Plane-Wave Fourier-Domain Beamforming with CNN-Assisted Resolution Enhancement
| dc.contributor.author | Musti Venkata, Shravanthi | |
| dc.contributor.supervisor | Rakhmatov, Daler | |
| dc.date.accessioned | 2022-04-06T01:18:16Z | |
| dc.date.available | 2022-04-06T01:18:16Z | |
| dc.date.copyright | 2022 | en_US |
| dc.date.issued | 2022-04-05 | |
| dc.degree.department | Department of Electrical and Computer Engineering | en_US |
| dc.degree.level | Master of Engineering M.Eng. | en_US |
| dc.description.abstract | Ultrafast plane-wave imaging has become a major medical imaging modality with a tremendous potential to advance ultrasound diagnostics. Plane-wave ultrasound imaging enables data acquisition at very high frame rates with a single insonification but can suffer from degraded image quality. The latter can be improved by using multiple plane-wave pulses emitted at different steering angles, which reduces the frame rate but allows for image-enhancing coherent compounding of multiple angle-specific beamformed datasets. With the huge success of deep learning approaches in ultrasound imaging, another promising alternative is to employ an image-enhancing convolutional neural network (CNN) for beamformed data post-processing. This project explores the use of an efficient CNN to enhance the resolution of ultrasound images. Our objective is to keep the plane-wave (PW) image reconstruction cost low. Hence, this work uses fast Fourier-domain migration (FDM) to process the raw channel data in conjunction with a well-known low-complexity CNN called Efficient Sub-Pixel Convolutional Neural Network (ESPCN) to enhance the beamformed data during image reconstruction. To evaluate our approach, we have used two in-vitro experimental datasets from the PICMUS evaluation framework and compared our results with conventional delay-and-sum (DAS) beamforming used for high-resolution image reconstruction. This report shows that the proposed approach outperformed a more expensive DAS beamformer with a significant improvement in B-mode image resolution assessed in terms of full width at half-maximum (FWHM) values measured on 0.1-mm wire targets. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/13851 | |
| dc.language.iso | en | en_US |
| dc.rights | Available to the World Wide Web | en_US |
| dc.subject | plane-wave imaging | en_US |
| dc.subject | frequency-wavenumber migration | en_US |
| dc.subject | image upscaling | en_US |
| dc.subject | convolutional neural network | en_US |
| dc.title | Plane-Wave Fourier-Domain Beamforming with CNN-Assisted Resolution Enhancement | en_US |
| dc.type | project | en_US |