Photonics West 2022 in San Francisco
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Conference 11960 > Paper 11960-75
Paper 11960-75

Photoacoustic deep tissue imaging enhanced by ultrasound-guided deep convolution neural networks

25 January 2022 • 3:45 PM - 4:00 PM PST | Room 211 (Level 2 South)

Abstract

Photoacoustic imaging is an imaging modality that combines the advantages of rich contrast from optical imaging and deep penetration depth of ultrasound imaging. Nevertheless, the penetration depth of photoacoustic imaging remains limited due to the optical tissue scattering; an analytical compensation is nearly impossible for an imaging target with several tissue types. Here we present an ultrasound-guided deep-learning approach to extend the depth of photoacoustic imaging. Our model can effectively identify the structure and enhance the signal across modality with the structural information acquired from an ultrasound image. With the pre-trained model, we achieved a deep-tissue photoacoustic imaging.

Presenter

Univ. of Illinois (United States)
Hsuan-Kai Huang received the B.Sc. degree in physics from National Taiwan University, Taipei, Taiwan in 2018. He is currently a PhD candidate of Electrical and Computer engineering in University of Illinois, Urbana-Champaign, Urbana. His research interests include photoacoustic imaging and photoacoustic computed tomography.
Presenter/Author
Univ. of Illinois (United States)
Author
Univ. of Illinois (United States)
Author
Univ. of Illinois (United States)
Author
Carle Illinois College of Medicine, Univ. of Illinois (United States)