Medical imaging has benefited tremendously from the recent surge in data-driven approaches to image formation and analysis. Ultrasound and photoacoustic imaging are two related medical imaging modalities that transmit sound and light, respectively, into the body and measure signals representing the acoustic response from tissue. Images are created from these acoustic signals through the beamforming process. In this talk, I will highlight three applications leveraging data-driven methods to improve medical decisions and expand the availability of advanced algorithms into the clinic including: (1) coherence-based beamforming and its impact on breast imaging, (2) the development of a deep neural network architecture, named CohereNet, to improve the speed and availability of coherence-based beamforming, and (3) a novel auditory photoacoustic-based surgical guidance system for hysterectomy procedures. Together these applications demonstrate an important future for data-driven methods in ultrasound and photoacoustic imaging. Speaker(s): Dr. Alycen Wiacek Bldg: College of Engineering, 5050 Anthony Wayne Dr., DETROIT, Michigan, United States, 48202, Virtual: https://events.vtools.ieee.org/m/356188
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