Automatic cervical cancer segmentation in multimodal magnetic resonance imaging using an EfficientNet encoder in UNet++ architecture.
Shan JinHongming XuYue DongXinyu HaoFengying QinQi XuYong ZhuFengyu CongPublished in: Int. J. Imaging Syst. Technol. (2023)
Keyphrases
- magnetic resonance imaging
- medical images
- lesion segmentation
- cervical cancer
- mri images
- computer aided diagnosis
- medical imaging
- mri data
- magnetic resonance images
- fully automatic
- positron emission tomography
- breast mri
- partial volume effects
- long axis
- anatomical structures
- image segmentation
- carotid artery
- brain mri
- diffusion tensor images
- imaging modalities
- computer tomography
- partial volume
- medical image analysis
- segmentation algorithm
- semi automatic
- mr images
- segmentation method
- multiple sclerosis
- image analysis
- brain tumors
- ct images
- x ray
- computer vision
- image registration
- beating heart
- computer assisted
- automatic segmentation
- clinical applications
- high quality
- neural network