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Exploratory Assessment of Pulsed-Wave Doppler Representations of Lung Sounds Using Deep Learning: An In-Vitro Phantom Study

Saad, A. A.; Murthi, S. B.; Boctor, E. M.; Teeter, W. A.; Seam, N.

2026-06-10 respiratory medicine
10.64898/2026.06.09.26353787 medRxiv
Show abstract

The increasing availability of portable ultrasound systems motivates exploration of novel approaches to respiratory signal assessment. In this in-vitro study, we investigate whether pulsed-wave (PW) Doppler ultrasound can capture structured spectral patterns from replayed lung sound recordings. Digitized respiratory sounds were replayed through a tissue-mimicking ultrasound phantom, generating 1,478 PW Doppler spectral images from recordings associated with healthy subjects and several externally labeled disease categories. Exploratory classification experiments using a ResNet-18 architecture demonstrated that these Doppler representations contain learnable differences under controlled conditions. These findings motivate further investigation into PW Doppler as a potential representation of respiratory acoustics.

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