title: Automatic detection and segmentation of kidneys in 3D CT images using random forests.
abstract: Kidney segmentation in 3D CT images allows extracting useful information for nephrologists. For practical use in clinical routine, such an algorithm should be fast, automatic and robust to contrast-agent enhancement and fields of view. By combining and refining state-of-the-art techniques (random forests and template deformation), we demonstrate the possibility of building an algorithm that meets these requirements. Kidneys are localized with random forests following a coarse-to-fine strategy. Their initial positions detected with global contextual information are refined with a cascade of local regression forests. A classification forest is then used to obtain a probabilistic segmentation of both kidneys. The final segmentation is performed with an implicit template deformation algorithm driven by these kidney probability maps. Our method has been validated on a highly heterogeneous database of 233 CT scans from 89 patients. 80% of the kidneys were accurately detected and segmented (Dice coefficient > 0.90) in a few seconds per volume.
authors.affiliation: Philips Research Medisys, France.
authors.forename: Rémi
authors.initials: R
authors.lastname: Cuingnet
authors.forename: Raphael
authors.initials: R
authors.lastname: Prevost
authors.forename: David
authors.initials: D
authors.lastname: Lesage
authors.forename: Laurent D
authors.initials: LD
authors.lastname: Cohen
authors.forename: Benoît
authors.initials: B
authors.lastname: Mory
authors.forename: Roberto
authors.initials: R
authors.lastname: Ardon
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007674:Kidney Diseases / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*