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Mu He

2 accepted papers

2025

Weakly-supervised Learning Based Spine Instance Segmentation for MRI Planning

ICASSP 2025accepted

Magnetic Resonance Imaging (MRI) spine planning involves setting several positioning lines, termed localizer, through the intervertebral discs (IVDs) of interest to enable axial scans. Deep learning models that generate IVD masks facilitate the automation of MRI spine planning workflow. However, tra…

Cited by 0SourceScholar
2022

RA-Depth: Resolution Adaptive Self-Supervised Monocular Depth Estimation

ECCV 2022poster

"Existing self-supervised monocular depth estimation methods can get rid of expensive annotations and achieve promising results. However, these methods suffer from severe performance degradation when directly adopting a model trained on a fixed resolution to evaluate at other different resolutions.…