G
Georgios Tziritas
Researcher at University of Crete
Publications - 90
Citations - 5986
Georgios Tziritas is an academic researcher from University of Crete. The author has contributed to research in topics: Image segmentation & Motion estimation. The author has an hindex of 30, co-authored 89 publications receiving 5235 citations. Previous affiliations of Georgios Tziritas include Centre national de la recherche scientifique & École Normale Supérieure.
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Journal ArticleDOI
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
Olivier Bernard,Alain Lalande,Clement Zotti,Frederick Cervenansky,Xin Yang,Pheng-Ann Heng,Irem Cetin,Karim Lekadir,Oscar Camara,Miguel Ángel González Ballester,Gerard Sanroma,Sandy Napel,Steffen E. Petersen,Georgios Tziritas,Elias Grinias,Mahendra Khened,Varghese Alex Kollerathu,Ganapathy Krishnamurthi,Marc-Michel Rohé,Xavier Pennec,Maxime Sermesant,Fabian Isensee,Paul F. Jäger,Klaus H. Maier-Hein,Peter M. Full,Ivo Wolf,Sandy Engelhardt,Christian F. Baumgartner,Lisa M. Koch,Jelmer M. Wolterink,Ivana Išgum,Yeonggul Jang,Yoonmi Hong,Jay Patravali,Shubham Jain,Olivier Humbert,Pierre-Marc Jodoin +36 more
TL;DR: How far state-of-the-art deep learning methods can go at assessing CMRI, i.e., segmenting the myocardium and the two ventricles as well as classifying pathologies is measured, to open the door to highly accurate and fully automatic analysis of cardiac CMRI.
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Face detection using quantized skin color regions merging and wavelet packet analysis
TL;DR: An efficient and reliable probabilistic metric derived from the Bhattacharrya distance is used in order to classify the extracted feature vectors into face or nonface areas, using some prototype face area vectors, acquired in a previous training stage.
Journal ArticleDOI
Dense image registration through MRFs and efficient linear programming.
Ben Glocker,Nikos Komodakis,Nikos Komodakis,Georgios Tziritas,Nassir Navab,Nikos Paragios,Nikos Paragios +6 more
TL;DR: A novel and efficient approach to dense image registration, which does not require a derivative of the employed cost function is introduced, and efficient linear programming using the primal dual principles is considered to recover the lowest potential of the cost function.
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Image Completion Using Efficient Belief Propagation Via Priority Scheduling and Dynamic Pruning
TL;DR: A new exemplar-based framework is presented, which treats image completion, texture synthesis, and image inpainting in a unified manner, and manages to resolve what is currently considered as one major limitation of the BP algorithm: its inefficiency in handling MRFs with very large discrete state spaces.
Journal ArticleDOI
MRF Energy Minimization and Beyond via Dual Decomposition
TL;DR: It is shown that by appropriately choosing what subproblems to use, one can design novel and very powerful MRF optimization algorithms, which are able to derive algorithms that generalize and extend state-of-the-art message-passing methods, and take full advantage of the special structure that may exist in particular MRFs.