Lumbar Spine Image Analysis Based on Vertebrae Segmentation in Spine MRI by Using Improved ICA-AAMs
基于脊椎MRI中改进型ICA-AAMs椎体分割的腰椎图像分析

An image analysis framework based on vertebrae segmentation in lumbar MRI is presented in this paper. As PCA lacks for describing data in detail, it is replaced by ICA in both shape and texture modeling with a further fast sorting of Independent Components. Improved ICA-AAMs is then built, with which vertebrae in MRI are segmented. Based on vertebra segmentation, the best fitting function of lumbar curve is obtained with the MDL principle; lumbar lordosis angles are then computed based on the curvature of this lumbar curve. At last, disc degeneration is evaluated from a declining intensity projecting profile between the endplates of vertebrae. Experiments have testified the accuracy and validity of the segmentation and quantitative analysis respectively. This framework reduces the clinical trifle in terms of providing impersonal quantitative information to doctors. It is also extensible to lumbar computer aided diagnosis (CAD).