Multiplexed immunohistochemistry image analysis using sparse coding

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Multiplexed immunohistochemical (IHC) methods have been developed to evaluate multiple protein biomarkers in a single formalin-fixed paraffin-embedded (FFPE) tissue section. Since distinct populations of resident and recruited immune cells in tissues (and tumors) not only regulate progression of malignant disease, these also represent targets for novel immune-based therapies; thus, improved tissue biomarker assessment evaluating immune responses in situ are needed. To objectively identify distinct cell subsets in tissues and tumors, we adopted sparse coding approaches enabling modeling of data vectors as sparse linear combinations of basis elements, to audit cellular presence and phenotypes using image cytometry datasets with unbiased assessments. By doing comparative analyses between manual gating (ground truth) and sparse coding, we report that results are comparable as obtained by manual gating strategies, and demonstrate robustness and objectivity of this novel bioinformatics approach.

Original languageEnglish (US)
Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationSmarter Technology for a Healthier World, EMBC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4046-4049
Number of pages4
ISBN (Electronic)9781509028092
DOIs
StatePublished - Sep 13 2017
Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
Duration: Jul 11 2017Jul 15 2017

Other

Other39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
CountryKorea, Republic of
CityJeju Island
Period7/11/177/15/17

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ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Chang, Y. H., Tsujikawa, T., Margolin, A., Coussens, L., & Gray, J. (2017). Multiplexed immunohistochemistry image analysis using sparse coding. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Smarter Technology for a Healthier World, EMBC 2017 - Proceedings (pp. 4046-4049). [8037744] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2017.8037744