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A deep learning approach for morphological feature extraction based on variational auto-encoder: an application to mandible shape

Biology

A deep learning approach for morphological feature extraction based on variational auto-encoder: an application to mandible shape

M. Tsutsumi, N. Saito, et al.

Explore the groundbreaking Morpho-VAE, a unique framework that employs deep learning for shape analysis in image data. This innovative tool, developed by Masato Tsutsumi, Nen Saito, Daisuke Koyabu, and Chikara Furusawa, excels at distinguishing morphological features among different classes, particularly in primate mandible images, showcasing its potential for biological discoveries.

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