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20162026
most citedDeep Learning for Quality Control of Subcortical Brain 3D Shape Models

1 citations · 2 across the 12 of their papers we have counts for

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q-bio.NC2018★ 1 cited

Deep Learning for Quality Control of Subcortical Brain 3D Shape Models

Dmitry Petrov, Boris A. Gutman Egor Kuznetsov, Theo G. M. van Erp +70

We present several deep learning models for assessing the morphometric fidelity of deep grey matter region models extracted from brain MRI. We test three different convolutional ne…

q-bio.NC2018

Connectivity-Driven Brain Parcellation via Consensus Clustering

Anvar Kurmukov, Ayagoz Mussabayeva, Yulia Denisova +2

We present two related methods for deriving connectivity-based brain atlases from individual connectomes. The proposed methods exploit a previously proposed dense connectivity repr…

q-bio.NC2017

Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification

Dmitry Petrov, Alexander Ivanov, Joshua Faskowitz +5

There is no consensus on how to construct structural brain networks from diffusion MRI. How variations in pre-processing steps affect network reliability and its ability to disting…

q-bio.NC2017

A Restaurant Process Mixture Model for Connectivity Based Parcellation of the Cortex

Daniel Moyer, Boris A Gutman, Neda Jahanshad +1

One of the primary objectives of human brain mapping is the division of the cortical surface into functionally distinct regions, i.e. parcellation. While it is generally agreed tha…

q-bio.NC2017

Structural Connectome Validation Using Pairwise Classification

Dmitry Petrov, Boris Gutman, Alexander Ivanov +4

In this work, we study the extent to which structural connectomes and topological derivative measures are unique to individual changes within human brains. To do so, we classify st…

q-bio.NC2016

An Empirical Study of Continuous Connectivity Degree Sequence Equivalents

Daniel Moyer, Boris A. Gutman, Joshua Faskowitz +2

In the present work we demonstrate the use of a parcellation free connectivity model based on Poisson point processes. This model produces for each subject a continuous bivariate i…

q-bio.NC2016

A Continuous Model of Cortical Connectivity

Daniel Moyer, Boris A. Gutman, Joshua Faskowitz +2

We present a continuous model for structural brain connectivity based on the Poisson point process. The model treats each streamline curve in a tractography as an observed event in…