Details about Alycen’s proposal seminar are available here: https://engineering.jhu.edu/ece/events/thesis-proposal-alycen-wiacek/?instance_id=1066#.YGna5khKi8o.
The topics discussed in Alycen’s seminar are summarized in the following publications:
- Wiacek A, Oluyemi E, Myers K, Mullen L, Bell MAL, Coherence-based beamforming increases the diagnostic certainty of distinguishing fluid from solid masses in breast ultrasound exams, Ultrasound in Medicine and Biology, 46(6):1380-1394, 2020 [pdf]
- Wiacek A, González E, Bell MAL, CohereNet: A Deep Learning Architecture for Ultrasound Spatial Correlation Estimation and Coherence-Based Beamforming, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 67(12):2574-2583, 2020 [featured on journal cover] [pdf]
- Wiacek A, Rindal OMH, Falomo E, Myers K, Fabrega-Foster K, Harvey S, Bell MAL, Robust Short-Lag Spatial Coherence Imaging of Breast Ultrasound Data: Initial Clinical Results, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 66(3):527-540, 2019 [pdf]
- Wiacek A, Oluyemi E, Myers K, Mullen L, Bell MAL, Coherence-based beamforming improves the diagnostic certainty of breast ultrasound exams, Proceedings of the 2020 IEEE International Ultrasonics Symposium, Virtual, September 6-11, 2020 [pdf]
- Wiacek A, González E, Dehak N, Bell MAL, CohereNet: A deep learning approach to coherence-based beamforming, Proceedings of the 2019 IEEE International Ultrasonics Symposium, Glasgow, Scotland, October 6-9, 2019 [pdf]
- Wiacek A, Myers K, Falomo E, Rindal OMH, Fabrega-Foster K, Harvey S, Bell MAL, Clinical feasibility of coherence-based beamforming to distinguish solid from fluid hypoechoic breast masses, Proceedings of the 2018 IEEE International Ultrasonics Symposium, Kobe, Japan, October 22-25, 2018 [pdf]