About this item:

70 Views | 30 Downloads

Author Notes:

Corresponding Author: Joel Saltz, Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11794. Phone: 631-638-2590; Fax: 631-638-1323; joel.saltz@stonybrookmedicine.edu

Conception and design: J. Saltz, A. Sharma, E. Bremer, J.S. Almeida, Y. Gao, M. Saltz, T. Kurc

Development of methodology: J. Saltz, A. Sharma, G. Iyer, E. Bremer, F. Wang, A. Jasniewski, J.S. Almeida, Y. Gao, M. Saltz, T. Kurc

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): A. Sharma, F. Wang, T. Zhao

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): A. Sharma, F. Wang, J.S. Almeida, Y. Gao

Writing, review, and/or revision of the manuscript: J. Saltz, A. Sharma, J.S. Almeida, T. Kurc

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): A. Sharma, G. Iyer, E. Bremer, A. Jasniewski, M. Saltz

Study supervision: A. Sharma, T. Kurc

Other (software developer): T. DiPrima

Other (provided pathology expertise and user interface feedback): T. Zhao

Subjects:

Research Funding:

This work was supported in part by 1U24CA180924-01A1 from the NCI, and R01LM011119-01 and R01LM009239 from the NLM and by NCIP/Leidos 14 × 138.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Oncology

A Containerized Software System for Generation, Management, and Exploration of Features from Whole Slide Tissue Images

Show all authors Show less authors

Tools:

Journal Title:

Cancer Research

Volume:

Volume 77, Number 21

Publisher:

, Pages E79-E82

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Well-curated sets of pathology image features will be critical to clinical studies that aim to evaluate and predict treatment responses. Researchers require information synthesized across multiple biological scales, from the patient to the molecular scale, to more effectively study cancer. This article describes a suite of services and web applications that allow users to select regions of interest in whole slide tissue images, run a segmentation pipeline on the selected regions to extract nuclei and compute shape, size, intensity, and texture features, store and index images and analysis results, and visualize and explore images and computed features. All the services are deployed as containers and the user-facing interfaces as web-based applications. The set of containers and web applications presented in this article is used in cancer research studies of morphologic characteristics of tumor tissues. The software is free and open source. Cancer Res; 77(21); e79-82.

Copyright information:

© 2017 American Association for Cancer Research.

Export to EndNote