Assessment of rotationally-invariant clustering using streamlet tractography

Matthew George Liptrot; Francois Bernard Lauze

Assessment of rotationally-invariant clustering using streamlet tractography

Matthew George Liptrot, Francois Bernard Lauze

Datalogisk Institut

Abstract

We present a novel visualisation-based strategy for the assessment of a recently proposed clustering technique for raw DWI volumes which derives rotationally-invariant metrics to classify voxels. The validity of the division of all brain tissue voxels into such classes was assessed using the recently developed streamlets visualisation technique, which aims to represent brain fibres by collections of many short streamlines. Under the assumption that streamlines seeded in a cluster should stay within it, we were able to assess how well perceptual tracing could occur across the boundaries of the clusters.

Originalsprog	Engelsk
Publikationsdato	2016
Status	Udgivet - 2016
Begivenhed	24th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine - Suntec Singapore Convention & Exhibition Centre, Singapore, Singapore Varighed: 7 maj 2016 → 13 maj 2016 Konferencens nummer: 24

Konference

Konference	24th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine
Nummer	24
Lokation	Suntec Singapore Convention & Exhibition Centre
Land/Område	Singapore
By	Singapore
Periode	07/05/2016 → 13/05/2016

Adgang til dokumentet

http://dev.ismrm.org/2016/3071.html

Citationsformater

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title = "Assessment of rotationally-invariant clustering using streamlet tractography",

abstract = "We present a novel visualisation-based strategy for the assessment of a recently proposed clustering technique for raw DWI volumes which derives rotationally-invariant metrics to classify voxels. The validity of the division of all brain tissue voxels into such classes was assessed using the recently developed streamlets visualisation technique, which aims to represent brain fibres by collections of many short streamlines. Under the assumption that streamlines seeded in a cluster should stay within it, we were able to assess how well perceptual tracing could occur across the boundaries of the clusters.",

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T1 - Assessment of rotationally-invariant clustering using streamlet tractography

AU - Liptrot, Matthew George

AU - Lauze, Francois Bernard

N1 - Conference code: 24

PY - 2016

Y1 - 2016

N2 - We present a novel visualisation-based strategy for the assessment of a recently proposed clustering technique for raw DWI volumes which derives rotationally-invariant metrics to classify voxels. The validity of the division of all brain tissue voxels into such classes was assessed using the recently developed streamlets visualisation technique, which aims to represent brain fibres by collections of many short streamlines. Under the assumption that streamlines seeded in a cluster should stay within it, we were able to assess how well perceptual tracing could occur across the boundaries of the clusters.

AB - We present a novel visualisation-based strategy for the assessment of a recently proposed clustering technique for raw DWI volumes which derives rotationally-invariant metrics to classify voxels. The validity of the division of all brain tissue voxels into such classes was assessed using the recently developed streamlets visualisation technique, which aims to represent brain fibres by collections of many short streamlines. Under the assumption that streamlines seeded in a cluster should stay within it, we were able to assess how well perceptual tracing could occur across the boundaries of the clusters.

M3 - Conference abstract for conference

T2 - 24th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine

Y2 - 7 May 2016 through 13 May 2016

ER -