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WO2008127927A1 - Detection de bordures tissulaires dans l'imagerie en coupe epaisse ultrasonore - Google Patents

Detection de bordures tissulaires dans l'imagerie en coupe epaisse ultrasonore Download PDF

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Publication number
WO2008127927A1
WO2008127927A1 PCT/US2008/059704 US2008059704W WO2008127927A1 WO 2008127927 A1 WO2008127927 A1 WO 2008127927A1 US 2008059704 W US2008059704 W US 2008059704W WO 2008127927 A1 WO2008127927 A1 WO 2008127927A1
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Prior art keywords
slice
imaging system
slices
ultrasonic diagnostic
image
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PCT/US2008/059704
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English (en)
Inventor
Robert L. Burnham
Karl Thiele
Patrick G. Rafter
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Koninklijke Philips Electronics, N.V.
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Application filed by Koninklijke Philips Electronics, N.V. filed Critical Koninklijke Philips Electronics, N.V.
Publication of WO2008127927A1 publication Critical patent/WO2008127927A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/46—Ultrasonic, sonic or infrasonic diagnostic devices with special arrangements for interfacing with the operator or the patient
    • A61B8/461—Displaying means of special interest
    • A61B8/463—Displaying means of special interest characterised by displaying multiple images or images and diagnostic data on one display
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
    • A61B8/5238—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for combining image data of patient, e.g. merging several images from different acquisition modes into one image
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
    • G01S7/52085—Details related to the ultrasound signal acquisition, e.g. scan sequences
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
    • G01S7/52085—Details related to the ultrasound signal acquisition, e.g. scan sequences
    • G01S7/52095—Details related to the ultrasound signal acquisition, e.g. scan sequences using multiline receive beamforming
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/06—Measuring blood flow
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Clinical applications
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Clinical applications
    • A61B8/0883—Clinical applications for diagnosis of the heart
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/48—Diagnostic techniques
    • A61B8/481—Diagnostic techniques involving the use of contrast agents, e.g. microbubbles introduced into the bloodstream
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/48—Diagnostic techniques
    • A61B8/483—Diagnostic techniques involving the acquisition of a 3D volume of data
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/48—Diagnostic techniques
    • A61B8/488—Diagnostic techniques involving Doppler signals

Definitions

  • This invention relates to medical diagnostic ultrasound systems and, in particular, to ultrasound systems which identify tissue borders in ultrasonic thick slice images.
  • Ultrasonic diagnostic imaging is an imaging modality which forms images of coherent signal information.
  • the nature of the coherent ultrasonic signals used like the monochromatic lightwaves used for holographic imaging, results in constructive and destructive interference of the waves in the medium being imaged.
  • the image contains noise in the form of a random mottling of the image known as "speckle.”
  • the common approach to reducing the effect is to combine uncorrelated image data and reduce the speckle by an averaging effect proportional to the square root of two.
  • the types of uncorrelated data used are typically data that are of different frequencies or acquired from different look directions, commonly known as frequency compounding (see, e.g., US Pat. 4,350,917 to Lizzi et al.) and spatial compounding (see, e.g., US Pat. 4,649,927 to Fehr et al . )
  • a diagnostic ultrasound system and method which improve the ability of automated and semi-automated tissue border detection processes to identify tissue borders in ultrasound images.
  • An ultrasound image is acquired of an image plane containing tissue with a border that is to be identified.
  • one or more images of adjacent image planes are also acquired, with all of the image planes being substantially parallel in the elevational dimension.
  • these multiple elevation images are projected in the elevation dimension and combined to form a single "thick slice" image.
  • common-mode structures will be positively reinforced, whereas artifacts such as speckle, side-lobe artifacts, and clutter which are not common to all of the component images will be de-weighted in the composited result.
  • the improvement in contrast resolution has been found to yield better results when the thick slice images are subjected to automated tracing and structure identification processing.
  • the inventive technique is effective for real time image sequences, static images, and the analysis of stored image loops.
  • FIGURE 1 illustrates a plurality of sector slices acquired in the elevational direction.
  • FIGURE 2 illustrates a plurality of rectilinear slices acquired in the elevational direction.
  • FIGURE 3 illustrates a plurality of slices which are at different angular increments in the elevational direction.
  • FIGURES 4a-4c illustrate the acquisition of multiple slices simultaneously by multiline acquisition in accordance with the principles of the present invention.
  • FIGURE 5 illustrates in block diagram form an ultrasonic diagnostic imaging system constructed in accordance with the principles of the present invention.
  • FIGURE 6 illustrates in block diagram form a second implementation of an ultrasonic diagnostic imaging system constructed in accordance with the principles of the present invention.
  • FIGURE 7a illustrates a dual ported memory used for slice storage in an implementation of the present invention.
  • FIGURE 7b illustrates partitioning of memory areas in an implementation of the present invention.
  • a volumetric region 10 is shown in perspective.
  • the volumetric region 10 is sector-shaped and contains a plurality of planar sector-shaped areas which are referred to herein as "slices.”
  • slices 12-18 are illustrated in this example.
  • the slices are oriented parallel to each other in the elevation direction with their azimuth and elevation dimensions indicated to the right of the drawing.
  • Each slice may be scanned by an array transducer located above the volumetric region by transmitting successive scanlines across a slice 12-18 in the azimuth direction and progressing from slice to slice in the elevation direction.
  • FIGURE 2 illustrates a rectilinear volumetric region 20 which also includes a plurality of slices oriented in parallel in the elevation direction. Four such slices 22-28 are shown in the drawing.
  • These slices may be scanned in the same manner as the slices of FIGURE 1 by a transducer array located above the volumetric region 20.
  • the slices are scanned by parallel scanlines in the azimuth direction rather than by angularly incremented scanlines from a common origin as is the case in the example of FIGURE 1.
  • FIGURE 3 provides another example of slices of a volumetric region. These slices are of a pyramidal volumetric region with an apex 34 at the top of the volume.
  • four sector-shaped slices Si- S 4 are shown in an "edge-on" view. That -is, the elevation direction of the slices is indicated by the arrow 32, and the azimuth direction is into the plane of the drawing. The azimuth and elevation directions with respect to the array transducer 30 are shown above the transducer array.
  • neighboring elevation slices are substantially parallel and are separated from each other by an angular increment ⁇ .
  • a single slice of a volume may be scanned and displayed.
  • a plurality of slices which are elevationally aligned are scanned and their data combined to form an image for display. Since each of the elevationally distinct slices is scanned by scanlines having different transmit-receive signal paths, each of the slices will exhibit its own unique speckle pattern. By combining the image data of a plurality of slices which define a thickness in the elevation dimension, the speckle artifact of the combined image will be reduced.
  • the slices may be scanned at a high speed by multiline acquisition.
  • multiline acquisition one transmit beam insonifies multiple receive line locations and multiple receive lines are acquired in response to the single transmit event.
  • FIGURES 4a-4c provide an example of multiline acquisition of four slices S 1 -S 4 which are arranged in parallel in the elevational dimension.
  • Each slice is made up of receive lines arrayed in the azimuth direction and identified in the drawing as Ll, L2,... Ln, where "n" may be 128, for instance.
  • each receive line is being viewed axially as it would from the perspective of the transducer array.
  • a transmit beam TxAl insonifies receive lines Ll and L2 of slice Si and receive lines Ll and L2 of slice S 2 .
  • receive lines Ll and L2 of slice Si insonifies receive lines Ll and L2 of slice S 2 .
  • two receive lines in azimuth and two receive lines in elevation, a total of four receive lines, are acquired simultaneously and processed. See, e.g., US Pat. 5,318,033 (Savord) for an explanation of the processing of simultaneously received multilines.
  • FIGURE 4b illustrates the next transmit event, in which a transmit beam TxA2 insonifies another four receive lines, L3 and L4 of slice Si and receive lines L3 and L4 of slice S 2 .
  • Scanning proceeds in this manner until all of the lines of slices Si and S 2 have been acquired.
  • echo data from two slices, Si and S 2 has been acquired.
  • the process then continues with a second azimuth scanning interval as shown in FIGURE 4c with the scanning of receive lines Ll and L2 of slice S 3 together with receive lines Ll and L2 of slice S 4 by transmit beam TxBl.
  • Slices S 3 and S4 are scanned during this second azimuth scanning interval in the same manner as slices Si and S 2 were acquired during the first. In these two scanning intervals all four slices Si-S 4 are scanned in the time required to scan a single slice in the conventional line-by-line approach. The speed of acquisition and hence the frame rate of display have been increased by a factor of four by the use of this 4X multiline acquisition.
  • FIGURE 5 An ultrasound system constructed in accordance with the principles of the present invention is shown in block diagram form in FIGURE 5.
  • a two dimensional array transducer 30 is provided which electronically steers and focuses beams over a volumetric region 10 under control of a microbeamformer 36, main beamformer 38, and beamformer controller 42.
  • a one dimensional array transducer can be mechanically oscillated to scan the volumetric region.
  • the microbeamformer 36 located in the probe case with the 2D transducer array 30 controls the scanning of groups of elements called subarrays or patches in scanning a volumetric region 10. Partially beamformed signals from the microbeamformer 36 are formed into fully beamformed signals by the main beamformer 38.
  • a beamformer controller 42 provides control signals for the beamformer and microbeamformer. Further details on microbeamformer-controlled scanning of volumetric regions may be found in US Pat. 6,623,432 (Powers et al.), and 6,709,394 (Frisa et al.), PCT publication WO 2005/099579 (Rafter) and US patent application 60/777,831 (Savord) , filed March 1, 2006.
  • a user control panel 40 is coupled to the beamformer controller 42 and is operated to control a number of parameters of the scanning of slices 12-16 of the volumetric region 10, including the number of slices to be scanned, the spacing between slices, the number of transmit slices, and the number of receive slices per transmit slice. Referring back to FIGURES 4a-4c, in that example the number of slices to be scanned was four, the spacing between slices was a specified angular or linear parameter, the number of transmit slices was two, and the number of receive slices per transmit slice was two.
  • the beamformed echo signals received from the scanned slices are detected by a log detector 52 for B mode imaging.
  • the received echo signals may be Doppler processed by a Doppler processor 54 for the display of flow or motion in the image field.
  • the B mode image data and the Doppler image data (e.g., Doppler power and/or velocity) of each slice are stored in slice storage buffer 60. Addressing of the buffer 60 to write data into the buffer or read data out of the buffer is controlled by memory controller 62.
  • a plurality of elevationally different slices are read out of the slice storage buffer 60 and combined by a combiner 64 .
  • the combiner 64 may combine the image data of multiple elevationally different slices in various ways. Combining is preferably performed on image data from different slices which have the same azimuth and depth coordinates in each slice. Alternatively, raylines can be mathematically projected through the multiple slices in the manner of raycasting for volume rendering. Preferably the raylines are projected normal to the planes of the slices.
  • the image data intersected by each rayline is the data which is combined. In the combining process the image data can be averaged or can be summed and normalized. A mean or median value of the data values can be computed, or a peak value of the data being combined can be used.
  • the data from the central slice can be weighted more greatly than the data of neighboring slices, with slice data being weighted in relation to its distance from the central slice.
  • Slice data can be weighted in relation to its proximity to the viewer with slice data in the front of the volume being weighted more greatly than slice data in the back.
  • the combined data thus forms a "thick slice" which can be displayed as a planar display of a slice with characteristics of multiple elevationally offset individual slices.
  • the thick slice data is coupled to an image processor 70 for further processing such as scan conversion into the desired display format (e.g., sector or linear) and is processed into video signals by a video processor 72 for display on a display 76.
  • the image data can also be saved or stored in a Cineloop® memory 78, harddrive or other image storage device.
  • the thick slice display will exhibit reduced speckle artifacts as compared to an individual one of the acquired slices .
  • Another example of the present invention is to scan a volume in a coordinate system appropriate for the transducer or for the clinical application.
  • a group of substantially parallel MPR (multi-planar- reformatted) planes are then derived from the acquired volumes, which may be but are not typically aligned with the acquisition slices contained within the volume.
  • These parallel MPR planes are then combined in the aforementioned techniques to produce an MPR thick slice, which is then used to facilitate the generation of automated borders.
  • FIGURE 7a illustrates the slice storage buffer 60 implemented as a dual port memory 160 which can be written to and read from simultaneously.
  • the use of such a R/W memory 160 enables the new data of a slice being scanned by the transducer array and beamformer to be written into one area of the R/W memory while the data of other slices previously stored in the memory is read out and combined to form a thick slice image.
  • the writing of new slice image data into the memory 160 is controlled by a write address controller 162a while the reading of slice image data from other locations in the memory is under the control of a read address controller 162b.
  • a new thick slice image can be combined for display while the image data from a new slice is being acquired.
  • FIGURE 7b One example of the allocation of memory for a combined four-slice thick slice image is illustrated by FIGURE 7b.
  • the storage area 260 of the memory is shown to contain seven image storage areas labeled A through G.
  • FIGURES 4a-4c An example employing the 4X multiline scanning technique of FIGURES 4a-4c for four component slices S 1 -S 4 is as follows.' Using the user interface 40, the ultrasound system is set to scan four slices with a given slice spacing, using two transmit slices and two receive slices per transmit slice. Scanning of the first two slices proceeds during a first scanning interval as shown in FIGURES 4a and 4b and the data of the two acquired slices Si and S 2 is written into memory areas A and B. Slices S 3 and S 4 are then scanned during a second interval and the data of these two slices is written into memory areas C and D. The transducer array and beamformer then begin to scan slices Si and S 2 again- and write the data from the rescanning of slices Si and S 2 into memory areas E and F.
  • the image data of memory areas A, B, C, and D is read out of the memory and coupled to the combiner 64 where the individual slice data is combined into a thick slice image.
  • the resultant thick slice image is written into memory area G, from which it is read out and coupled to the image processor (and other components as described below) as needed for processing and display.
  • the time required to composite the thick slice image and process the image for display will take less time than the time required to rescan slices Si and S 2 .
  • slices Si and S 2 After the rescanning of slices Si and S 2 is complete, the image data of slices Si, S 2 , S 3 , and S 4 which is stored in memory areas C, D, E, and F is read out for combining into a new thick slice image for display, and the new thick slice image is written into memory area G to update the real time thick slice image. Simultaneously, slices S 3 and S 4 are rescanned and their slice data is written into memory areas A and B. In the next scanning interval iteration slices Si and S 2 are scanned again and their data written into memory areas C and D while the slice data of memory areas E, F, A, and B is combined to form another thick slice image to update the image in memory area G.
  • Doppler processor 54 may result in black holes in the colorflow image where destructive interference from the speckle pattern has manifested itself, the differing speckle pattern of the neighboring slice may not exhibit this problem at the same point in the image.
  • the black hole of one slice may be filled in by valid colorflow of a neighboring slice.
  • the colorflow field will appear smoother and more sensitive to out-of-central plane jets with less far field degradation. Sensitivity of the procedure to jet detection is accordingly enhanced.
  • the combined color flow thick slice will improve both the qualitative and quantitative outline of the jet, further facilitating the use of techniques for automatically calculating jet area.
  • a thick slice image will better display the curved and tortuous paths of coronary arteries around the myocardium than a conventional single slice image. This is the case for contrast images as well as color flow images.
  • Doppler processor 54 For the production of a Doppler thick slice image, ensembles of echo signals are received from locations where flow or motion is present and are processed by the Doppler processor 54 to produce a Doppler estimate at those locations.
  • the Doppler estimate may be one of Doppler power at the location, or velocity or variance.
  • Corresponding B mode images may also be acquired if desired so that the Doppler information may be overlaid on structural detail framing the motion.
  • the Doppler slice images are stored in slice storage 60, then combined by combiner 64 using a selected combining technique. Defects in the flow or motion display due to speckle or dropout are thereby reduced, and flow or motion defects in adjacent slice planes are more easily identified by the projection of multiple Doppler slices in the elevation dimension. Furthermore, since the acquisition of multiple temporally different samples from each flow or motion location will decrease the frame rate of acquisition in the Doppler mode, at least some of this frame rate degradation may be overcome by use of the high speed thick slice display technique discussed in conjunction with FIGURES 7a and 7b above.
  • the thick slice images are also coupled to an automated or semi-automated border detector (ABD) 80.
  • border detectors are used to identify tissue borders in ultrasound images.
  • the border detectors can operate with initial user involvement to identify points on one border in one image, then use that input to automatically identify the full border and the border in other images of a real time image sequence.
  • Other border detectors operate automatically by identifying tissue landmarks in an image then drawing borders using those landmarks. See, for example, US Pats.
  • the border detector 80 identifies a tissue border in a thick slice image with or without user assistance (semi-automated or automated) and couples data identifying the location of the border in one or more thick slice images to a graphics processor 74.
  • the graphics processor 74 creates a graphic outline of the border to the image processor 70 which overlays the identified border over the corresponding thick slice image. It has been found that automated or semi-automated border detection performs better on thick slice images than on comparable single slice images.
  • tissue border defined by thin tissue which is not a strong reflector of ultrasonic echoes such as the endocardial border of the myocardium can produce a poorly defined tissue border in a single slice image.
  • Image dropout at the border region can produce an ill-defined image border which is difficult to trace reliably by an automated or semi-automated process.
  • the poorly-defined border can be further disrupted by the image speckle pattern.
  • the combining of elevationally distinct images into a thick slice image can reduce the speckle artifact and make the border more distinct in the image.
  • missing border segments in one slice can be augmented by identifiable border segments in adjoining slices, causing the consolidated tissue border of the thick slice image to be more clearly defined and hence more reliably processed and identified by the border detector 80.
  • thick slice imaging can be used with ultrasound contrast agents.
  • Ultrasound contrast agents have been approved in the United States for delineation of endocardial borders in difficult-to- image patients. These agents have also proven to be extremely valuable in quantification of volumes and ejection fraction. In several studies, quantification without contrast agents has been shown to underestimate volumes compared to other techniques like MRI. On the other hand, contrast-enhanced images have demonstrated values closer to these techniques. However, previous attempts for automated detection techniques with contrast agents have had limited success. Typically contrast images are acquired with lower power levels to minimize microbubble destruction - often 10-15dB lower than standard imaging.
  • thick slice imaging is used in the diagnosis and quantification of perfusion defects with the aid of ultrasonic contrast agents.
  • a contrast agent When a contrast agent is present in a blood pool such as a blood vessel or chamber of the heart, the contrast agent will generally be present in considerable volume and density in the blood pool.
  • the relatively high concentration of the microbubbles of the contrast agent enable quick and reliable detection of its presence in an ultrasound image.
  • the signal-to-noise ratio of the perfusion images is relatively low, frequently by as much as 20 dB lower than standard imaging techniques, causing further degradation in resolution.
  • the resultant images can have a display dynamic range which is 20 dB or more lower than conventional images without contrast, causing the speckle artifact to have a more pronounced adverse impact on image resolution and the detection of subendocardial regions of poor perfusion.
  • contrast images for perfusion diagnosis and/or quantification are improved in accordance with the present invention by scanning multiple planes in the elevation dimension and projecting these multiple elevation slices in the elevation dimension. By performing such operations it is possible to reduce speckle without sacrificing resolution and signal to noise.
  • the methods for compositing or combining slices which have been described above may be employed, including simple averaging and maximum intensity projection, or using compositing techniques from volume rendering (e.g., raycasting) .
  • volume rendering e.g., raycasting
  • the contrast agent speckle will be greatly reduced, subendocardial defects will be more evident, and quantification techniques such as parametric imaging will yield better results.
  • "destruction-replenishment" techniques require exactly the same elevation slice to be maintained for 10 seconds or more, thick-slice imaging will be more robust in the presence of small movements of the probe, since a plurality of adjacent slices are used to form the thick slice image plane. Thus, slight movement of the probe to different slice locations will have only minimal effect on the results obtained.
  • FIGURE 6 An ultrasound system constructed in accordance with the principles of the present invention for perfusion studies is shown in block diagram form in FIGURE 6, in which elements previously described in conjunction with FIGURE 5 are identified by the same reference numerals.
  • thick slice images of microbubble-perfused tissue which are produced by the combiner 64 may be processed as B mode images by the image processor 70, the video processor 72, and the display 76 for the display of real time grayscale images of perfusion which exhibit better resolution of tissue perfusion by virtue of reduced speckle caused by the elevational slice combining process.
  • the thick slice contrast images are also coupled to a perfusion detector 90.
  • the perfusion detector 90 may be constructed in the same manner as the contrast signal detector described in PCT publications WO 2005/044108 (Rafter) and WO 2005/099579 (Rafter) to detect and enhance the display of contrast agent perfusion in the images.
  • the perfusion detector may be configured as the contrast signal detector described in US Pat. 6,692,438 (Skyba et al.) to produce a color overlay of the B mode image which depicts perfused tissue in a qualitative color display, or a quantitative display of a perfusion curve or curve parameter for different points in the image.
  • the detection of epicardial borders is important to improve accuracy of stress echo exams and for detection of ischemia as well as to facilitate quantification of myocardial mass.
  • accurate automatic detection of the epicardium has proven to be elusive.
  • left ventricular opacification and myocardial perfusion improves the ability to detect both the epicardial and endocardial borders, allowing quantification of thickening and myocardial mass.
  • Other variation of the present invention will readily occur to those skilled in the art.
  • the concepts of the present invention may be employed in an implementation which does not use multiline acquisition but acquires qne receive line for every transmitted scanline.
  • Various sequence of line acquisition may be employed other than successive acquisition of adjacent lines such as those shown in US Pats.
  • Higher order multiline may be employed than the illustrated 4X multiline, including a multiline order which acquires all of the component slices in one azimuthal scan sequence.
  • Doppler modes other than colorflow may use the present invention including spectral Doppler, flow variance, and color M mode.
  • M mode may use an implementation of the present invention which acquires and combines spatially distinct M lines into one display M line. The techniques of the present invention are applicable to both fundamental and harmonic imaging.

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  • Ultra Sonic Daignosis Equipment (AREA)

Abstract

Selon l'invention, un système d'imagerie diagnostique ultrasonore balaye une pluralité de couples planes dans une zone volumétrique, parallèles les unes aux autres, au moins une couple plane contenant un élément anatomique présentant une bordure ou un repère tissulaire à identifier. Après la détection en mode B des données d'image des coupes, les données de coupes sont combinées par projection des données dans la dimension d'élévation, de sorte à produire une image de 'coupe épaisse' contenant l'élément anatomique à analyser. La combinaison peut se faire par un processus de détection d'intensité moyenne ou maximale ou de pondération ou par lancer de rayon dans la dimension d'élévation, dans un processus de rendu volumétrique. L'image de coupe épaisse est ensuite traitée par un détecteur de bordures automatisé ou semi-automatisé destiné à identifier de façon plus fiable la bordure ou les repères ciblés dans l'image, par la réduction de la granularité, des artefacts de lobes latéraux, du brouillage et autres anomalies d'image.
PCT/US2008/059704 2007-04-13 2008-04-09 Detection de bordures tissulaires dans l'imagerie en coupe epaisse ultrasonore WO2008127927A1 (fr)

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CN102697523A (zh) * 2011-03-25 2012-10-03 通用电气公司 用于显示体积超声图像上的交叉信息的方法和系统
EP3553785A1 (fr) * 2018-04-11 2019-10-16 Koninklijke Philips N.V. Systèmes et procédés permettant de générer des images de diagnostic à partir de données d'images médicales 3d
EP4231921A4 (fr) * 2020-10-21 2024-07-17 Maui Imaging, Inc. Systèmes et méthodes de caractérisation tissulaire à l'aide d'ultrasons à ouvertures multiples
US12167209B2 (en) 2012-09-06 2024-12-10 Maui Imaging, Inc. Ultrasound imaging system memory architecture
US12171621B2 (en) 2012-08-10 2024-12-24 Maui Imaging, Inc. Calibration of multiple aperture ultrasound probes
US12190627B2 (en) 2015-03-30 2025-01-07 Maui Imaging, Inc. Ultrasound imaging systems and methods for detecting object motion
US12186133B2 (en) 2012-03-26 2025-01-07 Maui Imaging, Inc. Systems and methods for improving ultrasound image quality by applying weighting factors
US12204023B2 (en) 2014-08-18 2025-01-21 Maui Imaging, Inc. Network-based ultrasound imaging system

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Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102697523A (zh) * 2011-03-25 2012-10-03 通用电气公司 用于显示体积超声图像上的交叉信息的方法和系统
US12186133B2 (en) 2012-03-26 2025-01-07 Maui Imaging, Inc. Systems and methods for improving ultrasound image quality by applying weighting factors
US12171621B2 (en) 2012-08-10 2024-12-24 Maui Imaging, Inc. Calibration of multiple aperture ultrasound probes
US12167209B2 (en) 2012-09-06 2024-12-10 Maui Imaging, Inc. Ultrasound imaging system memory architecture
US12204023B2 (en) 2014-08-18 2025-01-21 Maui Imaging, Inc. Network-based ultrasound imaging system
US12190627B2 (en) 2015-03-30 2025-01-07 Maui Imaging, Inc. Ultrasound imaging systems and methods for detecting object motion
CN112272850A (zh) * 2018-04-11 2021-01-26 皇家飞利浦有限公司 用于根据3d医学图像数据生成增强诊断图像的系统和方法
JP7278304B2 (ja) 2018-04-11 2023-05-19 コーニンクレッカ フィリップス エヌ ヴェ ３ｄ医用画像データから改良された診断画像を生成するためのシステムおよび方法
US11386606B2 (en) 2018-04-11 2022-07-12 Koninklijke Philips N.V. Systems and methods for generating enhanced diagnostic images from 3D medical image
JP2021520870A (ja) * 2018-04-11 2021-08-26 コーニンクレッカ フィリップス エヌ ヴェＫｏｎｉｎｋｌｉｊｋｅ Ｐｈｉｌｉｐｓ Ｎ．Ｖ． ３ｄ医用画像データから改良された診断画像を生成するためのシステムおよび方法
WO2019197203A1 (fr) * 2018-04-11 2019-10-17 Koninklijke Philips N.V. Systèmes et procédés de génération d'images de diagnostic améliorées à partir de données d'image médicales 3d
EP3553785A1 (fr) * 2018-04-11 2019-10-16 Koninklijke Philips N.V. Systèmes et procédés permettant de générer des images de diagnostic à partir de données d'images médicales 3d
EP4231921A4 (fr) * 2020-10-21 2024-07-17 Maui Imaging, Inc. Systèmes et méthodes de caractérisation tissulaire à l'aide d'ultrasons à ouvertures multiples

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