Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

Sandhya Prabhakaran, Clarence Yapp, Gregory J. Baker, Johanna Beyer, Young Hwan Chang, Allison L. Creason, Robert Krueger, Jeremy Muhlich, Nathan Heath Patterson, Kevin Sidak, Damir Sudar, Adam J. Taylor, Luke Ternes, Jakob Troidl, Xie Yubin, Artem Sokolov, Darren R. Tyson

Publications: Contribution to journalArticlePeer Reviewed

Abstract

The National Cancer Institute (NCI) supports numerous research consortia that rely on imaging technologies to study cancerous tissues. To foster collaboration and innovation in this field, the Image Analysis Working Group (IAWG) was created in 2019. As multiplexed imaging techniques grow in scale and complexity, more advanced computational methods are required beyond traditional approaches like segmentation and pixel intensity quantification. In 2022, the IAWG held a virtual hackathon focused on addressing challenges in analyzing complex, high‐dimensional datasets from fixed cancer tissues. The hackathon addressed key challenges in three areas: (1) cell type classification and assessment, (2) spatial data visualization and translation, and (3) scaling image analysis for large, multi‐terabyte datasets. Participants explored the limitations of current automated analysis tools, developed potential solutions, and made significant progress during the hackathon. Here we provide a summary of the efforts and resultant resources and highlight remaining challenges facing the research community as emerging technologies are integrated into diverse imaging modalities and data analysis platforms.
Original languageEnglish
Number of pages17
JournalMolecular Oncology
Early online date10 Feb 2025
DOIs
Publication statusPublished - 10 Feb 2025
Externally publishedYes

Austrian Fields of Science 2012

  • 102003 Image processing
  • 301114 Cell biology
  • 102019 Machine learning
  • 102035 Data science

Keywords

  • artifact removal
  • artifacts
  • cancer
  • computational scalability
  • domain representation
  • image analysis

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