التفاصيل البيبلوغرافية
| العنوان: |
Addressing persistent challenges in digital image analysis of cancerous tissues. |
| المؤلفون: |
Prabhakaran S, Yapp C, Baker GJ, Beyer J, Chang YH, Creason AL, Krueger R, Muhlich J, Patterson NH, Sidak K, Sudar D, Taylor AJ, Ternes L, Troidl J, Xie Y, Sokolov A, Tyson DR |
| مؤلفون مشاركون: |
Cell Imaging Hackathon 2022 Participants |
| المصدر: |
BioRxiv : the preprint server for biology [bioRxiv] 2023 Jul 24. Date of Electronic Publication: 2023 Jul 24. |
| نوع المنشور: |
Preprint |
| اللغة: |
English |
| بيانات الدورية: |
Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE |
| مستخلص: |
The National Cancer Institute (NCI) supports many research programs and consortia, many of which use imaging as a major modality for characterizing cancerous tissue. A trans-consortia Image Analysis Working Group (IAWG) was established in 2019 with a mission to disseminate imaging-related work and foster collaborations. In 2022, the IAWG held a virtual hackathon focused on addressing challenges of analyzing high dimensional datasets from fixed cancerous tissues. Standard image processing techniques have automated feature extraction, but the next generation of imaging data requires more advanced methods to fully utilize the available information. In this perspective, we discuss current limitations of the automated analysis of multiplexed tissue images, the first steps toward deeper understanding of these limitations, what possible solutions have been developed, any new or refined approaches that were developed during the Image Analysis Hackathon 2022, and where further effort is required. The outstanding problems addressed in the hackathon fell into three main themes: 1) challenges to cell type classification and assessment, 2) translation and visual representation of spatial aspects of high dimensional data, and 3) scaling digital image analyses to large (multi-TB) datasets. We describe the rationale for each specific challenge and the progress made toward addressing it during the hackathon. We also suggest areas that would benefit from more focus and offer insight into broader challenges that the community will need to address as new technologies are developed and integrated into the broad range of image-based modalities and analytical resources already in use within the cancer research community. |
| معلومات مُعتمدة: |
U54 CA225088 United States CA NCI NIH HHS; U54 CA217450 United States CA NCI NIH HHS; R50 CA243783 United States CA NCI NIH HHS; U2C CA233280 United States CA NCI NIH HHS; U2C CA233262 United States CA NCI NIH HHS; U54 CA209988 United States CA NCI NIH HHS |
| فهرسة مساهمة: |
Keywords: Multiplexed images; artifact removal; cancer; domain representation; image analysis; scalability; thumbnail generation |
| تواريخ الأحداث: |
Date Created: 20230807 Latest Revision: 20231019 |
| رمز التحديث: |
20231020 |
| مُعرف محوري في PubMed: |
PMC10401923 |
| DOI: |
10.1101/2023.07.21.548450 |
| PMID: |
37547011 |
| قاعدة البيانات: |
MEDLINE |
