@inproceedings{65b0c35b54684c459a170e38323da04c,
title = "A continuous model of cortical connectivity",
abstract = "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 connectome space,here a product space of cortical white matter boundaries. We approximate the model parameter via kernel density estimation. To deal with the heavy computational burden,we develop a fast parameter estimation method by pre-computing associated Legendre products of the data,leveraging properties of the spherical heat kernel. We show how our approach can be used to assess the quality of cortical parcellations with respect to connectivty. We further present empirical results that suggest the “discrete” connectomes derived from our model have substantially higher test-retest reliability compared to standard methods.",
keywords = "Diffusion MRI, Human connectome, Non-parametric estimation",
author = "Daniel Moyer and Gutman, {Boris A.} and Joshua Faskowitz and Neda Jahanshad and Thompson, {Paul M.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 ; Conference date: 21-10-2016 Through 21-10-2016",
year = "2016",
doi = "10.1007/978-3-319-46720-7_19",
language = "English",
isbn = "9783319467191",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "157--165",
editor = "Sebastian Ourselin and Leo Joskowicz and Sabuncu, {Mert R.} and William Wells and Gozde Unal",
booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings",
address = "Germany",
}