Elastic Shape Analysis of Cylindrical Surfaces for 3D/2D Registration in Endometrial Tissue Characterization - Archive ouverte HAL
Article Dans Une Revue IEEE Transactions on Medical Imaging Année : 2014

Elastic Shape Analysis of Cylindrical Surfaces for 3D/2D Registration in Endometrial Tissue Characterization

Résumé

We study the problem of joint registration and deformation analysis of endometrial tissue using 3D MRI and 2D Trans-vaginal Ultrasound (TVUS) measurements. In addition to the different imaging techniques involved in the two modalities, this problem is complicated due to: (1) different patient pose during MRI and TVUS observations, (2) the 3D nature of MRI and 2D nature of TVUS measurements, (3) the unknown intersecting plane for TVUS in MRI volume, and (4) the potential deformation of endometrial tissue during TVUS measurement process. Focusing on the shape of the tissue, we use expert manual segmentation of its boundaries in the two modalities and apply, with modification, recent developments in shape analysis of parametric surfaces to this problem. First, we extend the 2D TVUS curves to generalized cylindrical surfaces through replication, and then we compare them with MRI surfaces using elastic shape analysis. This shape analysis provides a simultaneous registration (optimal re-parameterization) and deformation (geodesic) between any two parametrized surfaces. Specifically, it provides optimal curves on MRI surfaces that match with the original TVUS curves. This framework results in an accurate quantification and localization of the deformable endometrial cells for radiologists, and growth characterization for gynecologists and obstetricians. We present experimental results using semi-synthetic data and real data from patients to illustrate these ideas.
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Dates et versions

hal-01598208 , version 1 (16-10-2017)

Identifiants

Citer

Chafik Samir, Sebastian Kurtek, Anuj Srivastava, Michel Canis. Elastic Shape Analysis of Cylindrical Surfaces for 3D/2D Registration in Endometrial Tissue Characterization. IEEE Transactions on Medical Imaging, 2014, 33 (5), pp.1035 - 1043. ⟨10.1109/TMI.2014.2300935⟩. ⟨hal-01598208⟩
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