Assessment of rotationally-invariant clustering using streamlet tractography
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Assessment of rotationally-invariant clustering using streamlet tractography. / Liptrot, Matthew George; Lauze, Francois Bernard.
2016. Abstract from 24th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine, Singapore, Singapore.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
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TY - ABST
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 -
ID: 167086560