Patrick Bardsley

NA
4papers
36citations
Novelty33%
AI Score18

4 Papers

NAJan 8, 2016
Kirchhoff migration without phases

Patrick Bardsley, Fernando Guevara Vasquez

We present a simple, frequency domain, preprocessing step to Kirchhoff migration that allows the method to image scatterers when the wave field phase information is lost at the receivers, and only intensities are measured. The resulting imaging method does not require knowing the phases of the probing field or manipulating the phase of the wave field at the receivers. In a regime where the scattered field is small compared to the probing field, the problem of recovering the full-waveform scattered field from intensity data can be formulated as an embarrassingly simple least-squares problem. Although this only recovers the projection (on a known subspace) of the full-waveform scattered field, we show that, for high frequencies, this projection gives Kirchhoff images asymptotically identical to the images obtained with full waveform data. Our method can also be used when the source is modulated by a Gaussian process and autocorrelations are measured at an array of receivers.

NAMar 30, 2018
Imaging small polarizable scatterers with polarization data

Patrick Bardsley, Maxence Cassier, Fernando Guevara Vasquez

We present a method for imaging small scatterers in a homogeneous medium from polarization measurements of the electric field at an array. The electric field comes from illuminating the scatterers with a point source with known location and polarization. We view this problem as a generalized phase retrieval problem with data being the coherency matrix or Stokes parameters of the electric field at the array. We introduce a simple preprocessing of the coherency matrix data that partially recovers the ideal data where all the components of the electric field are known for different source dipole moments. We prove that the images obtained using an electromagnetic version of Kirchhoff migration applied to the partial data are, for high frequencies, asymptotically identical to the images obtained from ideal data. We analyze the image resolution and show that polarizability tensor components in an appropriate basis can be recovered from the Kirchhoff images, which are tensor fields. A time domain interpretation of this imaging problem is provided and numerical experiments are used to illustrate the theory.

MED-PHJul 3, 2017
Quantitative Photoacoustic Imaging of Two-photon Absorption

Patrick Bardsley, Kui Ren, Rongting Zhang

Two-photon absorption photoacoustic tomography (TP-PAT) is a recent hybrid imaging modality that aims at reconstructing two-photon absorption properties of heterogeneous media from measured ultrasound signals generated by the photoacoustic effect. While there have been extensive experimental studies in recent years to show the great promises of TP-PAT, very little has been done on developing computational methods for quantitative image reconstruction in this imaging modality. In this work, we present a mathematical model for quantitative TP-PAT in diffusive media. We implemented a computational strategy for the reconstruction of the optical absorption coefficients, and provide numerical simulations based on synthetic acoustic data to demonstrate the feasibility of quantitative reconstructions in TP-PAT.

OPTICSMay 26, 2015
Imaging with power controlled source pairs

Patrick Bardsley, Fernando Guevara Vasquez

Scatterers in a homogeneous medium are imaged by probing the medium with two point sources of waves modulated by correlated signals and by measuring only intensities at one single receiver. For appropriately chosen source pairs, we show that full waveform array measurements can be recovered from such intensity measurements by solving a linear least squares problem. The least squares solution can be used to image with Kirchhoff migration, even if the solution is determined only up to a known one-dimensional nullspace. The same imaging strategy can be used when the medium is probed with point sources driven by correlated Gaussian processes and autocorrelations are measured at a single location. Since autocorrelations are robust to noise, this can be used for imaging when the probing wave is drowned in background noise.