Reflection-Mode Ultrasound Computed Tomography Based on Wavelet Processing for High-Contrast Anatomical and Morphometric Imaging - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Applied Sciences Année : 2021

Reflection-Mode Ultrasound Computed Tomography Based on Wavelet Processing for High-Contrast Anatomical and Morphometric Imaging

Résumé

Medical B-mode ultrasound is widely used for the examination of children’s limbs, including soft tissue, muscle, and bone. However, for the accurate examination of the bone only, it is often replaced by more restrictive clinical modalities. Several authors have investigated ultrasonic imaging of bone to assess cortical thickness and/or to estimate the wave velocity through the internal structure. The present work focuses on the transverse slice imaging process using reflection-mode ultrasound computed tomography (USCT). The method is valid for imaging soft tissues with similar acoustic impedances, but in the presence of bone, the higher contrasts alter the propagation of ultrasonic waves and reduce the contrast-to-noise ratio (CNR). There is a need to change the methods used for the processing of ultrasonic signals. Our group has developed a wavelet-based coded excitation (WCE) method to process information in frequency and time. The objective of this study is to use the method to improve reflection-mode USCT, at low ultrasonic intensities, to better address organ morphometry. Experimental results on a newborn arm phantom and on an ex vivo chicken drumstick are presented, and the usefulness of this WCE-mode USCT is discussed.
Fichier principal
Vignette du fichier
applsci-11-09368.pdf (12.23 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-03379598 , version 1 (15-10-2021)

Identifiants

Citer

Elise Doveri, Laurent Sabatier, Vincent Long, Philippe Lasaygues. Reflection-Mode Ultrasound Computed Tomography Based on Wavelet Processing for High-Contrast Anatomical and Morphometric Imaging. Applied Sciences, 2021, 11 (20), pp.9368. ⟨10.3390/app11209368⟩. ⟨hal-03379598⟩
31 Consultations
15 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More