Brain volume mapping for constructing volumetric statistical shape model

Shoko Miyauchi; Ken'ichi Morooka; Yasushi Miyagi; Takaichi Fukuda; Ryo Kurazume

doi:10.1117/12.2519819

27 March 2019 Brain volume mapping for constructing volumetric statistical shape model

Shoko Miyauchi, Ken'ichi Morooka, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume

Proceedings Volume 11050, International Forum on Medical Imaging in Asia 2019; 110501C (2019) https://doi.org/10.1117/12.2519819
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

We propose a new method for mapping onto a brain volume model including inner organs with complicated shapes such as lateral ventricles. The proposed method is based on a volumetric Self-organizing Deformable Model (vSDM) which allows to control the mapping positions of inner organs while preserving geometrical features before and after the mapping. The control sometimes causes the self-intersection of the volume model. The solution for the self-intersection in vSDM is to move vertices of the volume model. However, when the inner organ has complicated shape, the vertex movement cannot always correct the self-intersection. To solve this problem, we extend vSDM by introducing a new process of editing the mesh structure of the volume model. Moreover, by applying the proposed method to six brain volume models, a volumetric Statistical Shape Model (SSM) is constructed which represents the shape variations of not only brain surface but also brain inner organs. From experimental results, we confirmed the volumetric SSM has an acceptable performance compared with general surface SSMs generated by organ surface models.

Citation Download Citation

Shoko Miyauchi, Ken'ichi Morooka, Yasushi Miyagi, Takaichi Fukuda, and Ryo Kurazume "Brain volume mapping for constructing volumetric statistical shape model", Proc. SPIE 11050, International Forum on Medical Imaging in Asia 2019, 110501C (27 March 2019); https://doi.org/10.1117/12.2519819

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