High-Quality Plane Wave Compounding Using Convolutional Neural Networks
Single plane wave (PW) imaging produces ultrasound images of poor quality at high frame rates (ultrafast). High-quality PW imaging usually relies on the coherent compounding of several successive steered emissions (typically more than ten), which in turn results in a decreased frame rate. We propose...
| Veröffentlicht in: | IEEE transactions on ultrasonics, ferroelectrics, and frequency control. - 1986. - 64(2017), 10 vom: 09. Okt., Seite 1637-1639 |
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| Weitere Verfasser: | , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2017
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on ultrasonics, ferroelectrics, and frequency control |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
| Zusammenfassung: | Single plane wave (PW) imaging produces ultrasound images of poor quality at high frame rates (ultrafast). High-quality PW imaging usually relies on the coherent compounding of several successive steered emissions (typically more than ten), which in turn results in a decreased frame rate. We propose a new strategy to reduce the number of emitted PWs by learning a compounding operation from data, i.e., by training a convolutional neural network to reconstruct high-quality images using a small number of transmissions. We present experimental evidence that this approach is promising, as we were able to produce high-quality images from only three PWs, competing in terms of contrast ratio and lateral resolution with the standard compounding of 31 PWs ( 10× speedup factor) |
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| Beschreibung: | Date Completed 26.11.2018 Date Revised 26.11.2018 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1525-8955 |
| DOI: | 10.1109/TUFFC.2017.2736890 |