Challenge on Ultrasound Beamforming with Deep Learning (CUBDL)
The purpose of this challenge is to provide standardization of methods for assessing and benchmarking deep learning approaches to ultrasound image formation from ultrasound channel data that will live beyond the challenge.
- Participants will have the freedom to create their own training data to build networks that accomplish specified tasks
- Specified tasks and evaluation methods are described on the challenge website.
- Submissions and data sharing will be facilitated by IEEE DataPort.
Although the challenge is now closed, evaluation code remains available (more details on the challenge website https://cubdl.jhu.edu/), and datasets will be released with a journal paper describing challenge submissions. Stay tuned!