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Disambiguation of "Peressutti, Devis"

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A framework for automatic model-driven 2D echocardiography acquisition for robust respiratory motion estimation in image-guided cardiac interventions.

, , , , , , and . ISBI, page 29-32. IEEE, (2013)

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Devis Contarato

Anne Devismes

Stéphane Devismes

 

Other publications of authors with the same name

Prospective Identification of CRT Super Responders Using a Motion Atlas and Random Projection Ensemble Learning., , , , , , and . MICCAI (3), volume 9351 of Lecture Notes in Computer Science, page 493-500. Springer, (2015)A framework for combining a motion atlas with non-motion information to learn clinically useful biomarkers: Application to cardiac resynchronisation therapy response prediction., , , , , , , , , and 1 other author(s). Medical Image Anal., (2017)Learning a Global Descriptor of Cardiac Motion from a Large Cohort of 1000+ Normal Subjects., , , , , , and . FIMH, volume 9126 of Lecture Notes in Computer Science, page 3-11. Springer, (2015)An Evaluation of Atlas Selection Methods for Atlas-Based Automatic Segmentation in Radiotherapy Treatment Planning., , , , , , , and . IEEE Trans. Medical Imaging, 38 (11): 2654-2664 (2019)Personalising population-based respiratory motion models of the heart using neighbourhood approximation based on learnt anatomical features., , , and . Medical Image Anal., 18 (7): 1015-1025 (2014)Registration of Multiview Echocardiography Sequences Using a Subspace Error Metric., , , and . IEEE Trans. Biomed. Eng., 64 (2): 352-361 (2017)A novel Bayesian respiratory motion model to estimate and resolve uncertainty in image-guided cardiac interventions., , , , , , , , and . Medical Image Anal., 17 (4): 488-502 (2013)Estimating and resolving uncertainty in cardiac respiratory motion modelling., , , , and . ISBI, page 262-265. IEEE, (2012)Towards Left Ventricular Scar Localisation Using Local Motion Descriptors., , , , , , , , and . STACOM@MICCAI, volume 9534 of Lecture Notes in Computer Science, page 30-39. Springer, (2015)Can Atlas-Based Auto-Segmentation Ever Be Perfect? Insights From Extreme Value Theory., , , , , , , , and . IEEE Trans. Medical Imaging, 38 (1): 99-106 (2019)