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Thalamic nuclei segmentation using tractography, population-specific priors and local fibre orientation

Research output: Contribution to journalConference paperpeer-review

Carla Semedo, M. Jorge Cardoso, Sjoerd B. Vos, Carole H. Sudre, Martina Bocchetta, Annemie Ribbens, Dirk Smeets, Jonathan D. Rohrer, Sebastien Ourselin

Original languageEnglish
Pages (from-to)383-391
Number of pages9
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Early online date13 Sep 2018
Accepted/In press25 May 2018
E-pub ahead of print13 Sep 2018
Event21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018 - Granada, Spain
Duration: 16 Sep 201820 Sep 2018


King's Authors


The thalamus is a deep grey matter structure that plays an important role in propagating nerve impulses between subcortical regions and the cerebral cortex. It is composed of distinct nuclei that have unique long-range connectivity. Accurate thalamic nuclei segmentation provides insights about structural connectivity and the neurodegeneration mechanisms occurring in distinct brain disorders, for instance Alzheimer’s disease and Frontotemporal dementia (FTD). In this work, we propose a novel thalamic nuclei segmentation approach that relies on tractography, thalamic nuclei priors and local fibre orientation. Validation was performed in a cohort of healthy controls and FTD patients against other thalamus connectivity-based parcellation methods. Results showed that the proposed strategy led to anatomical plausible thalamic nuclei segmentations and was able to detect connectivity differences between controls and FTD patients.

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