Deep learning-based reconstruction of ultrasound images from raw channel data.

Journal: International journal of computer assisted radiology and surgery

PMID: 32495155

Abstract

PURPOSE: We investigate the feasibility of reconstructing ultrasound images directly from raw channel data using a deep learning network. Starting from the raw data, we present the network the full measurement information, allowing for a more generic reconstruction to form, as compared to common reconstructions constrained by physical models using fixed speed of sound assumptions.

Authors

Hannah Strohm

Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany. hannah.strohm@mevis.fraunhofer.de.
Sven Rothlübbers

Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.
Klaus Eickel

University of Bremen, Bremen, Germany.
Matthias Günther

Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.

Keywords

Algorithms Contrast Media Deep Learning Diagnosis, Computer-Assisted Humans Image Processing, Computer-Assisted Models, Theoretical Phantoms, Imaging Reference Values Reproducibility of Results Signal-To-Noise Ratio Ultrasonography

External Resources

View on PubMed Access via DOI PubMed (32495155)

Deep learning-based reconstruction of ultrasound images from raw channel data.

Abstract

Authors

Keywords

External Resources

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