← Back to papers

2024 MIDL MIDL 2024

Dense Self-Supervised Learning for Medical Image Segmentation

Authors

Maxime Seince , Loı̈c Le Folgoc , Luiz Facury De Souza , Elsa Angelini

Related papers

Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training 2024

HoVer-NeXt: A Fast Nuclei Segmentation and Classification Pipeline for Next Generation Histopathology 2024

Network conditioning for synergistic learning on partial annotations 2024

Real-time MR-based 3D motion monitoring using raw k-space data 2024

Target and task specific source-free domain adaptive image segmentation 2024