Subject-Specific Brain Activity Analysis in fMRI Data Using Merge Trees

Rasheed, Farhan; Jönsson, Daniel; Nilsson, Emma; Masood, Talha Bin; Hotz, Ingrid

doi:10.1109/topoinvis57755.2022.00018

Cited by 2 publications

(1 citation statement)

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“…This corresponds to a set of extrema falling in a level set adding (or respectively subtracting) a local offset threshold from its dominant extremum. This feature definition has been used for cyclone definition [7,20] and also in the medical context of building a patient-specific brain atlas [24]. There are other more application-specific feature definitions using critical points.…”

Section: Related Workmentioning

confidence: 99%

Towards Benchmark Data Generation for Feature Tracking in Scalar Fields

Nilsson

Lukasczyk

Masood

et al. 2022

2022 Topological Data Analysis and Visualization (TopoInVis)

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Feature tracking is a common task in visualization applications, where methods based on topological data analysis (TDA) have successfully been applied in the past for feature definition as well as tracking. In this work, we focus on tracking extrema of temporal scalar fields. A family of TDA approaches address this task by establishing one-to-one correspondences between extrema based on discrete gradient vector fields. More specifically, two extrema of subsequent time steps are matched if they fall into their respective ascending and descending manifolds. However, due to this oneto-one assignment, these approaches are prone to fail where, e.g., extrema are located in regions with low gradient magnitude, or are located close to boundaries of the manifolds. Therefore, we propose a probabilistic matching that captures a larger set of possible correspondences via neighborhood sampling, or by computing the overlap of the manifolds. We illustrate the usefulness of the approach with two application cases.

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Section: Related Workmentioning

confidence: 99%