A FEM-based deformable model for the 3D segmentation and tracking of the heart in cardiac MRI

Pham, Quoc-Cuong; Vincent, Fabrice; Clarysse, Patrick; Croisille, Pierre; Magnin, Isabelle E.

doi:10.1109/ispa.2001.938636

Cited by 38 publications

(44 citation statements)

References 15 publications

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“…The Deformable Elastic Template (DET) method introduced in [9] and later improved in [12], applied to a nonlinear model, makes use of a combination of the following items :…”

Section: Singular Perturbation Of the Elastic Modelmentioning

confidence: 99%

Singular Perturbations For Heart Image Segmentation Tracking

Pousin

2009

Math. Model. Nat. Phenom.

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“…The Deformable Elastic Template (DET) method introduced in [9] and later improved in [12], applied to a nonlinear model, makes use of a combination of the following items :…”

Section: Singular Perturbation Of the Elastic Modelmentioning

confidence: 99%

Singular Perturbations For Heart Image Segmentation Tracking

Pousin

2009

Math. Model. Nat. Phenom.

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“…This approach is commonly known in image processing as deformable models. The proposed model presents the advantage of allowing the simultaneous extraction of both the endocardial and epicardial surfaces [1,3]. The concept, named Deformable Elastic Template, is a combination of :…”

Section: Segmentation Using the Deformable Elastic Templatementioning

confidence: 99%

“…Our method is based on the Deformable Elastic Template method introduced by Pham [1], and later improved by Rouchdy [2]. This method was originally developed for the analysis of human cardiac sequences.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous segmentation of the left and right heart ventricles in 3D cine MR images of small animals

Schaerer

Rouchdy²,

Clarysse³

et al. 2005

Computers in Cardiology, 2005

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New high resolution image techniques allow to capture the anatomy and movement of the heart of small animals. The availability of these in vivo images can be very useful for medical research, however the amount of generated data for large animal studies makes manual analysis a very tedious task. To cope with the problem of automatic analysis of these images, we propose the use of the Deformable Elastic Template method to perform automatic segmentation of the ventricles. To adapt the method to the specificities of high-resolution MRI, several improvements are presented, including an image-context dependent scheme for more robust segmentation. Qualitative results show that our method is able to correctly retrieve the heart's contours in 3D.

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“…For diagnostic purposes, clinicians need image postprocessing techniques in order to obtain quantitative functional parameters, currently cavity volumes, ejection fraction or local motion indexes such as myocardial wall thickening. Therefore, several methods have been developed to estimate the heart shape and motion [1][2][3]. However, the performance comparison of theses methods is very difficult to achieve as usually in medical image analysis no ground truth exists.…”

Section: Introductionmentioning

confidence: 99%