Work

Sidelobes-Free Wavelet-Based Chirp Compression for Ultrasound Imaging

Year: 2025

Type: conference-paper

Abstract: Chirp-coded excitation improves signal-to-noise ratio in ultrasound imaging, but conventional matched filtering introduces high sidelobes that degrade image quality. Alternatives such as mismatched filtering reduce resolution, while Wiener filtering depends on accurate SNR estimation and may amplify noise. In this work, we adapt the Fourier–Wavelet Regularized Deconvolution (ForWaRD) algorithm for chirp compression, exploiting shrinkage in both Fourier and wavelet domains. Simulations and experiments demonstrate that the proposed wavelet-based filter outperforms conventional methods by combining high axial resolution with strong sidelobe suppression and effective noise reduction.

Source: IEEE International Ultrasonics Symposium

DOI: 10.1109/ius62464.2025.11201375

Authors: Mohamed Tamraoui, Ralph Abirizk, Ewen Carcreff, Barbara Nicolas, Hervé Liebgott

Institutions: Lyon 1 Université, Centre National de la Recherche Scientifique, Inserm, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé, Institut National des Sciences Appliquées de Lyon

Language: English

Topic: Ultrasound Imaging and Elastography

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

Open Access status: green

Funder: Agence Nationale de la Recherche

Award: 3D 1024-channel ultrasound medical imaging: a system for academic and clinical research