Source: http://www.google.fr/patents/US7998073
Timestamp: 2013-05-26 01:25:55
Document Index: 581185104

Matched Legal Cases: ['art 110', 'Application No. 2006', 'Application No. 04', 'Application No. 2006', 'Application No. 2006', 'Application No. 2006', 'Application No. 200480035079']

Brevet US7998073 - Ultrasound imaging with reduced noise - Google�BrevetsRecherche Images Maps Play YouTube Actualit�s Gmail Drive Plus » Recherche avanc�e dans les brevets | Historique Web | Connexion Recherche avanc�e dans les brevets BrevetsSignal processing techniques reduce the impact of noise (including speckle noise and shot noise) on ultrasound images by reducing the intensity of pixels that are probably noise and increasing the intensity of pixels that are probably signal. The decision of whether a given pixel is probably noise or...http://www.google.fr/patents/US7998073?utm_source=gb-gplus-shareBrevet US7998073 - Ultrasound imaging with reduced noise Num�ro de publicationUS7998073 B2Type de publicationOctroi Num�ro de demande11/098,923 Date de publication16 ao�t 2011 Date de d�p�t4 avr. 2005 Date de priorit�4 ao�t 2003Autre r�f�rence de publicationUS20050197573 InventeursHarold M. HastingsScott L. Roth Cessionnaire d'origineImacor Inc.Imacor, Inc.Wfd Ventures Llc, As AgentImacor Llc Classification aux �tats-Unis600/437600/449600/443 Classification internationaleA61B8/12G01S7/52A61B8/00G01S15/89 Classification coop�rativeA61B8/4488G01S15/8977G01S7/52033G01S7/52036A61B8/12G01S7/52077G01S15/8934 Classification europ�enneG01S15/89D2G01S15/89D6G01S7/52S2FG01S7/52S12A61B8/12A61B8/44R2R�f�rencesCitations de brevets (38)Citations hors brevets (13) R�f�renc� par (1)Liens externesUSPTO Cession USPTO EspacenetUltrasound imaging with reduced noiseUS 7998073 B2 R�sum� Signal processing techniques reduce the impact of noise (including speckle noise and shot noise) on ultrasound images by reducing the intensity of pixels that are probably noise and increasing the intensity of pixels that are probably signal. The decision of whether a given pixel is probably noise or probably signal is made based on spectral characteristics of the samples in and around the given pixel, based on knowledge of the expected spectral characteristics of the signal and the expected spectral characteristics of the noise.
CROSS REFERENCE TO RELATED APPLICATIONS This application is a continuation-in-part of application Ser. No. 10/633,949, filed Aug. 4, 2003, now U.S. Pat. No. 6,932,770; and this application is also a continuation-in-part of application Ser. No. 10/997,059, filed Nov. 24, 2004, now U.S. Pat. No. 7,717,850 which claims priority to provisional application 60/525,330, filed Nov. 26, 2003. Each of the above-identified applications is incorporated herein by reference.
BACKGROUND The usefulness of ultrasound imaging in the medical field is somewhat limited by a low signal-to-noise ratio in the resulting images. When ultrasonic energy is reflected by a nearby specular target such as a tissue interface having relatively large and generally planar surfaces, the reflected energy usually provides a distinct image. However, when ultrasonic energy is reflected from small discrete targets such as cell structures within the tissue having dimensions on the order of the wavelength of the ultrasonic energy, a combination of constructive and destructive interference from a large number of small scatters in a given voxel produces a finely textured salt-and-pepper interference pattern superimposed on the image produced by specular targets. This pattern is commonly referred to as acoustic speckle and may have an intensity equal to or greater than other features of the image, particularly at large depths where the signal is relatively small. Other types of noise, including electronic noise (e.g., shot noise) can also degrade the ultrasound images and are also more problematic at large depths where the signal is relatively small.
SUMMARY OF THE INVENTION Improved ultrasound images are obtained using signal processing techniques that distinguish between signal and noise based on frequency characteristics (i.e., spectral characteristics) of the received ultrasound signals. The ultrasound images are then modified to reduce the negative impact of noise on the image.
DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 1 is an overall block diagram of a system that may be used for continuous long term monitoring of cardiac function by direct visualization of the heart. An ultrasound system 200 is used to monitor the heart 110 of the patient 100 by sending driving signals into a probe 50 and processing the return signals received from the probe into images, using the image processing algorithms described below. The images generated by those algorithms are then displayed on a monitor 210, in any conventional manner. It should be noted that while the embodiments discussed herein are described primarily in the context of transesophageal echocardiography (TEE), the invention may also be used in other contexts, including both medical and non-medical uses, as will be appreciated by persons skilled in the relevant arts.
ΔθAZ=1.22�λ/d AZ andΔθEL=1.22�λ/d EL where ΔθAZ and ΔθEL are the azimuth and elevation resolutions, respectively, (both measured in radians); and dAZ and dEL are the azimuth and elevation apertures, respectively. These components may be combined into a single equation for overall resolution as a function of area and frequency, as follows:
For the first algorithm (i.e., the intensity algorithm) the samples of the scan line is divided into a plurality of pixels, with each pixel containing a plurality of samples. In the FIG. 13 example, each pixel contains 16 samples, as indicated by the boxes labeled �WIAP j� (which stands for �Window for Intensity Algorithm for Pixel j, where j is an integer from 0-8) that appear below the corresponding samples. Pixel data generated by signal processing is associated with the center position of the corresponding pixel. Of course, other numbers of samples per pixels could also be used instead of 16. In one preferred embodiment, for example, each pixel contains eight samples. The intensity algorithm is preferably a conventional image processing algorithm that converts the samples into a conventional image. The raw intensity for any given pixel is determined based on the amplitude of the samples that correspond to that pixel, with higher intensities corresponding to larger amplitudes. In the case of a 16 sample pixel, the average of those 16 samples would be used to determine the raw intensity at the pixel (with higher average intensity values appearing brighter and lower average intensity values appearing darker). Optionally, the raw intensity level of the pixel (or the samples that make up that pixel) may be compressed using conventional procedures such as logarithmic compression.
Δt=1/f c=1/(5 MHz)=0.200 μs,and thusΔr 0=0.77 mm/μs�0.200 μs=0.154 mm.
The inventors have determined that cardiac ultrasound images are dramatically improved when the intensity of the areas with R-values corresponding to muscle is increased to about 120% of its original value, and when the intensity of the areas with R-values corresponding to blood is decreased to between about 20% and 50% of its original value. Thus, in step 3 of FIG. 14, a gain factor of about 1.2 is assigned to those portions of the image with R values of about 0.45, and a gain factor of between about 0.2 and 0.5 is assigned to those portions of the image with R values of about 0.20. This gain factor is a multiplicative adjustment factor that is referred to herein as a �feature gain factor� or FGF because the gain is feature dependant.
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