activity
20162026
most citedQuantifying topological invariants of neuronal morphologies

10 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

physics.med-ph2026★ 1 cited

Contextual Cellular Growth (ConCeG) of neural cells for realistic grey matter tissue generation for diffusion MRI simulations

Charlie Aird-Rossiter, Kadir Şimşek, Maëliss Jallais +3

Accurate interpretation of diffusion magnetic resonance imaging (dMRI) signals in grey matter (GM) remains challenging due to the complex, heterogeneous, and densely packed cellula…

math.AT2024

Decomposing the Persistent Homology Transform of Star-Shaped Objects

Shreya Arya, Barbara Giunti, Abigail Hickok +3

In this paper, we study the geometric decomposition of the degree- Persistent Homology Transform (PHT) as viewed as a persistence diagram bundle. We focus on star-shaped objects…

math.AT2021★ 1 cited

From Trees to Barcodes and Back Again II: Combinatorial and Probabilistic Aspects of a Topological Inverse Problem

Justin Curry, Jordan DeSha, Adélie Garin +3

In this paper we consider two aspects of the inverse problem of how to construct merge trees realizing a given barcode. Much of our investigation exploits a recently discovered con…

math.AT2020★ 4 cited

From trees to barcodes and back again: theoretical and statistical perspectives

Lida Kanari, Adélie Garin, Kathryn Hess

Methods of topological data analysis have been successfully applied in a wide range of fields to provide useful summaries of the structure of complex data sets in terms of topologi…

q-bio.NC2016★ 10 cited

Quantifying topological invariants of neuronal morphologies

Lida Kanari, Paweł Dłotko, Martina Scolamiero +4

Nervous systems are characterized by neurons displaying a diversity of morphological shapes. Traditionally, different shapes have been qualitatively described based on visual inspe…