A hierarchical 3D segmentation method and the definition of vertebral body coordinate systems for QCT of the lumbar spine

Mastmeyer, André; Engelke, Klaus; Fuchs, Christina; Kalender, Willi A.

doi:10.1016/j.media.2006.05.005

Cited by 154 publications

(111 citation statements)

References 34 publications

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“…8,9 Most of the methods have shown success in certain anatomical structures where they have been optimized, such as carpal bones, 9 acetabulum and femoral head, 10 spinal canal, 11 pelvis, 7,12 vertebrae, 13 ribs, 14 and phalanx bones. 15 In, 8 two methods were validated on knee bone segmentation, which is also the subject of this study.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Feasibility of Active Contours on Automatic CT Bone Segmentation

et al. 2009

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Automatic bone segmentation of computed tomography (CT) images is an important step in image-guided surgery that requires both high accuracy and minimal user interaction. Previous attempts include global thresholding, region growing, region competition, watershed segmentation, and parametric active contour (AC) approaches, but none claim fully satisfactory performance. Recently, geometric or level-set-based AC models have been developed and appear to have characteristics suitable for automatic bone segmentation such as initialization insensitivity and topology adaptability. In this study, we have tested the feasibility of five level-set-based AC approaches for automatic CT bone segmentation with both synthetic and real CT images: namely, the geometric AC, geodesic AC, gradient vector flow fast geometric AC, Chan-Vese (CV) AC, and our proposed density distance augmented CV AC (Aug. CV AC). Qualitative and quantitative evaluations have been made in comparison with the segmentation results from standard commercial software and a medical expert. The first three models showed their robustness to various image contrasts, but their performances decreased much when noise level increased. On the contrary, the CV AC's performance was more robust to noise, yet dependent on image contrast. On the other hand, the Aug. CV AC demonstrated its robustness to both noise and contrast levels and yielded improved performances on a set of real CT data compared with the commercial software, proving its suitability for automatic bone segmentation from CT images.

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Section: Introductionmentioning

confidence: 99%

A Study on the Feasibility of Active Contours on Automatic CT Bone Segmentation

et al. 2009

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“…These NURBS models can then be used as templates for CAD model generation. Customized models can be obtained by modifying these templates according to dimensional specifications taken from individual patients (Mastmeyer et al, 2006). Once the geometric models of vertebrae have been prepared, FE models can be constructed according to these geometric models.…”

Section: Geometric Modeling Of Vertebraementioning

confidence: 99%

Development of a Detailed Human Spine Model with Haptic Interface

Huynh¹,

Gibson²,

Gao³

2012

Haptics Rendering and Applications

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“…There exists a wide range of approaches in the existing literature for spine and vertebral segmentation [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20]. Table I lists the main papers and reported segmentation results on spine segmentation in the literature.…”

Section: Introductionmentioning

confidence: 99%

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

Pereañez

Lekadir

Castro-Mateos

et al. 2015

IEEE Trans. Med. Imaging

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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.

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A hierarchical 3D segmentation method and the definition of vertebral body coordinate systems for QCT of the lumbar spine

Cited by 154 publications

References 34 publications

A Study on the Feasibility of Active Contours on Automatic CT Bone Segmentation

A Study on the Feasibility of Active Contours on Automatic CT Bone Segmentation

Development of a Detailed Human Spine Model with Haptic Interface

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

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