3D/2D registration and segmentation of scoliotic vertebrae using statistical models
β Scribed by Said Benameur; Max Mignotte; Stefan Parent; Hubert Labelle; Wafa Skalli; Jacques de Guise
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 970 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0895-6111
No coin nor oath required. For personal study only.
β¦ Synopsis
We propose a new 3D/2D registration method for vertebrae of the scoliotic spine, using two conventional radiographic views (postero-anterior and lateral), and a priori global knowledge of the geometric structure of each vertebra. This geometric knowledge is efficiently captured by a statistical deformable template integrating a set of admissible deformations, expressed by the first modes of variation in Karhunen-Loeve expansion, of the pathological deformations observed on a representative scoliotic vertebra population. The proposed registration method consists of fitting the projections of this deformable template with the preliminary segmented contours of the corresponding vertebra on the two radiographic views. The 3D/2D registration problem is stated as the minimization of a cost function for each vertebra and solved with a gradient descent technique. Registration of the spine is then done vertebra by vertebra. The proposed method efficiently provides accurate 3D reconstruction of each scoliotic vertebra and, consequently, it also provides accurate knowledge of the 3D structure of the whole scoliotic spine. This registration method has been successfully tested on several biplanar radiographic images and validated on 57 scoliotic vertebrae. The validation results reported in this paper demonstrate that the proposed statistical scheme performs better than other conventional 3D reconstruction methods.
π SIMILAR VOLUMES
## Abstract An improved integration approach for segmented 3D shapes using projected digitalized 2D pattern is presented. The digital 2D patterns are fabricated based on lithography techniques. Geometrical accuracy better than 0.5 ΞΌm can be achieved. Contrast ratio of the fringe pattern can be prec
We propose a novel method for 3D image segmentation, where a Bayesian formulation, based on joint prior knowledge of the object shape and the image gray levels, along with information derived from the input image, is employed. Our method is motivated by the observation that the shape of an object an
## Abstract ## Purpose To analyze the 3D microarchitecture of rat lumbar vertebrae by microβmagnetic resonance imaging (ΞΌβMRI). ## Materials and Methods ΞΌβMR images (20 Γ 20 Γ 20 ΞΌm^3^ apparent voxel size) were acquired with a threeβdimensional spinβecho pulse sequence on four lumbar vertebrae o