SegICL: A Universal In-context Learning Framework for Enhanced Segmentation in Medical Imaging.
Lingdong ShenFangxin ShangYehui YangXiaoshuang HuangShining XiangPublished in: CoRR (2024)
Keyphrases
- medical imaging
- medical images
- image segmentation
- x ray
- image processing and analysis
- medical image processing
- image processing
- image analysis
- volumetric data
- ct images
- shape analysis
- magnetic resonance imaging
- medical image segmentation
- clinical practice
- computed tomography
- image guided surgery
- anatomical structures
- image registration
- computer aided diagnosis
- image guided
- magnetic resonance images
- remote sensing
- biomedical engineering
- medical image analysis
- computer vision
- segmentation method
- brain mr images
- mri scans