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

被引:0
作者
Prabhakaran, Sandhya [1 ]
Yapp, Clarence [2 ]
Baker, Gregory J. [2 ]
Beyer, Johanna [3 ]
Chang, Young Hwan [4 ]
Creason, Allison L. [4 ]
Krueger, Robert [5 ]
Muhlich, Jeremy [6 ]
Patterson, Nathan Heath [7 ]
Sidak, Kevin [5 ]
Sudar, Damir [8 ]
Taylor, Adam J. [9 ]
Ternes, Luke [4 ]
Troidl, Jakob [3 ]
Yubin, Xie [10 ]
Sokolov, Artem [2 ]
Tyson, Darren R. [11 ]
机构
[1] H Lee Moffitt Canc Ctr & Res Inst, Tampa, FL USA
[2] Harvard Med Sch, Lab Syst Pharmacol, Boston, MA USA
[3] Harvard Univ, Sch Engn & Appl Sci, Cambridge, MA USA
[4] Oregon Hlth & Sci Univ, Dept Biomed Engn, Portland, OR USA
[5] Harvard Univ, Cambridge, MA USA
[6] Harvard Med Sch, Boston, MA USA
[7] Aspect Analyt, Genk, Belgium
[8] Quantitat Imaging Syst, Monroeville, PA USA
[9] Sage Bionetworks, Seattle, WA USA
[10] Mem Sloan Kettering Canc Ctr, New York, NY USA
[11] Vanderbilt Univ, Sch Med, 2220 Pierce Ave PRB 715B, Nashville, TN 37232 USA
关键词
artifact removal; artifacts; cancer; computational scalability; domain representation; image analysis; CELL; ATLAS;
D O I
10.1002/1878-0261.13783
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
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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页数:17
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