Fisher-Rao regularized transport analysis of the glymphatic system and waste drainage Conference Paper


Authors: Elkin, R.; Nadeem, S.; Lee, H.; Benveniste, H.; Tannenbaum, A.
Title: Fisher-Rao regularized transport analysis of the glymphatic system and waste drainage
Conference Title: 23rd International Conference of Medical Image Computing and Computer Assisted Intervention (MICCAI 2020)
Abstract: In this work, a unified representation of all the time-varying dynamics is accomplished with a Lagrangian framework for analyzing Fisher-Rao regularized dynamical optimal mass transport (OMT) derived flows. While formally equivalent to the Eulerian based Schrödinger bridge OMT regularization scheme, the Fisher-Rao approach allows a simple and interpretable methodology for studying the flows of interest in the present work. The advantage of the proposed Lagrangian technique is that the time-varying particle trajectories and attributes are displayed in a single visualization. This provides a natural capability to identify and distinguish flows under different conditions. The Lagrangian analysis applied to the glymphatic system (brain waste removal pathway associated with Alzheimer’s Disease) successfully captures known flows and distinguishes between flow patterns under two different anesthetics, providing deeper insights into altered states of waste drainage. © 2020, Springer Nature Switzerland AG.
Keywords: medical imaging; medical computing; optimal mass transport; time-varying dynamics; fisher-rao regularization; glymphatic system; lagrange multipliers; lagrangian analysis; lagrangian frameworks; lagrangian techniques; particle trajectories; regularization schemes; transport analysis
Journal Title Lecture Notes in Computer Science
Volume: 12267
Conference Dates: 2020 Oct 4-8
Conference Location: Lima, Peru
ISBN: 0302-9743
Publisher: Springer  
Date Published: 2020-01-01
Start Page: 573
End Page: 582
Language: English
DOI: 10.1007/978-3-030-59728-3_56
PROVIDER: scopus
DOI/URL:
Notes: Conference Paper -- Export Date: 2 November 2020 -- Source: Scopus
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  1. Saad Nadeem
    50 Nadeem
  2. Rena Elkin
    15 Elkin