <FIG>, an example is provided hereinbelow for a given spatially filtered image and for only one spatial dimension, x, and the time t dimension, t, for purposes of illustration. This representation corresponds to a continuous form of signals. However, it is understood that these continuous equations may be applied to process digitized images, according to techniques known in the art.

At operation <NUM>, a spatially filtered image is generated. An image I(x,t) may undergo spatial decomposition, as provided herein. For example, spatial decomposition may include pyramidal decomposition, in which coarse filtering is used to separate regions into different frequency bands and fine filtering is used to refine the image. The spatially decomposed or spatially filtered image I(x,t) may be represented as: <MAT>.

At operation <NUM>, a time-dependent translation (or temporal filter) is applied to x, to determine motion from vessels and extract cardiac frequency, wherein x is modified by a translation function ∂(t) that is a function of t: <MAT>.

At operation <NUM>, the time-dependent translation to extract cardiac frequency motion is amplified by an amplification factor α, which is applied to the translation function a(t) to give: <MAT>.

In aspects, the term f(x+∂(t)) is expanded as a first order Taylor expansion about x as: <MAT>.

In aspects, higher order terms (e.g., second order, third order, etc.) from the Taylor expansion may be included. This equation corresponds to the reconstructed signal including the amplified time dependent translation. For instance, the term ∂(t) ∂f(x)/ ∂x acts as a cardiac frequency bandpass filter (with time windowing) such that its value is zero for temporal phenomena outside of the cardiac frequency band. The time dependent translation is amplified by (<NUM>+ α) (if α is chosen to be greater than zero) and combined with the original image f(x). This reconstruction may be shown as a cine video sequence to illustrate the spatiotemporal angiographic phenomena. Thus, by applying this strategy in combination with spatial decomposition, the images may be synthesized from their pyramids of spatially decomposed images. In aspects, amplification techniques may be optional, and only bandpass filtering may be performed.

In another aspect, a Fourier transform may act as a bandpass filter. At operation <NUM>, a spatial decomposition is performed on the image. At operation <NUM>, the image may be subjected to a cardiac scale bandpass filter and then pixel-wise transformed into the frequency domain using a Fourier transform. In other aspects, a time windowed Fourier transform may be applied. At operation <NUM>, the cardiac scale may be amplified in the frequency domain. At operation <NUM>, the amplified frequency domain image may be inverse transformed into the time domain, and the spatiotemporal angiographic phenomena with an amplified cardiac range may be displayed.

In another aspect, Eulerian magnification techniques may be modified and extended to allow for custom amplification of the cardiac angiographic phenomena. For example, present approaches extend these techniques to an angiogram, comprising a temporal sequence of images obtained during the passage of an intravascularly injected contrast bolus into the vasculature at faster than cardiac frequency. In this case, the amplification factor α may be selected to amplify spatiotemporal angiographic phenomenon, allowing for reproducibility by restricting and standardizing ranges for this factor. Additionally, Eulerian methods may select a bandpass filter for angiographic data, and may include higher order terms (e.g., second or third order terms as needed) to estimate the cardiac frequency band, which may be narrowly estimated and/or restricted from independent data such as a heartbeat monitor.

For example, amplification may be performed using Eulerian magnification methods. In this approach, a spatial filter is applied to a temporally arranged sequence of two or more images. A temporal filter is applied to the plurality of results of the spatial filter. One or more of the dual spatial and temporal filtered results are selectively amplified, and then reassembled into a sequence of images in order to yield an amplified effect corresponding to reconstruction of spatiotemporal phenomena. These techniques may be applied to angiographic images in order to select for those with temporal and spatial phenomena of interest, including temporal phenomena corresponding to the cardiac frequency phenomena.

According to an additional embodiment of the invention, shearlet or ridgelet transforms may be used in extracting cardiac frequency phenomena in angiographic data. Shearlet and ridgelet transforms accommodate multivariate functions that are governed by anisotropic features, such as edges in images. Wavelets, as isotropic objects, are not capable of capturing such phenomena. While wavelet transforms may be used for purposes of time-domain resolution, shearlet and ridgelet transforms may be used for spatial resolution, allowing a multi-resolution (e.g., 2D-spatial and temporal) analysis of the angiographic data to be performed.

An example implementation is provided in <FIG>. In this example, a bandpass filter is applied with an amplification factor to visualize the cardiac frequency phenomena. The left hand portion of the diagram shows a patient <NUM> undergoing an angiogram simultaneous with a cardiac signal being recorded from a finger pulse oximeter <NUM> (also known as optical plethysmogram).

The angiogram is obtained by injecting a bolus of contrast into the patient and acquiring angiographic images at faster than cardiac frequency. The cardiac frequency may be obtained from the patient's cardiac signal. In some aspects, the cardiac signal may vary as a function of time. In this case, the momentary cardiac signal may be referenced with respect to corresponding obtained images.

In this example, a graphical user interface is shown with two main display elements <NUM> and <NUM> and two visual control widgets <NUM> and <NUM>. It will be appreciated that the graphical user interface could be displayed on a computer monitor, such as the monitor of computer system <NUM>. The two main display elements are a cardiac angiogram image <NUM> without cardiac frequency amplification (left on the computer monitor, labeled "Raw") and a cardiac angiogram image <NUM> with cardiac frequency amplification (right on the computer monitor, labeled "Cardiac Frequency Amplified," with the brightness-hue model for cardiac frequency magnitude and phase). Other display methods including but not limited to grayscale, monochrome, etc. are contemplated for use with present techniques. In this example, a horizontally oriented slider control widget <NUM> (labeled "Frame"), positioned below the images, may be moved left and right on the screen by a user (e.g., by dragging with a mouse) to control the image frame being displayed. A cardiac frequency filter (as described in <FIG>) is applied to all image frames of the angiographic image sequence, and a clinician or radiologist may inspect one frame at a time. Optionally, a 3D rendering of the cardiac frequency-amplified image is provided, e.g., using the techniques described in co-pending <CIT>.

The graphical user interface also includes a vertically oriented slider control <NUM> on the right (labeled "Amp Factor") that can be adjusted by a user (e.g., by dragging with a mouse) to specify the degree of amplification of cardiac frequency. By controlling these parameters while viewing the images, users who are interpreting the images may modify the amplification and spatial resolution of the images based on the techniques provided herein, to customize these settings for specific medical analysis. These techniques may provide medical insight into cardiac frequency activity transpiring in the subject being imaged.

<FIG> shows high level operations of the techniques provided herein. At operation <NUM>, data is acquired or received from an angiographic study obtained at a rate faster than cardiac frequency. At operation <NUM>, a cardiac frequency bandpass filter is applied to the angiographic data to output a spatiotemporal reconstruction of cardiac frequency angiographic phenomena. At operation <NUM>, the spatiotemporal reconstruction of cardiac frequency angiographic phenomena in one or more images is displayed.

Beneficially, embodiments provided herein include a system, method, and computer readable media for spatiotemporally reconstructing cardiac frequency phenomena in angiographic data that apply a cardiac frequency bandpass filter to angiographic data, with or without a Eulerian magnification, for extracting and potentially magnifying cardiac frequency phenomena. In some aspects, these techniques may be combined with the techniques provided in the '<NUM> patent to further magnify cardiac frequency phenomena.

These techniques may be applied with a hardware system designed to obtain angiographic images, and in particular an angiographic system, to obtain images for a patient. These techniques provide an improvement in the art over existing angiographic approaches, namely, allowing the spatiotemporal cardiac frequency phenomenon to be amplified an superimposed on the angiographic signal. This enhancement may allow improved visualization by amplification of vascular pulse waves as well as resolution of fine detail (based on spatial filtering techniques), as compared to existing techniques. In aspects, amplification may be custom controlled as described in herein to allow varying degrees of amplification and resolution, which may be customized to yield information for various medical analysis.

It will thus be seen that the objects set forth above, among those made apparent from the preceding description, are efficiently attained and, because certain changes may be made in carrying out the above method and in the construction(s) set forth, it is intended that all matter contained in the above description and shown in the accompanying drawings shall be interpreted as illustrative and not in a limiting sense.

It is also to be understood that the following claims are intended to cover all of the generic and specific features of the invention herein described and all statements of the scope of the invention which, as a matter of language, might be said to fall there-between.

Claim 1:
A method for extracting cardiac frequency angiographic phenomena from an angiographic study obtained at a rate faster than cardiac frequency, the method comprising:
acquiring or receiving (<NUM>) data from an angiographic study obtained at a rate faster than cardiac frequency;
acquiring a contemporaneously measured cardiac signal that varies as a function of time;
obtaining from the contemporaneously measured cardiac signal a momentary cardiac frequency;
using the cardiac frequency as a cross correlation target to provide a cardiac frequency bandpass filter limited in range by the cardiac frequency;
applying (<NUM>) the cardiac frequency bandpass filter to the angiographic data to generate a spatiotemporal reconstruction of cardiac frequency angiographic phenomena without the use of wavelets; and
displaying (<NUM>) the spatiotemporal reconstruction of cardiac frequency angiographic phenomena in one or more images.