Surgery – Diagnostic testing – Detecting nuclear – electromagnetic – or ultrasonic radiation
Reexamination Certificate
1999-06-17
2001-09-04
Lateef, Marvin M. (Department: 3737)
Surgery
Diagnostic testing
Detecting nuclear, electromagnetic, or ultrasonic radiation
C600S443000
Reexamination Certificate
active
06283917
ABSTRACT:
This invention relates to ultrasonic diagnostic imaging systems and, in particular, to ultrasonic diagnostic imaging systems which produce spatially compounded images which are corrected for image blurring.
Spatial compounding is an imaging technique in which a number of ultrasound images of a given target that have been obtained from multiple vantage points or angles are combined into a single compounded image by combining the data received from each point in the compound image target which has been received from each angle. Examples of spatial compounding may be found in U.S. Pat. Nos. 4,649,927; 4,319,489; and 4,159,462. Real time spatial compound imaging is performed by rapidly acquiring a series of partially overlapping component image frames from substantially independent spatial directions, utilizing an array transducer to implement electronic beam steering and/or electronic translation of the component frames. The component frames are combined into a compound image by summation, averaging, peak detection, or other combinational means. The acquisition sequence and formation of compound images are repeated continuously at a rate limited by the acquisition frame rate, that is, the time required to acquire the full complement of scanlines over the selected width and depth of imaging.
The compounded image typically shows lower speckle and better specular reflector delineation than conventional ultrasound images from a single viewpoint. Speckle is reduced (i.e. speckle signal to noise ratio is improved) by the square root of N in a compound image with N component frames, provided that the component frames used to create the compound image are substantially independent and are averaged. Several criteria can be used to determine the degree of independence of the component frames (see, e.g., O'Donnell et al. in IEEE Trans. UFFC v.35, no. 4, pp 470-76 (1988)). In practice, for spatial compound imaging with a steered linear array, this implies a minimum steering angle between component frames. This minimum angle is typically on the order of several degrees.
The second way that spatial compound scanning improves image quality is by improving the acquisition of specular interfaces. For example, a curved bone-soft tissue interface produces a strong echo when the ultrasound beam is exactly perpendicular to the interface, and a very weak echo when the beam is only a few degrees off perpendicular. These interfaces are often curved, and with conventional scanning only a small portion of the interface is visible. Spatial compound scanning acquires views of the interface from many different angles, making the curved interface visible and continuous over a larger field of view. Greater angular diversity generally improves the continuity of specular targets. However, the angular diversity available is limited by the acceptance angle of the transducer array elements. The acceptance angle depends on the transducer array element pitch, frequency, and construction methods.
The challenges of acquiring images which are in spatial alignment, or of spatially aligning separate images after they have been received, can be considerable. When the objective is to produce spatially compounded images in real time, an even greater challenge is presented. Image processing must be fast and efficient so that the frame rate of compound images appears to be in real time. The compound images can suffer from motion artifacts, as organs such as the heart and blood vessels can be continually moving as the image data to be compounded is acquired.
One of the problems associated with real time spatial compound imaging is that several image acquisitions are needed to produce each new compound image frame. The time needed to acquire a spatial compound image consisting of N component frames is approximately N times longer than that of each individual component frame. It is generally desirable to acquire a large number of component frames to maximize the image quality of the compound image. However, since the images to be compounded are acquired temporally, the compounding of the images can produce a blurred resultant image. Image blurring occurs in real time spatial compound imaging because common features in the acquired component frames do not superimpose exactly when compounded. Misregistration between acquisition frames can occur for a number of reasons, such as:
1) features can shift position within the image plane due to scanhead and/or patient movement during acquisition (in-plane motion misregistration). This kind of misregistration can be global (translation and/or rotation of entire image) or local (image distortion due to cardiac or respiratory motion, or compression of the tissue with the scanhead).
2) features can shift position due to an incorrect assumption regarding the speed of sound, causing the features to be rendered with axial and angular misregistration (SOS misregistration). This kind of misregistration can be due to an incorrect mean speed of sound or variations in local speed of sound within different tissue types.
Accordingly, it is desirable to prevent blurring from causes such as these when compounding images for real time display.
In accordance with the principles of the present invention, blurring of a compound image is reduced and image quality improved through correction of misregistration errors by registering the component frames to each other prior to compounding. This is possible by the application of image registration techniques. Image registration is meant here as a general term to describe any process which estimates global and/or local displacement information between two images, and warps one (or both) images to make them congruent with each other. A number of techniques may be used to estimate the displacement, including cross correlation search, block matching algorithms, maximum brightness, and feature extraction and tracking. Warping algorithms may be first order, global transformations (translation and/or rotation) or higher order (complex local warping), based on the nature and magnitude of the displacements. The component frames are registered to each other prior to compounding, improving image quality.
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Entrekin Robert R.
Jago James R.
ATL Ultrasound
Lateef Marvin M.
Patel Maulin
Yorks, Jr. W. Brinton
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