Integration of spatial distribution in imaging-genetics

Vaishnavi Subramanian, Weizhao Tang, Benjamin Chidester, Jian Ma, Minh N Do

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

Abstract

To better understand diseases such as cancer, it is crucial for computational inference to quantify the spatial distribution of various cell types within a tumor. To this end, we used Ripley’s K-statistic, which captures the spatial distribution patterns at different scales of both individual point sets and interactions between multiple point sets. We propose to improve the expressivity of histopathology image features by incorporating this descriptor to capture potential cellular interactions, especially interactions between lymphocytes and epithelial cells. We demonstrate the utility of the Ripley’s K-statistic by analyzing digital slides from 710 TCGA breast invasive carcinoma (BRCA) patients. In particular, we consider its use in the context of imaging-genetics to understand correlations between gene expression and image features using canonical correlation analysis (CCA). Our analysis shows that including these spatial features leads to more significant associations between image features and gene expression.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings
EditorsGabor Fichtinger, Christos Davatzikos, Carlos Alberola-López, Alejandro F. Frangi, Julia A. Schnabel
PublisherSpringer-Verlag
Pages245-253
Number of pages9
ISBN (Print)9783030009335
DOIs
StatePublished - Jan 1 2018
Event21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018 - Granada, Spain
Duration: Sep 16 2018Sep 20 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11071 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018
CountrySpain
CityGranada
Period9/16/189/20/18

Fingerprint

Spatial Distribution
Gene expression
Spatial distribution
Imaging
Statistics
Imaging techniques
Point Sets
Gene Expression
Statistic
Lymphocytes
Tumors
Point Interactions
Canonical Correlation Analysis
Cell
Interaction
Descriptors
Tumor
Cancer
Quantify
Demonstrate

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Subramanian, V., Tang, W., Chidester, B., Ma, J., & Do, M. N. (2018). Integration of spatial distribution in imaging-genetics. In G. Fichtinger, C. Davatzikos, C. Alberola-López, A. F. Frangi, & J. A. Schnabel (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings (pp. 245-253). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11071 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-030-00934-2_28

Integration of spatial distribution in imaging-genetics. / Subramanian, Vaishnavi; Tang, Weizhao; Chidester, Benjamin; Ma, Jian; Do, Minh N.

Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings. ed. / Gabor Fichtinger; Christos Davatzikos; Carlos Alberola-López; Alejandro F. Frangi; Julia A. Schnabel. Springer-Verlag, 2018. p. 245-253 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11071 LNCS).

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

Subramanian, V, Tang, W, Chidester, B, Ma, J & Do, MN 2018, Integration of spatial distribution in imaging-genetics. in G Fichtinger, C Davatzikos, C Alberola-López, AF Frangi & JA Schnabel (eds), Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11071 LNCS, Springer-Verlag, pp. 245-253, 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018, Granada, Spain, 9/16/18. https://doi.org/10.1007/978-3-030-00934-2_28
Subramanian V, Tang W, Chidester B, Ma J, Do MN. Integration of spatial distribution in imaging-genetics. In Fichtinger G, Davatzikos C, Alberola-López C, Frangi AF, Schnabel JA, editors, Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings. Springer-Verlag. 2018. p. 245-253. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-00934-2_28
Subramanian, Vaishnavi ; Tang, Weizhao ; Chidester, Benjamin ; Ma, Jian ; Do, Minh N. / Integration of spatial distribution in imaging-genetics. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings. editor / Gabor Fichtinger ; Christos Davatzikos ; Carlos Alberola-López ; Alejandro F. Frangi ; Julia A. Schnabel. Springer-Verlag, 2018. pp. 245-253 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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