His Artificial intelligence study frequently draws connections to other fields, such as Pattern recognition (psychology). His Pattern recognition (psychology) study frequently draws connections to other fields, such as Artificial intelligence. His study on Cardiology is mostly dedicated to connecting different topics, such as Ventricular tachycardia. Maxime Sermesant undertakes interdisciplinary study in the fields of Ventricular tachycardia and Catheter ablation through his works. He undertakes multidisciplinary investigations into Computer vision and Algorithm in his work. Maxime Sermesant integrates many fields in his works, including Algorithm and Computer vision. His research on Internal medicine frequently connects to adjacent areas such as Ablation. Ablation is frequently linked to Catheter ablation in his study. He combines topics linked to Image registration with his work on Image (mathematics).
His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Pattern recognition (psychology), Image (mathematics) and Segmentation. Image (mathematics) and Computer vision are frequently intertwined in his study. Maxime Sermesant undertakes multidisciplinary studies into Computer vision and Algorithm in his work. Maxime Sermesant undertakes multidisciplinary studies into Algorithm and Artificial intelligence in his work. His Cardiology study frequently links to related topics such as Ablation. His Ablation study often links to related topics such as Cardiology. His research is interdisciplinary, bridging the disciplines of Ventricular tachycardia and Internal medicine. His Ventricular tachycardia study frequently links to adjacent areas such as Internal medicine. His Electrophysiology study frequently links to related topics such as Cardiac electrophysiology.
Maxime Sermesant is involved in relevant fields of research such as Tensor (intrinsic definition) and Orientation (vector space) in the field of Geometry. Orientation (vector space) is closely attributed to Geometry in his study. His Ventricle research encompasses a variety of disciplines, including Interventricular septum and Ventricular outflow tract. Maxime Sermesant integrates Ventricular outflow tract with Ventricle in his study. Cardiology is closely attributed to Tachycardia in his research. As part of his studies on Artificial intelligence, he often connects relevant areas like Subspace topology. His Internal medicine study frequently links to other fields, such as Strain (injury). His Strain (injury) study frequently links to other fields, such as Internal medicine. His Computed tomography research extends to the thematically linked field of Radiology.
Interventricular septum and Ventricular outflow tract are fields of study that intersect with his Ventricle research. Maxime Sermesant performs multidisciplinary studies into Ventricular outflow tract and Ventricle in his work. Cardiology is closely attributed to Endocardium in his study. Internal medicine and Tachycardia are commonly linked in his work. The study of Tachycardia is intertwined with the study of Internal medicine in a number of ways. Radiology is frequently linked to Computed tomography in his study. Computed tomography is closely attributed to Radiology in his study. While working in this field, Maxime Sermesant studies both Artificial intelligence and Algorithm. Maxime Sermesant conducts interdisciplinary study in the fields of Algorithm and Artificial intelligence through his works.
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Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
Olivier Bernard;Alain Lalande;Clement Zotti;Frederick Cervenansky.
IEEE Transactions on Medical Imaging (2018)
Realistic simulation of the 3-D growth of brain tumors in MR images coupling diffusion with biomechanical deformation
O. Clatz;M. Sermesant;P.-Y. Bondiau;H. Delingette.
IEEE Transactions on Medical Imaging (2005)
An electromechanical model of the heart for image analysis and simulation
M. Sermesant;H. Delingette;N. Ayache.
IEEE Transactions on Medical Imaging (2006)
Patient-specific electromechanical models of the heart for the prediction of pacing acute effects in CRT: A preliminary clinical validation
Maxime Sermesant;Radomir Chabiniok;Phani Pradeep Chinchapatnam;T. Mansi.
Medical Image Analysis (2012)
Functional Imaging and Modeling of the Heart
Nicholas Ayache;Hervé Delingette;Maxime Sermesant.
Lecture Notes in Computer Science (2009)
A system for real-time XMR guided cardiovascular intervention
K.S. Rhode;M. Sermesant;D. Brogan;S. Hegde.
IEEE Transactions on Medical Imaging (2005)
SVF-Net: Learning Deformable Image Registration Using Shape Matching
Marc-Michel Rohé;Manasi Datar;Tobias Heimann;Maxime Sermesant.
medical image computing and computer assisted intervention (2017)
Inverse relationship between fractionated electrograms and atrial fibrosis in persistent atrial fibrillation: combined magnetic resonance imaging and high-density mapping.
Amir S. Jadidi;Hubert Cochet;Ashok J. Shah;Steven J. Kim.
Journal of the American College of Cardiology (2013)
iLogDemons: A Demons-Based Registration Algorithm for Tracking Incompressible Elastic Biological Tissues
Tommaso Mansi;Xavier Pennec;Maxime Sermesant;Hervé Delingette.
International Journal of Computer Vision (2011)
Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties.
Maxime Sermesant;Philippe Moireau;Oscar Camara;Jacques Sainte-Marie.
Medical Image Analysis (2006)
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