Optimized source estimation for full waveform inversion in ultrasound computed tomography

2021 ◽  
Author(s):  
Atsuro Suzuki ◽  
Yushi Tsubota ◽  
Takahide Terada ◽  
Hiroko Yamashita ◽  
Fumi Kato ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Source Estimation ◽  
Ultrasound Computed Tomography

Ultrasonic computed tomography based on full-waveform inversion for bone quantitative imaging

2017 ◽  
Vol 62 (17) ◽  
pp. 7011-7035 ◽  
Author(s):  
Simon Bernard ◽  
Vadim Monteiller ◽  
Dimitri Komatitsch ◽  
Philippe Lasaygues
Keyword(s):  
Computed Tomography ◽  
Quantitative Imaging ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Full Waveform

Source estimation for wavefield-reconstruction inversion

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. R345-R359 ◽  
Author(s):  
Zhilong Fang ◽  
Rongrong Wang ◽  
Felix J. Herrmann
Keyword(s):  
Objective Function ◽  
Prior Information ◽  
Additional Data ◽  
Waveform Inversion ◽  
Search Space ◽  
Full Waveform Inversion ◽  
Auxiliary Variables ◽  
Full Waveform ◽  
Source Estimation ◽  
Exact Data

Source estimation is essential for all wave-equation-based seismic inversions, including full-waveform inversion (FWI) and the recently proposed wavefield-reconstruction inversion (WRI). When the source estimation is inaccurate, errors will propagate into the predicted data and introduce additional data misfit. As a consequence, inversion results that minimize this data misfit may become erroneous. To mitigate the errors introduced by the incorrect and preestimated sources, an embedded procedure that updates sources along with medium parameters is necessary for the inversion. So far, such a procedure is still missing in the context of WRI, a method that is, in many situations, less prone to local minima related to so-called cycle skipping, compared with FWI through exact data fitting. Although WRI indeed helps to mitigate issues related to cycle skipping by extending the search space with wavefields as auxiliary variables, it relies on having access to the correct source functions. To remove the requirement of having the accurate source functions, we have developed a source-estimation technique specifically designed for WRI. To achieve this task, we consider the source functions as unknown variables and arrive at an objective function that depends on the medium parameters, wavefields, and source functions. During each iteration, we apply the so-called variable projection method to simultaneously project out the source functions and wavefields. After the projection, we obtain a reduced objective function that only depends on the medium parameters and invert for the unknown medium parameters by minimizing this reduced objective. Numerical experiments illustrate that this approach can produce accurate estimates of the unknown medium parameters without any prior information of the source functions.

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