Multi-scale segmentation squeeze-and-excitation UNet with conditional random field for segmenting lung tumor from CT images.
Baihua ZhangShouliang QiYanan WuXiaohuan PanYudong YaoWei QianYubao GuanPublished in: Comput. Methods Programs Biomed. (2022)
Keyphrases
- ct images
- conditional random fields
- multiscale
- medical images
- treatment planning
- image segmentation
- pet ct
- medical imaging
- computed tomography
- crf model
- lung parenchyma
- segmentation method
- lung nodules
- ct scans
- computer tomography
- superpixels
- ground glass opacity
- contrast enhanced
- accurate segmentation
- graphical models
- fracture detection
- pet images
- lymph nodes
- markov random field
- hidden markov models
- probabilistic model
- generative model
- brain tumors
- information extraction
- pairwise
- higher order
- automated segmentation
- segmentation algorithm
- level set
- region growing
- region of interest
- mr images
- ct data
- automatic segmentation
- lung cancer
- imaging modalities
- x ray
- medical image processing
- radiation therapy
- shape prior
- image guided
- magnetic resonance images
- magnetic resonance imaging
- computer vision
- computer aided
- breast cancer
- deformable models
- natural images
- image processing