Model-based Postoperative Modeling of Stent-Based Devices from CT: Application to TAVI - Voigt, Ingmar; Assoumou Mengue, Etienne; Ionasec, Razvan; Tommaso, Mansi; Bernhardt, Dominik; Georgescu, Bogdan; Hornegger, Joachim; Comaniciu, Dorin (1st International MICCAI-Workshop on Computer Assisted Stenting, 2012)

Patient-Specific Model of Left Heart Anatomy, Dynamics and Hemodynamics from 4D TEE: A First Validation Study - Voigt, Ingmar; Mansi, Tommaso; Mihalef, Viorel; Ionasec, Razvan; Calleja, Anna; Assoumou Mengue, Etienne; Sharma, Puneet; Houle, Helene; Georgescu, Bogdan; Hornegger, Joachim; Comaniciu, Dorin (Springer-verlag, 2011)
Patient-specific models of the heart physiology have become powerful instruments able to improve the diagnosis and treatment of cardiac disease. A systemic representation of the whole organ is required to capture the complex functional and hemodynamical interdependencies among the anatomical structures. We propose a novel framework for personalized modeling of the left-side heart that integrates comprehensive data of the morphology, function and hemodynamics. Patient-specific fluid dynamics are computed over the entire cardiac cycle using embedded boundary and ghost fluid methods, constrained by the dynamics of highly detailed anatomical models. Personalized boundary conditions are determined by estimating cardiac shape and motion from 4D TEE images through robust discriminative learning methods. Qualitative and quantitative validation of the computed blood dynamics is performed against Doppler echocardiography measurements, following an original methodology. Results showed a high agreement between simulation and ground truth and a correlation of r = 0.85 (p < 0.0002675). To the best of our knowledge, this is the first time that computational fluid dynamics are simulated on a systemic and comprehensive patient-specific model of the heart and validated against routinely acquired clinical ground truth. © 2011 Springer-Verlag Berlin Heidelberg.
UnivIS-Import:2015-04-16:Pub.2011.tech.IMMD.IMMD5.patien

Robust Physically-Constrained Modeling of the Mitral Valve and Subvalvular Apparatus - Voigt, Ingmar; Mansi, Tommaso; Ionasec, Razvan Ioan; Assoumou Mengue, Etienne; Houle, Helene; Georgescu, Bogdan; Hornegger, Joachim; Comaniciu, Dorin (Proceedings of the 14th International Conference on Medical Image Computing and Computer Assisted Intervention, 2011)
Mitral valve (MV) is often involved in cardiac diseases, with various pathological patterns that require a systemic view of the entire MV apparatus. Due to its complex shape and dynamics, patient-specific modeling of the MV constitutes a particular challenge. We propose a novel approach for personalized modeling of the dynamic MV and its subvalvular apparatus that ensures temporal consistency over the cardiac sequence and provides realistic deformations. The idea is to detect the anatomical MV components under constraints derived from the biomechanical properties of the leaflets. This is achieved by a robust two-step alternate algorithm that combines discriminative learning and leaflet biomechanics. Extensive evaluation on 200 transesophageal echochardiographic sequences showed an average Hausdorff error of 5.1 mm at a speed of 9 sec, which constitutes an improvement of up to 11.5% compared to purely data driven approaches. Clinical evaluation on 42 subjects showed, that the proposed fully-automatic approach could provide discriminant biomarkers to detect and quantify remodeling of annulus and leaflets in functional mitral regurgitation.
UnivIS-Import:2015-04-16:Pub.2011.tech.IMMD.IMMD5.robust_1

Robust physically-constrained modeling of the mitral valve and subvalvular apparatus - Voigt, Ingmar; Tommaso, Mansi; Ionasec, Razvan; Assoumou Mengue, Etienne; Houle, Helene; Georgescu, Bogdan; Hornegger, Joachim; Comaniciu, Dorin (Springer-verlag, 2011)
Mitral valve (MV) is often involved in cardiac diseases, with various pathological patterns that require a systemic view of the entire MV apparatus. Due to its complex shape and dynamics, patient-specific modeling of the MV constitutes a particular challenge. We propose a novel approach for personalized modeling of the dynamic MV and its subvalvular apparatus that ensures temporal consistency over the cardiac sequence and provides realistic deformations. The idea is to detect the anatomical MV components under constraints derived from the biomechanical properties of the leaflets. This is achieved by a robust two-step alternate algorithm that combines discriminative learning and leaflet biomechanics. Extensive evaluation on 200 transesophageal echochardiographic sequences showed an average Hausdorff error of 5.1mm at a speed of 9sec, which constitutes an improvement of up to 11.5% compared to purely data driven approaches. Clinical evaluation on 42 subjects showed, that the proposed fully-automatic approach could provide discriminant biomarkers to detect and quantify remodeling of annulus and leaflets in functional mitral regurgitation. © 2011 Springer-Verlag.

ROCHADE: Robust Checkerboard Advanced Detection for Camera Calibration - Placht, Simon; Fürsattel, Peter; Assoumou Mengue, Etienne; Hofmann, Hannes; Schaller, Christian; Balda, Michael; Angelopoulou, Elli (Lecture Notes in Computer Science, 2014)
We present a new checkerboard detection algorithm which is able to detect checkerboards at extreme poses, or checkerboards which are highly distorted due to lens distortion even on low-resolution images. On the detected pattern we apply a surface fitting based subpixel refinement specifically tailored for checkerboard X-junctions. Finally, we investigate how the accuracy of a checkerboard detector affects the overall calibration result in multi-camera setups. The proposed method is evaluated on real images captured with different camera models to show its wide applicability. Quantitative comparisons to OpenCV's checkerboard detector show that the proposed method detects up to 80% more checkerboards and detects corner points more accurately, even under strong perspective distortion as often present in wide baseline stereo setups. © 2014 Springer International Publishing.
UnivIS-Import:2015-04-16:Pub.2014.tech.IMMD.IMMD5.rochad
Keywords: Checkerboard Detection; Lens Distortion; Low Resolution Sensors; Multi Camera Calibration; Saddle-Based Subpixel Refinement