Author Title Type [ Year(Asc)]
B. VanBerlo, Li, B. , Hoey, J. , and Wong, A. , Self-Supervised Pretraining Improves Performance and Inference Efficiency in Multiple Lung Ultrasound Interpretation Tasks, IEEE Access, vol. 11, pp. 135696-135707, 2023.
B. VanBerlo, Li, B. , Wong, A. , Hoey, J. , and Arntfield, R. , Exploring the Utility of Self-Supervised Pretraining Strategies for the Detection of Absent Lung Sliding in M-Mode Lung Ultrasound, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 3076–3085.
C. Dave et al., Prospective Real-Time Validation of a Lung Ultrasound Deep Learning Model in the ICU, Critical Care Medicine, vol. 51, pp. 301–309, 2023.
L. A. Groves, Li, N. , VanBerlo, B. , Veinberg, N. , Peters, T. M. , and Chen, E. C. S. , Improving central line needle insertions using in-situ vascular reconstructions, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, pp. 1-7, 2020.
L. A. Groves, VanBerlo, B. , Veinberg, N. , Alboog, A. , Peters, T. M. , and Chen, E. C. S. , Automatic segmentation of the carotid artery and internal jugular vein from 2D ultrasound images for 3D vascular reconstruction, International Journal of Computer Assisted Radiology and Surgery, 2020.
B. VanBerlo, Ross, M. A. S. , Rivard, J. , and Booker, R. , Interpretable Machine Learning Approaches to Prediction of Chronic Homelessness, pp. 1–14, 2020.
L. A. Groves, VanBerlo, B. , Peters, T. M. , and Chen, E. C. S. , Deep learning approach for automatic out-of-plane needle localisation for semi-automatic ultrasound probe calibration, Healthcare Technology Letters, vol. 6, pp. 204–209, 2019.