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cs.CV2026
Clinical DVH metrics as a loss function for 3D dose prediction in head and neck radiotherapy
Ruochen Gao, Marius Staring, Frank Dankers
Purpose: Deep-learning-based three-dimensional (3D) dose prediction is widely used in automated radiotherapy workflows. However, most existing models are trained with voxel-wise re…
cs.CV2025
MCP-MedSAM: A Powerful Lightweight Medical Segment Anything Model Trained with a Single GPU in Just One Day
Donghang Lyu, Ruochen Gao, Marius Staring
Medical image segmentation involves partitioning medical images into meaningful regions, with a focus on identifying anatomical structures and lesions. It has broad applications in…
cs.CV2024
Swin-LiteMedSAM: A Lightweight Box-Based Segment Anything Model for Large-Scale Medical Image Datasets
Ruochen Gao, Donghang Lyu, Marius Staring
Medical imaging is essential for the diagnosis and treatment of diseases, with medical image segmentation as a subtask receiving high attention. However, automatic medical image se…