Challenge on Ultrasound Beamforming with Deep Learning (CUBDL)

Warning message

You must login to view this form.
End Date:
09/08/2020
Citation Author(s):
Muyinatu
Bell
Johns Hopkins University
Jiaqi
Huang
Johns Hopkins University
Submitted by:
Muyinatu Lediju Bell
Last updated:
Tue, 10/06/2020 - 15:18
DOI:
10.21227/f0hn-8f92
Links:
License:
Creative Commons Attribution

Abstract 

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.

Instructions: 
  • 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!

 

Comments

Are there any test datasets available to get started with?

Dataset Files

You must be an approved participant in this data competition to access dataset files. To request access you must first login.

Login