Supervised segmentation with domain adaptation for small sampled orbital CT images.
Sungho SuhSojeong CheonWonseo ChoiYeon Woong ChungWon-Kyung ChoJi-Sun PaikSung Eun KimDong-Jin ChangYong Oh LeePublished in: J. Comput. Des. Eng. (2022)
Keyphrases
- ct images
- domain adaptation
- medical images
- medical imaging
- semi supervised
- liver segmentation
- pet ct
- lung nodules
- computed tomography
- fracture detection
- computer tomography
- pet images
- ct scans
- lung parenchyma
- ground glass opacity
- cross domain
- multiple sources
- labeled data
- sentiment classification
- unsupervised learning
- image segmentation
- region of interest
- semi supervised learning
- supervised learning
- level set
- image analysis
- medical image processing
- lymph nodes
- segmentation algorithm
- unlabeled data
- x ray images
- document classification
- x ray
- ct data
- fully automatic
- test data
- training data
- machine learning
- lung disease
- image reconstruction
- transfer learning