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

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

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: United States : Molecular oncology , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 679838

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.
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