3D U-JAPA-Net: Mixture of Convolutional Networks for Abdominal Multi-organ CT Segmentation.
Hideki KakeyaToshiyuki OkadaYukio OshiroPublished in: MICCAI (4) (2018)
Keyphrases
- abdominal organs
- medical images
- organ segmentation
- liver segmentation
- computed tomography images
- ct data
- ct scans
- ct volume
- ct images
- computed tomography
- automatic segmentation
- x ray
- medical imaging
- medical image processing
- fully automatic
- medical image segmentation
- automated segmentation
- computer tomography
- anatomical structures
- segmentation algorithm
- mri images
- inter patient
- patient specific
- magnetic resonance
- imaging modalities
- level set
- deformable models
- computer aided diagnosis
- mr images
- social networks
- automatically segmenting
- mri brain
- volume rendering
- magnetic resonance images
- image segmentation
- lung nodules
- treatment planning
- clinical applications
- brain mri
- statistical shape model
- magnetic resonance imaging
- network structure
- image slices
- ct imaging
- image reconstruction
- three dimensional
- white blood
- manual segmentation
- segmentation method