Abstract #1136

Fully automatic segmentation of wrist cartilage on MR images by convolutional neural network

Ekaterina A. Brui¹, Aleksandr Y. Efimtcev^1,2, Vladimir A. Fokin^1,2, Remi Fernandez³, Anatoliy G. Levchuk², Augustin C. Ogier⁴, Irina V. Melchakova¹, David Bendahan⁴, and Anna E. Andreychenko¹

¹The International Research Center Nanophotonics and Metamaterials, University of Information Technology Mechanics and Optics, Saint-Petersburg, Russian Federation, ²Federal Almazov North-West Medical Research Center, Saint-Petersburg, Russian Federation, ³APHM, Service de Radiologie, Hôpital de la Conception, Marseille, France, ⁴CRMBM, Aix-Marseille Universite, Marseille, France

A fully automatic, wrist cartilage segmentation method on magnetic resonance images is developed and validated. The method is based on convolutional neural networks (CNN). Cartilage segmentations obtained with the CNN showed a substantial agreement with manual segmentations for the full 3D wrist images and a good agreement for central coronal slices. The proposed method provided cartilage masks having a high concordance with manually obtained ones.

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