Filters included 11 of 52 total posts
March 2023 Cycle Report
20 March 2023 by Chris van Run and Miriam Groeneveld
Cycle report of the research-software engineers of March 2023, including: more statistics on Grand Challenge, updated algorithm-job permissions on Grand Challenge, upgrade the CIRRUS backbone MeVisLab version to v3.6, added a new reader-study workflow for accepting and rejecting findings in both CIRRUS and Grand Challenge.
January 2023 Cycle Report
15 Feb. 2023 by Miriam Groeneveld
This cycle work was done to make algorithm result viewing faster by reusing Cirrus sessions. We also made it possible to select existing images for trying out an Algorithm, creating a Display Set in Reader Studies and creating Archive Items.
December 2022 Cycle Report
10 Jan. 2023 by Miriam Groeneveld and Chris van Run
In this year's first release, we added the option to reuse existing images to run an algorithm on or create an archive item or display set. Previously this was only possible with the python client. We extended our annotation types with the ellipse annotation, to be used in Reader studies or Algorithms. Under the hood, we are working on improving the viewing of pathology images, making them faster and more error-proof. To improve the reliability and ease of use of the GC-API client, we have added retries to certain requests in the client. This should reduce the number of errors that need to be handled by the user.
November 2022 Cycle Report
29 Nov. 2022 by Miriam Groeneveld
A new tool and some bug fixes for the viewer in this cycle, while most effort has gone to the development of Grand Challenge Connect, presented at RSNA! A lot of interesting and exciting developments, so make sure to check out the dedicated blogpost.
Grand Challenge at RSNA 2022
23 Nov. 2022 by James Meakin
Radboudumc will be at RSNA to present the latest developments of Grand Challenge, building on Amazon HealthLake Imaging. Visit us for a hands-on demo at the AWS Booth (6758) between 27-30 November 2022 at McCormick Place in Chicago.
October 2022 Cycle Report
1 Nov. 2022 by Miriam Groeneveld
A relatively small update as we are working hard on something new and exciting, which will be revealed next cycle!
September 2022 Cycle Report
26 Sept. 2022 by Miriam Groeneveld
Highlights include the addition of an angle tool, a rotate tool for pathology images and displaying probability scores for annotations.
August 2022 Cycle Report
22 Aug. 2022 by Miriam Groeneveld
Highlights include the option to send an algorithm result to a reader study, using non-image type values in reader studies, the option to send feedback and more.
June 2022 Cycle Report
8 Aug. 2022 by Miriam Groeneveld, Chris van Run, Harm van Zeeland, James Meakin, Paul K. Gerke and Anne Mickan
Highlights include improvements in type 2 challenge submission workflow, creating non-binary masks, adding static annotations to reader studies and more.
May 2022 Cycle Report
5 July 2022 by Miriam Groeneveld, Harm van Zeeland and Chris van Run
Highlights include viewing a reader's answers, providing default answers for questions in a reader study, starting a reader study at a specific display set and more.
How to build a global, scalable, low-latency, and secure machine learning medical imaging analysis platform on AWS
24 Aug. 2020 by Razvan Ionasec, Bram van Ginneken and James Meakin
It is hard to imagine the future for medical imaging without machine learning (ML) as its central innovation engine. Countless researchers, developers, start-ups, and larger enterprises are engaged in building, training, and deploying machine learning solutions for medical imaging that are posed to transform today’s medical workflows and the future value of imaging in diagnosis and treatment.