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Communication Dans Un Congrès Année : 2017

Enhanced ultrasound image reconstruction using a compressive blind deconvolution approach

Résumé

Compressive deconvolution, combining compressive sampling and image deconvolution, represents an interesting possibility to reconstruct enhanced ultrasound images from compressed measurements. The model of compressive deconvolution includes, in addition to the measurement matrix, a 2D convolution operator carrying the information on the system point spread function which is usually unkown in practice. In this paper, we propose a novel alternating minimization-based optimization scheme to invert the resulting linear model, to jointly reconstruct enhanced ultrasound images and estimate the point spread function. The performance of the method is evaluated on both Shepp-Logan phantom and simulated ultrasound data.

Domaines

Son [cs.SD]
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Dates et versions

hal-03656980 , version 1 (02-05-2022)

Identifiants

Citer

Zhouye Chen, Adrian Basarab, Denis Kouamé. Enhanced ultrasound image reconstruction using a compressive blind deconvolution approach. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017), Mar 2017, New Orleans, United States. pp.6245--6249, ⟨10.1109/ICASSP.2017.7953357⟩. ⟨hal-03656980⟩
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