Exploiting Bilateral Symmetry in Brain Lesion Segmentation with Reflective Registration

Kevin Raina, Uladzimir Yahorau, Tanya Schmah

Abstract

Brain lesions, including stroke lesions and tumours, have a high degree of variability in terms of location, size, intensity and form, making automatic segmentation difficult. We propose an improvement to existing segmentation methods by exploiting the bilateral quasi-symmetry of healthy brains, which breaks down when lesions are present. Specifically, we use nonlinear registration of a neuroimage to a reflected version of itself (“reflective registration”) to determine for each voxel its homologous (corresponding) voxel in the other hemisphere. A patch around the homologous voxel is added as a set of new features to the segmentation algorithm. To evaluate this method, we implemented two different CNN-based multimodal MRI stroke lesion segmentation algorithms, and then augmented them by adding extra symmetry features using the reflective registration method described above. For each architecture, we compared the performance with and without symmetry augmentation, on the SISS Training dataset of the Ischemic Stroke Lesion Segmentation Challenge (ISLES) 2015 challenge. Using linear reflective registration improves performance over baseline, but nonlinear reflective registration gives significantly better results: an improvement in Dice coefficient of 13 percentage points over baseline for one architecture and 9 points for the other. We argue for the broad applicability of adding symmetric features to existing segmentation algorithms, specifically using the proposed nonlinear, template-free method.

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Paper Citation


in Harvard Style

Raina K., Yahorau U. and Schmah T. (2020). Exploiting Bilateral Symmetry in Brain Lesion Segmentation with Reflective Registration.In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING, ISBN 978-989-758-398-8, pages 116-122. DOI: 10.5220/0008912101160122


in Bibtex Style

@conference{bioimaging20,
author={Kevin Raina and Uladzimir Yahorau and Tanya Schmah},
title={Exploiting Bilateral Symmetry in Brain Lesion Segmentation with Reflective Registration},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING,},
year={2020},
pages={116-122},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008912101160122},
isbn={978-989-758-398-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING,
TI - Exploiting Bilateral Symmetry in Brain Lesion Segmentation with Reflective Registration
SN - 978-989-758-398-8
AU - Raina K.
AU - Yahorau U.
AU - Schmah T.
PY - 2020
SP - 116
EP - 122
DO - 10.5220/0008912101160122