Chapter title |
A Continuous Model of Cortical Connectivity
|
---|---|
Chapter number | 19 |
Book title |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016
|
Published in |
Lecture notes in computer science, October 2016
|
DOI | 10.1007/978-3-319-46720-7_19 |
Pubmed ID | |
Book ISBNs |
978-3-31-946719-1, 978-3-31-946720-7
|
Authors |
Daniel Moyer, Boris A. Gutman, Joshua Faskowitz, Neda Jahanshad, Paul M. Thompson, Daniel Moyer, Boris A. Gutman, Joshua Faskowitz, Neda Jahanshad, Paul M. Thompson |
Editors |
Sebastien Ourselin, Leo Joskowicz, Mert R. Sabuncu, Gozde Unal, William Wells |
Abstract |
We present a continuous model for structural brain connectivity based on the Poisson point process. The model treats each stream-line 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. |
Mendeley readers
Geographical breakdown
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Japan | 1 | 3% |
Unknown | 30 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 8 | 26% |
Researcher | 5 | 16% |
Student > Master | 5 | 16% |
Professor | 4 | 13% |
Student > Bachelor | 3 | 10% |
Other | 3 | 10% |
Unknown | 3 | 10% |
Readers by discipline | Count | As % |
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Computer Science | 10 | 32% |
Engineering | 5 | 16% |
Mathematics | 2 | 6% |
Agricultural and Biological Sciences | 2 | 6% |
Biochemistry, Genetics and Molecular Biology | 2 | 6% |
Other | 5 | 16% |
Unknown | 5 | 16% |