Defining patient specific functional parcellations in lesional cohorts via markov random fields

Naresh Nandakumar, Niharika S. D’Souza, Jeff Craley, Komal Manzoor, Jay Pillai, Sachin K Gujar, Haris Sair, Archana Venkataraman

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

Abstract

We propose a hierarchical Bayesian model that refines a population-based atlas using resting-state fMRI (rs-fMRI) coherence. Our method starts from an initial parcellation and then iteratively reassigns the voxel memberships at the subject level. Our algorithm uses a maximum a posteriori inference strategy based on the neighboring voxel assignments and the Pearson correlation coefficients between the voxel time series and the parcel reference signals. Our method is generalizable to different initial atlases, ensures spatial and temporal contiguity in the final network organization, and can handle subjects with brain lesions, whose rs-fMRI data varies tremendously from that of a healthy cohort. We validate our method by comparing the intra-network cohesion and the motor network identification against two baselines: a standard functional parcellation with no reassignment and a recently published method with a purely data-driven reassignment procedure. Our method outperforms the original functional parcellation in intra-network cohesion and both methods in motor network identification.

Original languageEnglish (US)
Title of host publicationConnectomics in NeuroImaging - 2nd International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Proceedings
EditorsGuorong Wu, Markus D. Schirmer, Ai Wern Chung, Islem Rekik, Brent Munsell
PublisherSpringer Verlag
Pages88-98
Number of pages11
ISBN (Print)9783030007546
DOIs
StatePublished - Jan 1 2018
Event2nd International Workshop on Connectomics in NeuroImaging, CNI 2018 held in conjunction with the 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018 - Granada, Spain
Duration: Sep 20 2018Sep 20 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11083 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Workshop on Connectomics in NeuroImaging, CNI 2018 held in conjunction with the 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018
CountrySpain
CityGranada
Period9/20/189/20/18

    Fingerprint

Keywords

  • Markov random field
  • Patient-specific networks
  • Rs-fMRI

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Nandakumar, N., D’Souza, N. S., Craley, J., Manzoor, K., Pillai, J., Gujar, S. K., Sair, H., & Venkataraman, A. (2018). Defining patient specific functional parcellations in lesional cohorts via markov random fields. In G. Wu, M. D. Schirmer, A. W. Chung, I. Rekik, & B. Munsell (Eds.), Connectomics in NeuroImaging - 2nd International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Proceedings (pp. 88-98). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11083 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-00755-3_10