Robust, accurate and fast automatic segmentation of the spinal cord

Leener, Benjamin De; Kadoury, Samuel; Cohen‐Adad, Julien

doi:10.1016/j.neuroimage.2014.04.051

Cited by 137 publications

(138 citation statements)

References 19 publications

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“…7,9,11,21,23,28 This proof-of-concept study demonstrates the prognostic validity of this approach and how segmented analysis of SC subregions (ie, %GM and %WM) may reflect the underlying pathophysiology of disease.…”

Section: Discussionmentioning

confidence: 68%

“…The tubular mesh is then deformed toward the edges of the SC. 21 Results of segmentation accuracy were unsatisfactory because of the large signal hyperintensity in this cluster of patients. Because of this, segmentation of normal tissue was done using the SCT segmentation algorithm.…”

Section: Image Processingmentioning

confidence: 91%

“…These locations flag the beginning and end regions for the propagation deformation model to segment the SC. 21 During automatic segmentation, detection of the SC is done in the axial plane by using the Hough transform. This is followed by propagation of an elliptical triangular tubular mesh built inside the SC.…”

Section: Image Processingmentioning

confidence: 99%

See 2 more Smart Citations

MRI Atlas-Based Measurement of Spinal Cord Injury Predicts Outcome in Acute Flaccid Myelitis

McCoy

Talbott

Wilson

et al. 2016

AJNR Am J Neuroradiol

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BACKGROUND AND PURPOSE:Recent advances in spinal cord imaging analysis have led to the development of a robust anatomic template and atlas incorporated into an open-source platform referred to as the Spinal Cord Toolbox. Using the Spinal Cord Toolbox, we sought to correlate measures of GM, WM, and cross-sectional area pathology on T2 MR imaging with motor disability in patients with acute flaccid myelitis.

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Section: Discussionmentioning

confidence: 68%

Section: Image Processingmentioning

confidence: 91%

See 1 more Smart Citation

MRI Atlas-Based Measurement of Spinal Cord Injury Predicts Outcome in Acute Flaccid Myelitis

McCoy

Talbott

Wilson

et al. 2016

AJNR Am J Neuroradiol

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“…The deformation is controlled manually by interactively varying the parameters of the model or automatically by minimizing an energy functional [6,9]. Deformable models have been applied successfully for image segmentation, tracking and face recognition [10,11,12]. In the medical field, they are used for 3D visualization for surgical planning or to detect morphological changes of a specific anatomic structure over time.…”

Section: Introductionmentioning

confidence: 99%

Local refinement for 3D deformable parametric surfaces

Badoual

Schmitter

Unser

2016

2016 IEEE International Conference on Image Processing (ICIP)

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Biomedical image segmentation is an active field of research where deformable models have proved to be efficient. The geometric representation of such models determines their ability to approximate the shape of interest as well as the speed of convergence of related optimization algorithms. We present a new tensor-product parameterization of surfaces that offers the possibility of local refinement. The goal is to allocate additional degrees of freedom to the surface only where an increase in local detail is required. We introduce the possibility of locally increasing the number of control points by inserting basis functions at specific locations. Our approach is generic and relies on refinable functions which satisfy the refinement relation. We show that the proposed method improves brain segmentation in 3D MRI images.

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“…This motivates the development of a deformable model with few degrees of freedom. Existing methods for the segmentation of vascular structures often rely on a large number of parameters, such as mesh- [2], tensor- [4] or tracking [4]-and path minimization [5]-based models.…”

Section: Introductionmentioning

confidence: 99%

New parametric 3D snake for medical segmentation of structures with cylindrical topology

Schmitter

Gaudet-Blavignac

Piccini

et al. 2015

2015 IEEE International Conference on Image Processing (ICIP)

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We propose a new parametric 3D snake with cylindrical topology. Its construction is based on interpolatory basis functions which facilitates user-interaction because the control points of the snake directly lie on the surface of the deformable cylinder. We prove that the basis functions exactly reproduce a cylinder and propose a new parametrization as a tensorproduct spline surface. We provide explicit formulas for the energy function based on Green's theorem that speed up the computation of the optimization algorithm. We have implemented the proposed framework as a freely available opensource plugin for the bioimaging platform Icy. Its utility has been tested on phantom data as well as on real 3D data to segment the spinal cord and the descending aorta.

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Robust, accurate and fast automatic segmentation of the spinal cord

Cited by 137 publications

References 19 publications

MRI Atlas-Based Measurement of Spinal Cord Injury Predicts Outcome in Acute Flaccid Myelitis

MRI Atlas-Based Measurement of Spinal Cord Injury Predicts Outcome in Acute Flaccid Myelitis

Local refinement for 3D deformable parametric surfaces

New parametric 3D snake for medical segmentation of structures with cylindrical topology

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