Developing an explainable deep learning boundary correction method by incorporating cascaded x-Dim models to improve segmentation defects in liver CT images.
Saeed MohagheghiAmir Hossein ForuzanPublished in: Comput. Biol. Medicine (2022)
Keyphrases
- ct images
- medical images
- deep learning
- medical imaging
- anatomical knowledge
- liver segmentation
- computed tomography
- lung nodules
- pet ct
- ct scans
- computer tomography
- fracture detection
- probabilistic model
- region of interest
- pet images
- multiscale
- treatment planning
- lung parenchyma
- medical image processing
- traumatic brain injury
- medical image segmentation
- machine learning
- ct data
- region growing
- segmentation algorithm
- model selection
- level set
- image segmentation
- imaging modalities
- weakly supervised
- lymph nodes
- fully automatic
- unsupervised learning
- pattern recognition
- image processing