Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning
- 21 May 2015
- journal article
- Published by Elsevier BV in Medical Image Analysis
- Vol. 24 (1), 18-27
- https://doi.org/10.1016/j.media.2015.05.009
Abstract
No abstract availableKeywords
Funding Information
- NIH (1R03EB012461)
- NIH (2R01EB006136)
- NIH (R01EB006193)
- VICTR (VR3029)
- NIH (UL1 RR024975-01)
- NIH (UL1 TR000445-06)
- NIH (P30 CA068485)
This publication has 27 references indexed in Scilit:
- Statistical 4D graphs for multi-organ abdominal segmentation from multiphase CTMedical Image Analysis, 2012
- Statistical shape models for 3D medical image segmentation: A reviewMedical Image Analysis, 2009
- Segmentation of multiple organs in non-contrast 3D abdominal CT imagesInternational Journal of Computer Assisted Radiology and Surgery, 2007
- Simultaneous Truth and Performance Level Estimation (STAPLE): An Algorithm for the Validation of Image SegmentationIEEE Transactions on Medical Imaging, 2004
- Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brainsNeuroImage, 2004
- Construction of an abdominal probabilistic atlas and its application in segmentationIEEE Transactions on Medical Imaging, 2003
- Fast approximate energy minimization via graph cutsIeee Transactions On Pattern Analysis and Machine Intelligence, 2001
- Nonrigid registration using free-form deformations: application to breast MR imagesIEEE Transactions on Medical Imaging, 1999
- Automated model-based bias field correction of MR images of the brainIEEE Transactions on Medical Imaging, 1999
- Measures of the Amount of Ecologic Association Between SpeciesEcology, 1945