no code implementations • 15 Dec 2022 • François Lecomte, Jean-Louis Dillenseger, Stéphane Cotin
From this dataset, a neural network is trained to recover the unknown 3D displacement field from a single projection image.
no code implementations • 15 Aug 2021 • Song Wang, Yuting He, Youyong Kong, Xiaomei Zhu, Shaobo Zhang, Pengfei Shao, Jean-Louis Dillenseger, Jean-Louis Coatrieux, Shuo Li, Guanyu Yang
We propose a novel weakly supervised learning framework, Cycle Prototype Network, for 3D renal compartment segmentation.
no code implementations • ECCV 2020 • Yuting He, Tiantian Li, Guanyu Yang, Youyong Kong, Yang Chen, Huazhong Shu, Jean-Louis Coatrieux, Jean-Louis Dillenseger, Shuo Li
Deep learning-based medical image registration and segmentation joint models utilize the complementarity (augmentation data or weakly supervised data from registration, region constraints from segmentation) to bring mutual improvement in complex scene and few-shot situation.
no code implementations • 30 Nov 2019 • Yannick Wend Kuni Zoetgnande, Geoffroy Cormier, Alain-Jérôme Fougères, Jean-Louis Dillenseger
Finally, we showed that our method could extract four times more matches than a baseline method ORB + OpenCV KNN matching on low-resolution images.