Signal Processing Seminar

Deep learning in ultrasound imaging

Ruud van Sloun
TU Eindhoven

This talk will elaborate on deep learning strategies in ultrasound systems, from the front-end to advanced applications, thereby discussing the possible impact of deep learning methodologies on many aspects of ultrasound imaging. In particular, it will outline methods that lie at the interface of signal acquisition and machine learning, exploiting both data structure (e.g. sparsity in some domain) and data dimensionality (big data) already at the raw radio-frequency channel stage. Several illustrative examples will be given, covering efficient and effective deep learning solutions for adaptive beamforming and adaptive spectral Doppler through artificial agents, learning of compressive encodings for color Doppler, and a framework for structured signal recovery by learning fast approximations of iterative minimization problems, with applications to clutter suppression and super-resolution ultrasound. These emerging technologies may have a considerable impact on ultrasound imaging, showing promise across key components in the receive processing chain.

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Overview of Signal Processing Seminar