A Convolutional Autoencoder Approach to Learn Volumetric Shape Representations for Brain Structures
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arXiv
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| Format: | Preprint |
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2018
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| _version_ | 1866914995235717120 |
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| author | Yu, Evan M. Sabuncu, Mert R. |
| author_facet | Yu, Evan M. Sabuncu, Mert R. |
| contents | We propose a novel machine learning strategy for studying neuroanatomical shape variation. Our model works with volumetric binary segmentation images, and requires no pre-processing such as the extraction of surface points or a mesh. The learned shape descriptor is invariant to affine transformations, including shifts, rotations and scaling. Thanks to the adopted autoencoder framework, inter-subject differences are automatically enhanced in the learned representation, while intra-subject variances are minimized. Our experimental results on a shape retrieval task showed that the proposed representation outperforms a state-of-the-art benchmark for brain structures extracted from MRI scans. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_1810_07746 |
| institution | arXiv |
| publishDate | 2018 |
| record_format | arxiv |
| spellingShingle | A Convolutional Autoencoder Approach to Learn Volumetric Shape Representations for Brain Structures Yu, Evan M. Sabuncu, Mert R. Computer Vision and Pattern Recognition We propose a novel machine learning strategy for studying neuroanatomical shape variation. Our model works with volumetric binary segmentation images, and requires no pre-processing such as the extraction of surface points or a mesh. The learned shape descriptor is invariant to affine transformations, including shifts, rotations and scaling. Thanks to the adopted autoencoder framework, inter-subject differences are automatically enhanced in the learned representation, while intra-subject variances are minimized. Our experimental results on a shape retrieval task showed that the proposed representation outperforms a state-of-the-art benchmark for brain structures extracted from MRI scans. |
| title | A Convolutional Autoencoder Approach to Learn Volumetric Shape Representations for Brain Structures |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/1810.07746 |