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Super-resolution image reconstruction using diffuse source models.

Publication ,  Journal Article
Ellis, MA; Viola, F; Walker, WF
Published in: Ultrasound in Medicine & Biology
June 2010

Image reconstruction is central to many scientific fields, from medical ultrasound and sonar to computed tomography and computer vision. Although lenses play a critical reconstruction role in these fields, digital sensors enable more sophisticated computational approaches. A variety of computational methods have thus been developed, with the common goal of increasing contrast and resolution to extract the greatest possible information from raw data. This paper describes a new image reconstruction method named the Diffuse Time-domain Optimized Near-field Estimator (dTONE). dTONE represents each hypothetical target in the system model as a diffuse region of targets rather than a single discrete target, which more accurately represents the experimental data that arise from signal sources in continuous space, with no additional computational requirements at the time of image reconstruction. Simulation and experimental ultrasound images of animal tissues show that dTONE achieves image resolution and contrast far superior to those of conventional image reconstruction methods. We also demonstrate the increased robustness of the diffuse target model to major sources of image degradation through the addition of electronic noise, phase aberration and magnitude aberration to ultrasound simulations. Using experimental ultrasound data from a tissue-mimicking phantom containing a 3-mm-diameter anechoic cyst, the conventionally reconstructed image has a cystic contrast of -6.3 dB, whereas the dTONE image has a cystic contrast of -14.4 dB.

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Published In

Ultrasound in Medicine & Biology

DOI

EISSN

1879-291X

ISSN

0301-5629

Publication Date

June 2010

Volume

36

Issue

6

Start / End Page

967 / 977

Related Subject Headings

  • Ultrasonics
  • Phantoms, Imaging
  • Mice
  • Image Processing, Computer-Assisted
  • Heart
  • Echocardiography
  • Animals
  • Algorithms
  • Acoustics
  • 1103 Clinical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
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Ellis, M. A., Viola, F., & Walker, W. F. (2010). Super-resolution image reconstruction using diffuse source models. Ultrasound in Medicine & Biology, 36(6), 967–977. https://doi.org/10.1016/j.ultrasmedbio.2010.03.002
Ellis, Michael A., Francesco Viola, and William F. Walker. “Super-resolution image reconstruction using diffuse source models.Ultrasound in Medicine & Biology 36, no. 6 (June 2010): 967–77. https://doi.org/10.1016/j.ultrasmedbio.2010.03.002.
Ellis MA, Viola F, Walker WF. Super-resolution image reconstruction using diffuse source models. Ultrasound in Medicine & Biology. 2010 Jun;36(6):967–77.
Ellis, Michael A., et al. “Super-resolution image reconstruction using diffuse source models.Ultrasound in Medicine & Biology, vol. 36, no. 6, June 2010, pp. 967–77. Epmc, doi:10.1016/j.ultrasmedbio.2010.03.002.
Ellis MA, Viola F, Walker WF. Super-resolution image reconstruction using diffuse source models. Ultrasound in Medicine & Biology. 2010 Jun;36(6):967–977.
Journal cover image

Published In

Ultrasound in Medicine & Biology

DOI

EISSN

1879-291X

ISSN

0301-5629

Publication Date

June 2010

Volume

36

Issue

6

Start / End Page

967 / 977

Related Subject Headings

  • Ultrasonics
  • Phantoms, Imaging
  • Mice
  • Image Processing, Computer-Assisted
  • Heart
  • Echocardiography
  • Animals
  • Algorithms
  • Acoustics
  • 1103 Clinical Sciences