Iterative Reconstruction of Medical Ultrasound Images Using Spectrally Constrained Phase Updates

Oleg Michailovich (1) , Adrian Basarab (2, 3) , Denis Kouamé (2)

1 University of Waterloo [Waterloo]
2 IRIT-MINDS - CoMputational imagINg anD viSion
3 UT3 - Université Toulouse III - Paul Sabatier

Image deconvolution is a standard numerical procedure used in medical ultrasound imaging for improving the resolution and contrast of diagnostic sonograms. However, due to the intrinsic bandlimitedness of ultrasound scanners and the adverse effect of measurement noises, image deconvolution is known to be exceedingly sensitive to the errors incurred during inference of the point spread function (PSF) that characterizes the imaging system in use. In this case, even the slightest errors in specification of the PSF are likely to result in significant artifacts, rendering the reconstructed images worthless. To address the aforementioned problem, this paper describes a new method for blind deconvolution of ultrasound images, in which the errors due to inaccuracies in specification of the PSF are eliminated concurrently with estimation of tissue reflectivity directly from its associated radio-frequency data. A principal derivation and justification of the proposed method are supported by experimental results which demonstrate the effectiveness and viability of the new technique.

Mots clés: Alternating minimization; Blind deconvolution; Medical ultrasound; All-pass filtering

Domaines: Imagerie médicale; Traitement du signal et de l'image [eess.SP]

Oleg Michailovich, Adrian Basarab, Denis Kouamé. Iterative Reconstruction of Medical Ultrasound Images Using Spectrally Constrained Phase Updates. 16th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2019), Apr 2019, Venise, Italy. pp.1765-1768, ⟨10.1109/ISBI.2019.8759245⟩. ⟨hal-02891740⟩