Accurate Segmentation of Vertebral Bodies and Processes Using Statistical Shape Decomposition and Conditional Models

Abstract

Abstract-Detailed segmentation of the vertebrae is an important pre-requisite in various applications of image-based spine assessment, surgery and biomechanical modeling. In particular, accurate segmentation of the processes is required for imageguided interventions, for example for optimal placement of bone grafts between the transverse processes. Furthermore, the geometry of the processes is now required in musculoskeletal models due to their interaction with the muscles and ligaments. In this paper, we present a new method for detailed segmentation of both the vertebral bodies and processes based on statistical shape decomposition and conditional models. The proposed technique is specifically developed with the aim to handle the complex geometry of the processes and the large variability between individuals. The key technical novelty in this work is the introduction of a part-based statistical decomposition of the vertebrae, such that the complexity of the subparts is effectively reduced, and model specificity is increased. Subsequently, in order to maintain the statistical and anatomic coherence of the ensemble, conditional models are used to model the statistical inter-relationships between the different subparts. For shape reconstruction and segmentation, a robust model fitting procedure is used to exclude improbable inter-part relationships in the estimation of the shape parameters. Segmentation results based on a dataset of 30 healthy CT scans and a dataset of 10 pathological scans show a point-to-surface error improvement of 20% and 17% respectively, and the potential of the proposed technique for detailed vertebral modeling.

Automatic segmentation of the spine by means of a probabilistic atlas with a special focus on ribs suppression

“…The results reported by Korez et al and Castro‐Mateos et al were more accurate in the thoracic region but, to evaluate this region, they only included healthy patients. In addition, the development of completely automatic algorithms is still an open problem, being necessary in many cases some degree of user interaction . This has been accomplished with the current method, which is fully automatic.…”

“…However, most of the problems leading to back pain are related to lumbar region, as this area supports the greatest load of the spine. This is the reason why the majority of studies have only been focused on this region . Despite that, several studies found in the literature have made a great effort to segment all thoracic and lumbar vertebrae, but in most of the cases, the results obtained were more successful in segmenting the lumbar region.…”

“…The development of methods using prior knowledge of the shape to be segmented is an active field of research. 9 Therefore, most of the developed methods are based on deformable models, [10][11][12][13][14][15][16][17][18][19][20] which make use of this information. However, the availability of this kind of data is not always possible, therefore, other methods that do not require any form of prior knowledge are used, too.…”

Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images

“…3). To overcome these limitations, some researchers imposed statistical shape constraints on nonrigid registration [16, 25]. But it is difficult to implement them in practice due to pre-segmentation prerequisite and high complexity.

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Automatic segmentation of vertebral contours from CT images using fuzzy corners

“…The use of atlas for aiding segmentation is an alternate method [14][15][16]. A three step algorithm is developed in [17] adopting Statistical Shape Models (SSM), that includes a seed placement, initial labeling and final optimization. This method is designed to handle complex geometry of all processes and variability between the individuals.…”