4 papers
Abdominal multi-organ segmentation in CT using Swinunter
Mingjin Chen, Yongkang He, Yongyi Lu
Abdominal multi-organ segmentation in computed tomography (CT) is crucial for many clinical applications including disease detection and treatment planning. Deep learning methods h…
Learning to In-paint: Domain Adaptive Shape Completion for 3D Organ Segmentation
Mingjin Chen, Yongkang He, Yongyi Lu +1
We aim at incorporating explicit shape information into current 3D organ segmentation models. Different from previous works, we formulate shape learning as an in-painting task, whi…
A Transformer-based Prediction Method for Depth of Anesthesia During Target-controlled Infusion of Propofol and Remifentanil
Yongkang He, Siyuan Peng, Mingjin Chen +2
Accurately predicting anesthetic effects is essential for target-controlled infusion systems. The traditional (PK-PD) models for Bispectral index (BIS) prediction require manual se…
Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation
Yongkang He, Mingjin Chen, Zhijing Yang +1
This paper seeks to address the dense labeling problems where a significant fraction of the dataset can be pruned without sacrificing much accuracy. We observe that, on standard me…