Image Reconstruction in Exploration Geophysics

Robinson, Enders A.

doi:10.1109/t-su.1984.31506

Cited by 18 publications

(3 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are numerous potential applications of DT that can be found in various scientific fields Tabbara et al, 1988;Mueller et al, 1979;Kino, 1979;Devaney, 1984;Robinson, 1984). Recently, there has also been considerable interest in using DT to perform coherent x-ray imaging using third-generation synchrotron sources (Cheng and Han, 2001).…”

Section: Introductionmentioning

confidence: 99%

Breast Cancer Detection and Management Using 3D Quantitative Ultrasonic Diffraction Tomography

Pan¹

2002

View full text Add to dashboard Cite

SUPPLEMENTARY NOTES 12a. DISTRIBUTION / AVAILABILITY STATEMENTApproved for Public Release; Distribution Unlimited 12b. DISTRIBUTION CODE Abstract (Maximum 200 Words) (abstract should contain no oroorietarv or confidential information)The broad objective of the proposed project is to investigate, develop, and evaluate the application of three-dimensional (3D) ultrasonic diffraction tomography (UDT) for detection of breast cancer. UDT can be viewed as a generalization of X-ray tomography where X-rays have been replaced with an acoustical wavefield. It can determine refractive index distributions within the breast that are of interest clinically and can be an excellent imaging modality for breast cancer because it can provide important information complementary to that obtained from mammograms and because it is non-invasive, free of radiation hazard, and reproducible. While UDT promises several potentially important advantages over conventional ultrasonic imaging and has found important uses in a wide variety of engineering and scientific disciplines, its apphcation to breast imaging still remains largely unexplored. In the last year, our research on this project has, we believe, been successftil and productive. We have investigated, developed, and evaluated computationally efficient and statistically optimal algorithms for accurate reconstruction of UDT images that may find applications in UDT imaging of breast cancer. We have made contributions to UDT research, as summarized in the report, by addressing numerous scientific and engineering problems involved in UDT image reconstruction. These results are necessary in making UDT a viable medical technique for imaging of breast cancer. SUBJECT TERMSultrasonic diffraction tomography, breast cancer detection Body 4 Key Research Accomplishments 7Reportable Outcomes 8 Conclusions 9References 10Appendices 11 IntroductionUltrasonic diffraction tomography (UDT) [1][2][3] can be viewed as a generalization of X-ray tomography where X-rays have been replaced with an acoustical wavefield. Because UDT is non-invasive, free of radiation hazard, and reproducible, it is potentially an excellent tool for imaging of breast cancer [4,5]. While UDT promises several potentially important advantages over conventional ultrasonic imaging and has found important uses in a wide variety of engineering and scientific disciplines, its appHcation to imaging of breast cancer still remains largely unexplored. The broad objective of the proposed project is to investigate, develop, and evaluate computationally efficient [6] and statistically optimal [7][8][9] algorithms for accurate image reconstruction in three-dimensional (3D) UDT imaging of the breast cancer. In the last year, our research on this project has, we believe, been successful and productive. The report below summarizes our research activities and results on the project to date. BodyOur research activities on the project to date can be grouped naturally into 4 categories. The first was the investigation of efficient linear algorithms...

show abstract

Section: Introductionmentioning

confidence: 99%

Breast Cancer Detection and Management Using 3D Quantitative Ultrasonic Diffraction Tomography

Pan¹

2002

View full text Add to dashboard Cite

show abstract

“…There are numerous potential applications of DT that can be found in various scientific fields (Andre et al, 1995;Tabbara et al, 1988;Mueller et al, 1979;Kino, 1979;Devaney, 1984;Robinson, 1984). Recently, there has also been considerable interest in using DT to perform coherent x-ray imaging using third-generation synchrotron sources (Cheng and Han, 2001).…”

Section: Introductionmentioning

confidence: 99%

Numerically robust minimal‐scan reconstruction algorithms for diffraction tomography via radon transform inversion

Anastasio

Pan

2002

Int J Imaging Syst Tech

View full text Add to dashboard Cite

ABSTRACT:It is widely believed that measurements from a full angular range of 2 are generally required to exactly reconstruct a complex-valued refractive index distribution in diffraction tomography (DT). In this work, we developed a new class of minimal-scan reconstruction algorithms for DT that utilizes measurements only over the angular range 0 Յ Յ 3/2 to perform an exact reconstruction. These algorithms, referred to as minimal-scan estimate-combination (MS-E-C) reconstruction algorithms, effectively operate by transforming the DT reconstruction problem into a conventional x-ray CT reconstruction problem that requires inversion of the Radon transform. We performed computer simulations to compare the noise and numerical properties of the MS-E-C algorithms against existing filtered backpropagation-based algorithms.

show abstract

“…Diffraction tomography (DT) is a multiview imaging technique that seeks to determine the distribution of the index of refraction of a scattering object. It has found applications in the fields of medical imaging, underwater sound, nondestructive evaluation of materials, and geophysics (Andre et al, 1995;Rouseff and Porter, 1991;Gelius et al, 1991;Langenberg, 1985;Kino, 1979;Robinson, 1984;Mueller et al, 1979). Unlike conventional X-ray computed tomography (CT), the acoustical or electromagnetic radiation in DT is generally treated in terms of wave fields and satisfies the inhomogeneous Helmholtz equation (Ishimaru, 1978;Chernov, 1969;Morse and Ingard, 1986).…”

Section: Introductionmentioning

confidence: 99%

Investigation of the noise properties of a new class of reconstruction methods in diffraction tomography

Anastasio

Pan

1999

Int. J. Imaging Syst. Technol.

View full text Add to dashboard Cite

In diffraction tomography (DT), the measured scattered data are unavoidably contaminated by noise. Because the detectability of an object in a noisy image relies strongly on the signal-to-noise ratio, it is important in certain applications to reduce the statistical variation in the reconstructed image. Recently, we revealed the existence of statistically complementary information inherent in the scattered data and proposed a linear strategy that makes use of this information to achieve a bias-free reduction of the image variance in two-dimensional (2D) DT. This strategy leads to the development of an infinite class of estimation methods, that from the measured scattered data, can estimate the Radon transform of the scattering object function. From the estimated Radon transforms, one can readily reconstruct the object function by using a variety of existing reconstruction algorithms. The estimation methods in the class are mathematically equivalent, but they respond to noise differently. We investigated the noise properties of these estimation methods by use of computer simulation studies. The results of our simulation studies demonstrate quantitatively that it is possible to achieve a bias-free variance reduction in the reconstructed scattering object by utilizing complementary statistical information that is inherent in the scattered data.

show abstract

Image Reconstruction in Exploration Geophysics

Cited by 18 publications

References 35 publications

Breast Cancer Detection and Management Using 3D Quantitative Ultrasonic Diffraction Tomography

Breast Cancer Detection and Management Using 3D Quantitative Ultrasonic Diffraction Tomography

Numerically robust minimal‐scan reconstruction algorithms for diffraction tomography via radon transform inversion

Investigation of the noise properties of a new class of reconstruction methods in diffraction tomography

Contact Info

Product

Resources

About