An EffcientNet-encoder U-Net Joint Residual Refinement Module with Tversky-Kahneman Baroni-Urbani-Buser loss for biomedical image Segmentation.
Do-Hai-Ninh NhamMinh-Nhat TrinhViet-Dung NguyenVan-Truong PhamThi-Thao TranPublished in: Biomed. Signal Process. Control. (2023)
Keyphrases
- image segmentation
- rate distortion
- method for image segmentation
- feedback loop
- boundary detection
- image processing
- bit rate
- graph cuts
- image analysis
- contour detection
- markov random field
- text mining
- level set
- probabilistic relaxation
- gray level
- biomedical data
- multiscale
- low complexity
- region growing
- biomedical literature
- biomedical images
- level set method
- video compression
- deformable models
- refinement process
- segmentation algorithm
- motion estimation
- unsupervised image segmentation
- computer vision
- segmented images
- image sequences
- graph partitioning
- segmentation method
- energy function
- edge detection
- information extraction