Publication result detail

Features of the linear operator in a process of computation of false positive detection in white matter tractography

PISKOŘOVÁ, Z.

Original Title

Features of the linear operator in a process of computation of false positive detection in white matter tractography

English Title

Features of the linear operator in a process of computation of false positive detection in white matter tractography

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

To date, tractography using magnetic resonance data is the only way how to map white matter structure in living human brain. However, current tractography algorithms carry a burden of high false positive detection rate. COMMIT algorithm reduces the implausible positive connections by incorporation microstructural information into the analysis. In this paper, features of the COMMIT formulation are explored and hypothesis for further exploration is proposed.

English abstract

To date, tractography using magnetic resonance data is the only way how to map white matter structure in living human brain. However, current tractography algorithms carry a burden of high false positive detection rate. COMMIT algorithm reduces the implausible positive connections by incorporation microstructural information into the analysis. In this paper, features of the COMMIT formulation are explored and hypothesis for further exploration is proposed.

Keywords

magnetic resonance, white matter, brain, tracts, tractography, COMMIT

Key words in English

magnetic resonance, white matter, brain, tracts, tractography, COMMIT

Authors

PISKOŘOVÁ, Z.

RIV year

2021

Released

16.06.2020

ISBN

978-80-7582-307-6

Book

Matematika, Informační technologie, aplikované vědy (MITAV 2020)

Pages from

1

Pages to

6

Pages count

6

BibTex

@inproceedings{BUT163994,
  author="Zuzana {Gavorová}",
  title="Features of the linear operator in a process of computation of false positive detection in white matter tractography",
  booktitle="Matematika, Informační technologie, aplikované vědy (MITAV 2020)",
  year="2020",
  pages="1--6",
  isbn="978-80-7582-307-6"
}