no code implementations • 5 Feb 2024 • Qixiang Ma, Antoine Łucas, Huazhong Shu, Adrien Kaladji, Pascal Haigron
On the local dataset, our weakly-supervised learning approach based on pseudo labels outperforms strong-label-based fully-supervised learning (1. 54\% of Dice score on average), reducing labeling time by around 82. 0\%.
no code implementations • 4 Feb 2024 • Qixiang Ma, Antoine Lucas, Adrien Kaladji, Pascal Haigron
The segmentation of the abdominal aorta in non-contrast CT images is a non-trivial task for computer-assisted endovascular navigation, particularly in scenarios where contrast agents are unsuitable.