title: Localization of the lumbar discs using machine learning and exact probabilistic inference.
abstract: We propose a novel fully automatic approach to localize the lumbar intervertebral discs in MR images with PHOG based SVM and a probabilistic graphical model. At the local level, our method assigns a score to each pixel in target image that indicates whether it is a disc center or not. At the global level, we define a chain-like graphical model that represents the lumbar intervertebral discs and we use an exact inference algorithm to localize the discs. Our main contributions are the employment of the SVM with the PHOG based descriptor which is robust against variations of the discs and a graphical model that reflects the linear nature of the vertebral column. Our inference algorithm runs in polynomial time and produces globally optimal results. The developed system is validated on a real spine MRI dataset and the final localization results are favorable compared to the results reported in the literature.
authors: GIT Vision Lab, Department of Computer Engineering, Gebze Institute of Technology, Kocaeli, 41400, Turkey. oktay@bilmuh.gyte.edu.tr
authors: Ayse Betul
authors: AB
authors: Oktay
authors: Yusuf Sinan
authors: YS
authors: Akgul
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007403:Intervertebral Disc / Q000473:pathology*; D008159:Lumbar Vertebrae / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods; D015233:Models, Statistical; D011336:Probability