SE-U-Net: Contextual Segmentation by Loosely Coupled Deep Networks for Medical Imaging Industry.
Lin-Yi JiangCheng-Ju KuoTang-Hsuan OMin-Hsiung HungChao-Chun ChenPublished in: ACIIDS (2021)
Keyphrases
- medical imaging
- loosely coupled
- medical images
- image segmentation
- tightly coupled
- image analysis
- x ray
- image processing and analysis
- medical image processing
- computed tomography
- anatomical structures
- web services
- image processing
- brain mr images
- volumetric data
- medical image analysis
- ct images
- image registration
- distributed systems
- imaging modalities
- image guided
- magnetic resonance images
- shape analysis
- highly distributed
- computer aided diagnosis
- biomedical engineering
- service oriented architecture
- remote sensing
- magnetic resonance imaging
- medical image segmentation
- mri scans
- deformable models
- web service technology
- image guided surgery
- brain structures
- computer vision
- biomedical imaging
- shape prior
- pattern recognition
- case study
- high resolution
- mri brain