Surgery – Diagnostic testing – Detecting nuclear – electromagnetic – or ultrasonic radiation
Reexamination Certificate
2001-07-20
2003-02-04
Lateef, Marvin M. (Department: 3737)
Surgery
Diagnostic testing
Detecting nuclear, electromagnetic, or ultrasonic radiation
Reexamination Certificate
active
06514204
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates to ultrasonic elasticity imaging devices and more particularly relates to computer based signal processing methods for improving strain estimation.
2. Description of the Related Art
Ultrasound based elasticity imaging methods produce images that convey information regarding tissue elastic properties, as opposed to information regarding tissue acoustic scattering properties conveyed by conventional b-mode ultrasonograms. One of the ultrasonic elasticity imaging methods is elastography. Elastography produces high resolution elastograms (elastographic images) that quantitatively depict local tissue deformation under quasi-static external compression.
In general terms, elastograms may be generated as follows:
a.) a frame of RF echo signals from tissue is digitized before compression;
b.) a small quasi-static compression is applied on the tissue along the axis of the transducer by a computer controlled fixture;
c.) a second frame of RF frame echo signals is digitized after compression; and
d.) the acquired pre-and post-compression RF echoes are analyzed to compute the induced tissue strain.
FIGS. 8A through 8C
illustrate the principal of elastography.
FIGS. 8A and 8B
illustrate an exemplary tissue structure which includes a very soft top layer, a rigid intermediate layer and a soft lower layer, before and after compression, respectively. As illustrated in
FIG. 8B
, when an object is subjected to external compression, the rigid middle layer undergoes virtually no deformation whereas the top softest layer experiences a large deformation. This is represented in the strain profile graph of FIG.
8
C. Using suitable signal processing techniques, such a strain profile can be translated into an image of the underlying tissue.
The quality of an elastogram depends largely on the amount and character of undesired motion during signal acquisition as well as the signal processing which determines tissue response when compressed. For example, the quality of elastograms is highly dependent on the quality of time delay estimation (TDE). However, TDE in elastography can be corrupted by two primary factors: the occurrence of random noise, and the large and irregular tissue motions. These motions reduce correlation (decorrelation) between the post-compression signal and the pre-compressed signal.
There have been several attempts to compensate decorrelations that occur at relatively small strains. For example, in I. Céspedes and J. Ophir,
Reduction of signal decorrelation from mechanical compression of tissues by temporal stretching: applications to elastography
, Ultrasound Med. Biol., vol. 23, pp. 95-105 (1997), a temporal stretching method used to compensate for echo waveform changes in the axial direction is disclosed.
Also in the article
An adaptive strain Estimator for Elastography
, by S. K. Alam, J. Ophir, and E. E. Konofagou, IEEE Trans. Ultrason., Ferroelec., Freq. Contr., vol. 45, No. 2, pp. 461-472 (1998), an adaptive stretching strain estimator, which computes strain by iteratively varying a stretch factor to maximize correlation between pre- and post-compression echo signals, is disclosed. While these references provide techniques which allow for compensation of small decorrelations, they suffer from a common drawback in that these techniques cannot produce acceptable elastograms for large and irregular tissue motions.
Accordingly, there remains a need for improved methods of determining tissue strain estimation during compression. An object of the present invention is to provide new and improved signal-processing methods for estimating acceptable tissue strain even in the presence of large tissue motions.
SUMMARY OF THE INVENTION
In accordance with the invention, there is provided a method of estimating tissue strain including transmitting the ultrasonic signals into tissue and detecting first reflected signals. The tissue is then compressed to induce tissue strain. Ultrasonic signals are transmitted into the compressed tissue and second reflected signals are detected. Following detection of the first and second reflected signals, first and second Fourier Transforms of the first and second reflected signals are computed in overlapping temporal windows along each scan line and one of the first and second Fourier Transforms is frequency scaled. A correlation signal of the scaled Fourier Transform and the other Fourier Transform is derived and tissue strain is estimated from the frequency scaling factor representing a maximum of the correlation signal.
In accordance with the invention, there is provided a method of estimating tissue strain which includes transmitting ultrasonic signals into tissue and detecting first reflected signals. The tissue is then compressed to induce tissue strain and ultrasonic signals are transmitted into the compressed tissue and second reflected signals are detected. The first and second reflected signals are converted into the spectral domain and the first and the second reflected signals are low-pass filtered. The second filtered reflected signal is then frequency scaled. A correlation signal of the frequency-scaled filtered reflected signal and the other signal is derived. The tissue strain is finally estimated from the time scaling factor representing a maximum of the correlation function.
In accordance with the invention, there is provided a method of estimating tissue strain which includes transmitting ultrasonic signals into tissue and detecting first reflected signals. The tissue is then compressed to cause tissue strain, ultrasonic signals are transmitted into the compressed tissue and second reflected signals are detected. The first and second reflected signals are transformed into the spectral domain, such as by computing first and second Fourier Transforms of the first and second reflected signals. The second spectral domain signal is frequency scaled by a scaling factor and the variance of the ratio of the scaled spectral domain signal and the non-scaled first spectral domain signal is computed. The scaling factor is then varied and the process repeated to minimize the variance. Local tissue strain is the estimated from the frequency scaling factor representing a minimum of the variance.
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Alam Sheikh Kaisar
Feleppa Ernest J.
Lizzi Frederic L.
Baker & Botts LLP
Imam Ali M.
Lateef Marvin M.
Riverside Research Institute
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