Localization of the Lumbar discs using machine learning and exact probabilistic inference

Authors:
Ayse Betul Oktay;Yusuf Sinan Akgul
Affiliations:
GIT Vision Lab, Department of Computer Engineering, Gebze Institute of Technology, Kocaeli, Turkey;GIT Vision Lab, Department of Computer Engineering, Gebze Institute of Technology, Kocaeli, Turkey
Venue:
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
Year:
2011

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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.