Abstract：
:The interest of compressive sampling in ultrasound imaging has been recently extensively evaluated by several research teams. Following the different application setups, it has been shown that the RF data may be reconstructed from a small number of measurements and/or using a reduced number of ultrasound pulse emissions. Nevertheless, RF image spatial resolution, contrast and signal to noise ratio are affected by the limited bandwidth of the imaging transducer and the physical phenomenon related to US wave propagation. To overcome these limitations, several deconvolution-based image processing techniques have been proposed to enhance the ultrasound images. In this paper, we propose a novel framework, named compressive deconvolution, that reconstructs enhanced RF images from compressed measurements. Exploiting an unified formulation of the direct acquisition model, combining random projections and 2D convolution with a spatially invariant point spread function, the benefit of our approach is the joint data volume reduction and image quality improvement. The proposed optimization method, based on the Alternating Direction Method of Multipliers, is evaluated on both simulated and in vivo data.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Chen Z,Basarab A,Kouamé Ddoi
10.1109/TMI.2015.2493241subject
Has Abstractpub_date
2016-03-01 00:00:00pages
728-37issue
3eissn
0278-0062issn
1558-254Xjournal_volume
35pub_type
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