Sorry, you need to enable JavaScript to visit this website.

Restoration of ultrasound images using spatially-variant kernel deconvolution

Citation Author(s):
Mihai I. Florea, Adrian Basarab, Denis Kouame, Sergiy A. Vorobyov
Submitted by:
Mihai Florea
Last updated:
17 April 2018 - 9:01pm
Document Type:
Presentation Slides
Document Year:
2018
Event:
Presenters:
Mihai I. Florea
Paper Code:
2938
Categories:
 

Most of the existing ultrasound image restoration methods consider a spatially-invariant point-spread function (PSF) model and circulant boundary conditions. While computationally efficient, this model is not realistic and severely limits the quality of reconstructed images. In this work, we address ultrasound image restoration under the hypothesis of vertical variation of the PSF. To regularize the solution, we use the classical elastic net constraint. Existing methodologies are rendered impractical either due to their reliance on matrix inversion or due to their inability to exploit the strong convexity of the objective. Therefore, we propose an optimization algorithm based on the Accelerated Composite Gradient Method, adapted and optimized for this task. Our method is guaranteed to converge at a linear rate and is able to adaptively estimate unknown problem parameters. We support our theoretical results with simulation examples.

up
0 users have voted: