Segmentation of uterus and placenta in MR images using a fully convolutional neural network.
Maysam ShahediJames D. DormerT. T. Anusha DeviQuyen N. DoYin XiMatthew A. LewisAnanth J. MadhuranthakamDiane M. TwicklerBaowei FeiPublished in: Medical Imaging: Computer-Aided Diagnosis (2020)
Keyphrases
- mr images
- accurate segmentation
- medical images
- convolutional neural network
- brain mr images
- partial volume
- magnetic resonance
- brain tumors
- mr brain
- brain structures
- magnetic resonance images
- manual segmentation
- segmentation result
- bias field
- intensity inhomogeneity
- dice similarity coefficient
- cardiac magnetic resonance
- mr imaging
- mri data
- image data
- intensity distribution
- inhomogeneity correction
- mr brain images
- contrast enhanced
- automated segmentation
- tissue segmentation
- inter patient
- phantom images
- nonrigid registration
- brain mri
- brain tissue
- fully automatic
- brain images
- anatomical structures
- magnetic resonance imaging
- face detection
- medical image analysis
- medical imaging
- automatic segmentation
- prostate cancer
- brain segmentation
- quantitative measurements
- segmentation method
- image segmentation
- image sequences
- lesion segmentation
- atlas based segmentation
- deformable models
- segmentation algorithm
- histological images
- cerebrospinal fluid
- model based segmentation
- image intensity
- computer vision