Now showing items 1-5 of 5
Spatially variant regularization based on model resolution and fidelity embedding characteristics improves photoacoustic tomography
Photoacoustic tomography tends to be an ill-conditioned problem with noisy limited data, requiring imposition of regularization constraints like standard Tikhonov or total-variation to reconstruct meaningful initial pressure ...
Accelerated image reconstruction using extrapolated Tikhonov filtering for photoacoustic tomography
Purpose: Development of simple and computationally efficient extrapolated Tikhonov filtering reconstruction methods for photoacoustic tomography. Methods: The model-based reconstruction algorithms in photoacoustic tomography ...
Modeling errors compensation with total least squares for limited data photoacoustic tomography
The limited data photoacoustic image reconstruction problem is typically solved using either weighted or ordinary least squares (LS), with regularization term being added for stability, which account only for data imperfections ...
Modified delay-and-sum reconstruction algorithm to improve tangential resolution in photoacoustic tomography
In photoacoustic/optoacoustic tomography (PAT/OAT) for a circular scanning geometry, the axial/radial resolution is not variant spatially and also do not depend on the ultrasound transducer (UST) aperture. But the tangential ...
Fractional regularization to improve photoacoustic tomographic image reconstruction
Photoacoustic tomography involves reconstructing the initial pressure rise distribution from the measured acoustic boundary data. The recovery of the initial pressure rise distribution tends to be an ill-posed problem in ...