Multi-view Attention for gestational age at birth prediction

Autor:	Leclercq, Mathieu, Styner, Martin, Prieto, Juan Carlos
Rok vydání:	2022
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	We present our method for gestational age at birth prediction for the SLCN (surface learning for clinical neuroimaging) challenge. Our method is based on a multi-view shape analysis technique that captures 2D renderings of a 3D object from different viewpoints. We render the brain features on the surface of the sphere and then the 2D images are analyzed via 2D CNNs and an attention layer for the regression task. The regression task achieves a MAE of 1.637 +- 1.3 on the Native space and MAE of 1.38 +- 1.14 on the template space. The source code for this project is available in our github repository https://github.com/MathieuLeclercq/SLCN_challenge_UNC Comment: 7 pages, 5 figures, 1 table
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2207.04130 Zobrazit plný text záznamu View this record from Arxiv