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Frederik Maes
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- affiliation: University Hospitals Leuven, Medical Imaging Research Center
- affiliation: KU Leuven, Department of Electrical Engineering
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2020 – today
- 2023
- [j44]Pooya Ashtari, Diana Maria Sima, Lieven De Lathauwer, Dominique Sappey-Marinier, Frederik Maes, Sabine Van Huffel:
Factorizer: A scalable interpretable approach to context modeling for medical image segmentation. Medical Image Anal. 84: 102706 (2023) - [c94]Lotte Huysmans, Bram De Wel, Louise Iterbeke, Kristl G. Claeys, Frederik Maes:
Deep Learning Approaches for Automated Classification of Muscular Dystrophies from MRI. MICAD 2023: 273-281 - [c93]Konstantinos Koukoutegos, Frederik Maes, Hilde Bosmans:
Cascade UNets for Kidney and Kidney Tumor Segmentation. KiTS@MICCAI 2023: 107-113 - 2022
- [j43]Berardino Barile, Pooya Ashtari, Claudio Stamile, Aldo Marzullo, Frederik Maes, Françoise Durand-Dubief, Sabine Van Huffel, Dominique Sappey-Marinier:
Classification of multiple sclerosis clinical profiles using machine learning and grey matter connectome. Frontiers Robotics AI 9 (2022) - [j42]Adriaan Lambrechts, Roel Wirix-Speetjens, Frederik Maes, Sabine Van Huffel:
Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty. Frontiers Robotics AI 9: 840282 (2022) - [j41]Adriaan Lambrechts, Roel Wirix-Speetjens, Frederik Maes, Sabine Van Huffel:
Corrigendum: Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty. Frontiers Robotics AI 9: 899349 (2022) - [j40]Sofie Tilborghs, Jan Bogaert, Frederik Maes:
Shape constrained CNN for segmentation guided prediction of myocardial shape and pose parameters in cardiac MRI. Medical Image Anal. 81: 102533 (2022) - [j39]Masoomeh Rahimpour, Jeroen Bertels, Ahmed Radwan, Henri Vandermeulen, Stefan Sunaert, Dirk Vandermeulen, Frederik Maes, Karolien Goffin, Michel Koole:
Cross-Modal Distillation to Improve MRI-Based Brain Tumor Segmentation With Missing MRI Sequences. IEEE Trans. Biomed. Eng. 69(7): 2153-2164 (2022) - [c92]Berardino Barile, Pooya Ashtari, Françoise Durand-Dubief, Frederik Maes, Dominique Sappey-Marinier, Sabine Van Huffel:
A Kernel Based Multilinear SVD Approach for Multiple Sclerosis Profiles Classification. ESANN 2022 - [c91]Sofie Tilborghs, Jeroen Bertels, David Robben, Dirk Vandermeulen, Frederik Maes:
The Dice Loss in the Context of Missing or Empty Labels: Introducing $\varPhi $ and ε. MICCAI (5) 2022: 527-537 - [i9]Pooya Ashtari, Diana Maria Sima, Lieven De Lathauwer, Dominique Sappey-Marinier, Frederik Maes, Sabine Van Huffel:
Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image Segmentation. CoRR abs/2202.12295 (2022) - [i8]Sofie Tilborghs, Jan Bogaert, Frederik Maes:
Shape constrained CNN for segmentation guided prediction of myocardial shape and pose parameters in cardiac MRI. CoRR abs/2203.01089 (2022) - [i7]Sofie Tilborghs, Jeroen Bertels, David Robben, Dirk Vandermeulen, Frederik Maes:
The Dice loss in the context of missing or empty labels: Introducing Φ and ε. CoRR abs/2207.09521 (2022) - 2021
- [c90]Siri Willems, Heleen Bollen, Julie Van Der Veen, Edmond Sterpin, Wouter Crijns, Sandra Nuyts, Frederik Maes:
Learning from Mistakes: An Error-Driven Mechanism to Improve Segmentation Performance Based on Expert Feedback. CLIP/DCL/LL-COVID19/PPML@MICCAI 2021: 68-77 - [c89]Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Matthew B. Blaschko:
On the Relationship Between Calibrated Predictors and Unbiased Volume Estimation. MICCAI (1) 2021: 678-688 - [c88]Masoomeh Rahimpour, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Karolien Goffin, Michel Koole:
Improving T1w MRI-based brain tumor segmentation using cross-modal distillation. Image Processing 2021 - [p1]Tom Eelbode, Pieter Sinonquel, Raf Bisschops, Frederik Maes:
Convolutional LSTM. Computer-Aided Analysis of Gastrointestinal Videos 2021: 121-126 - [i6]Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Matthew B. Blaschko:
On the relationship between calibrated predictors and unbiased volume estimation. CoRR abs/2112.12560 (2021) - 2020
- [j38]Liesbeth Vandewinckele, Siri Willems, David Robben, Julie Van Der Veen, Wouter Crijns, Sandra Nuyts, Frederik Maes:
Segmentation of head-and-neck organs-at-risk in longitudinal CT scans combining deformable registrations and convolutional neural networks. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 8(5): 519-528 (2020) - [j37]Tom Eelbode, Jeroen Bertels, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko:
Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index. IEEE Trans. Medical Imaging 39(11): 3679-3690 (2020) - [c87]Pooya Ashtari, Frederik Maes, Sabine Van Huffel:
Low-Rank Convolutional Networks for Brain Tumor Segmentation. BrainLes@MICCAI (1) 2020: 470-480 - [c86]Sofie Tilborghs, Tom Dresselaers, Piet Claus, Jan Bogaert, Frederik Maes:
Shape Constrained CNN for Cardiac MR Segmentation with Simultaneous Prediction of Shape and Pose Parameters. M&Ms and EMIDEC/STACOM@MICCAI 2020: 127-136 - [i5]Sofie Tilborghs, Ine Dirks, Lucas Fidon, Siri Willems, Tom Eelbode, Jeroen Bertels, Bart Ilsen, Arne Brys, Adriana Dubbeldam, Nico Buls, Panagiotis Gonidakis, Sebastián Amador Sánchez, Annemiek Snoeckx, Paul M. Parizel, Johan de Mey, Dirk Vandermeulen, Tom Vercauteren, David Robben, Dirk Smeets, Frederik Maes, Jef Vandemeulebroucke, Paul Suetens:
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients. CoRR abs/2007.15546 (2020) - [i4]Sofie Tilborghs, Tom Dresselaers, Piet Claus, Jan Bogaert, Frederik Maes:
Shape Constrained CNN for Cardiac MR Segmentation with Simultaneous Prediction of Shape and Pose Parameters. CoRR abs/2010.08952 (2020) - [i3]Tom Eelbode, Jeroen Bertels, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko:
Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index. CoRR abs/2010.13499 (2020) - [i2]Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky, Maryna Kvasnytsia, Ine Dirks, Mitchel Alioscha-Pérez, Nikos Deligiannis, Panagiotis Gonidakis, Sebastián Amador Sánchez, Redona Brahimetaj, Evgenia Papavasileiou, Jonathan Cheung-Wai Chan, Fei Li, Shangzhen Song, Yixin Yang, Sofie Tilborghs, Siri Willems, Tom Eelbode, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Paul Suetens, Lucas Fidon, Tom Vercauteren, David Robben, Arne Brys, Dirk Smeets, Bart Ilsen, Nico Buls, Nina Watté, Johan de Mey, Annemiek Snoeckx, Paul M. Parizel, Julien Guiot, Louis Deprez, Paul Meunier, Stefaan Gryspeerdt, Kristof De Smet, Bart Jansen, Jef Vandemeulebroucke:
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging. CoRR abs/2011.11719 (2020)
2010 – 2019
- 2019
- [j36]Sofie Tilborghs, Tom Dresselaers, Piet Claus, Guido Claessen, Jan Bogaert, Frederik Maes, Paul Suetens:
Robust motion correction for cardiac T1 and ECV mapping using a T1 relaxation model approach. Medical Image Anal. 52: 212-227 (2019) - [c85]Siri Willems, Wouter Crijns, Edmond Sterpin, Karin Haustermans, Frederik Maes:
Feasibility of CT-Only 3D Dose Prediction for VMAT Prostate Plans Using Deep Learning. AIRT@MICCAI 2019: 10-17 - [c84]Sofie Tilborghs, Tom Dresselaers, Piet Claus, Jan Bogaert, Frederik Maes:
3D Left Ventricular Segmentation from 2D Cardiac MR Images Using Spatial Context. STACOM@MICCAI 2019: 90-99 - [c83]Jeroen Bertels, Tom Eelbode, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko:
Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice. MICCAI (2) 2019: 92-100 - [c82]Sofie Tilborghs, Frederik Maes:
Left Ventricular Parameter Regression from Deep Feature Maps of a Jointly Trained Segmentation CNN. STACOM@MICCAI 2019: 395-404 - [i1]Jeroen Bertels, Tom Eelbode, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko:
Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice. CoRR abs/1911.01685 (2019) - 2018
- [j35]Philip Joris, Wim De Maerteleire, Wim Van De Voorde, Paul Suetens, Frederik Maes, Dirk Vandermeulen, Peter Claes:
Preprocessing of Heteroscedastic Medical Images. IEEE Access 6: 26047-26058 (2018) - [c81]Liesbeth Vandewinckele, David Robben, Wouter Crijns, Frederik Maes:
Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks. DLMIA/ML-CDS@MICCAI 2018: 146-154 - [c80]Siri Willems, Wouter Crijns, Agustina La Greca Saint-Esteven, Julie Van Der Veen, David Robben, Tom Depuydt, Sandra Nuyts, Karin Haustermans, Frederik Maes:
Clinical Implementation of DeepVoxNet for Auto-Delineation of Organs at Risk in Head and Neck Cancer Patients in Radiotherapy. OR 2.0/CARE/CLIP/ISIC@MICCAI 2018: 223-232 - 2017
- [j34]Nicolas Sauwen, Marjan Acou, Diana Maria Sima, Jelle Veraart, Frederik Maes, Uwe Himmelreich, Eric Achten, Sabine Van Huffel:
Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization. BMC Medical Imaging 17(1): 29:1-29:14 (2017) - [j33]Daan Christiaens, Stefan Sunaert, Paul Suetens, Frederik Maes:
Convexity-constrained and nonnegativity-constrained spherical factorization in diffusion-weighted imaging. NeuroImage 146: 507-517 (2017) - [j32]Claudio Stamile, Gabriel Kocevar, François Cotton, Frederik Maes, Dominique Sappey-Marinier, Sabine Van Huffel:
Multiparametric Non-Negative Matrix Factorization for Longitudinal Variations Detection in White-Matter Fiber Bundles. IEEE J. Biomed. Health Informatics 21(5): 1393-1402 (2017) - [c79]Adrian Ion-Margineanu, Sofie Van Cauter, Diana Maria Sima, Frederik Maes, Stefan Sunaert, Uwe Himmelreich, Sabine Van Huffel:
Comparison of manual and semi-manual delineations for classifying glioblastoma multiforme patients based on histogram and texture MRI features. ESANN 2017 - [c78]Sofie Tilborghs, Tom Dresselaers, Piet Claus, Guido Claessen, Jan Bogaert, Frederik Maes, Paul Suetens:
Robust Model-Based Registration of Cardiac MR Images for T1 and ECV Mapping. FIMH 2017: 42-50 - 2016
- [j31]David Robben, Engin Türetken, Stefan Sunaert, Vincent Thijs, Guy Willems, Pascal Fua, Frederik Maes, Paul Suetens:
Simultaneous segmentation and anatomical labeling of the cerebral vasculature. Medical Image Anal. 32: 201-215 (2016) - [c77]Nicolas Sauwen, Marjan Acou, Halandur Nagaraja Bharath, Diana Maria Sima, Jelle Veraart, Frederik Maes, Uwe Himmelreich, Eric Achten, Sabine Van Huffel:
Initializing nonnegative matrix factorization using the successive projection algorithm for multi-parametric medical image segmentation. ESANN 2016 - [c76]Claudio Stamile, François Cotton, Frederik Maes, Dominique Sappey-Marinier, Sabine Van Huffel:
White Matter Fiber-Bundle Analysis Using Non-negative Tensor Factorization. ICIAR 2016: 650-657 - [c75]Niels Verheyen, David Robben, Daniel Ruijters, Vitor Mendes Pereira, Olivier Brina, Frederik Maes, Paul Suetens:
Inferring brain deformation during open neurosurgery using CBCT angiography. ISBI 2016: 111-114 - [c74]Tom Haeck, Frederik Maes, Paul Suetens:
An untrained and unsupervised method for MRI brain tumor segmentation. ISBI 2016: 265-268 - [c73]Saurabh Jain, Diana Maria Sima, Faezeh Sanaei Nezhad, Steve Williams, Sabine Van Huffel, Frederik Maes, Dirk Smeets:
Patch based super-resolution of MR spectroscopic images. ISBI 2016: 452-456 - [c72]An Elen, Sofie Isebaert, Frederik De Keyzer, Uwe Himmelreich, Steven Joniau, Lorenzo Tosco, Wouter Everaerts, Tom Dresselaers, Evelyne Lerut, Raymond Oyen, Roger Bourne, Frederik Maes, Karin Haustermans:
Validation of an Improved Patient-Specific Mold Design for Registration of In-vivo MRI and Histology of the Prostate. CLIP@MICCAI 2016: 36-43 - [c71]Saurabh Jain, Annemie Ribbens, Diana Maria Sima, Sabine Van Huffel, Frederik Maes, Dirk Smeets:
Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation. MCV/BAMBI@MICCAI 2016: 208-219 - [c70]Nicolas Sauwen, Diana Maria Sima, Marjan Acou, Eric Achten, Frederik Maes, Uwe Himmelreich, Sabine Van Huffel:
A Semi-Automated Segmentation Framework for MRI Based Brain Tumor Segmentation Using Regularized Nonnegative Matrix Factorization. SITIS 2016: 88-95 - 2015
- [j30]Daan Christiaens, Marco Reisert, Thijs Dhollander, Stefan Sunaert, Paul Suetens, Frederik Maes:
Global tractography of multi-shell diffusion-weighted imaging data using a multi-tissue model. NeuroImage 123: 89-101 (2015) - [c69]Daan Christiaens, Frederik Maes, Stefan Sunaert, Paul Suetens:
Convex Non-negative Spherical Factorization of Multi-Shell Diffusion-Weighted Images. MICCAI (1) 2015: 166-173 - [c68]Tom Haeck, Frederik Maes, Paul Suetens:
ISLES Challenge 2015: Automated Model-Based Segmentation of Ischemic Stroke in MR Images. Brainles@MICCAI 2015: 246-253 - [c67]David Robben, Daan Christiaens, Janaki Raman Rangarajan, Jaap Gelderblom, Philip Joris, Frederik Maes, Paul Suetens:
A Voxel-Wise, Cascaded Classification Approach to Ischemic Stroke Lesion Segmentation. Brainles@MICCAI 2015: 254-265 - [c66]David Robben, Stefan Sunaert, Vincent Thijs, Guy Willms, Frederik Maes, Paul Suetens:
Perfusion Paths: Inference of Voxelwise Blood Flow Trajectories in CT Perfusion. MICCAI (2) 2015: 407-414 - 2014
- [j29]Caroline Guglielmetti, Jelle Praet, Janaki Raman Rangarajan, Ruth Vreys, Nathalie De Vocht, Frederik Maes, Marleen Verhoye, Peter Ponsaerts, Annemie van der Linden:
Multimodal imaging of subventricular zone neural stem/progenitor cells in the cuprizone mouse model reveals increased neurogenic potential for the olfactory bulb pathway, but no contribution to remyelination of the corpus callosum. NeuroImage 86: 99-110 (2014) - [j28]Thijs Dhollander, Louise Emsell, Wim Van Hecke, Frederik Maes, Stefan Sunaert, Paul Suetens:
Track Orientation Density Imaging (TODI) and Track Orientation Distribution (TOD) based tractography. NeuroImage 94: 312-336 (2014) - [j27]Annemie Ribbens, Jeroen Hermans, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Unsupervised Segmentation, Clustering, and Groupwise Registration of Heterogeneous Populations of Brain MR Images. IEEE Trans. Medical Imaging 33(2): 201-224 (2014) - [c65]David Robben, Engin Türetken, Stefan Sunaert, Vincent Thijs, Guy Willms, Pascal Fua, Frederik Maes, Paul Suetens:
Simultaneous Segmentation and Anatomical Labeling of the Cerebral Vasculature. MICCAI (1) 2014: 307-314 - [c64]Jean-Yves Wielandts, Stijn De Buck, Joris Ector, Dieter Nuyens, Frederik Maes, Hein Heidbüchel:
Registration-based filtering: An acceptable tool for noise reduction in left ventricular dynamic rotational angiography images? Image-Guided Procedures 2014: 903628 - 2013
- [j26]Brecht Heyde, Ruta Jasaityte, Daniel Barbosa, Valérie Robesyn, Stefaan Bouchez, Patrick Wouters, Frederik Maes, Piet Claus, Jan D'hooge:
Elastic Image Registration Versus Speckle Tracking for 2-D Myocardial Motion Estimation: A Direct Comparison In Vivo. IEEE Trans. Medical Imaging 32(2): 449-459 (2013) - [c63]Brecht Heyde, Daniel Barbosa, Piet Claus, Frederik Maes, Jan D'hooge:
Influence of the Grid Topology of Free-Form Deformation Models on the Performance of 3D Strain Estimation in Echocardiography. FIMH 2013: 308-315 - [c62]Daan Christiaens, Thijs Dhollander, Frederik Maes, Stefan Sunaert, Paul Suetens:
Groupwise Deformable Registration of Fiber Track Sets Using Track Orientation Distributions. CDMRI/MMBC@MICCAI 2013: 151-161 - [c61]David Robben, Stefan Sunaert, Vincent Thijs, Guy Willms, Frederik Maes, Paul Suetens:
Anatomical Labeling of the Circle of Willis Using Maximum A Posteriori Graph Matching. MICCAI (1) 2013: 566-573 - 2012
- [j25]Greetje Vande Velde, Janaki Raman Rangarajan, Ruth Vreys, Caroline Guglielmetti, Tom Dresselaers, Marleen Verhoye, Annemie van der Linden, Zeger Debyser, Veerle Baekelandt, Frederik Maes, Uwe Himmelreich:
Quantitative evaluation of MRI-based tracking of ferritin-labeled endogenous neural stem cell progeny in rodent brain. NeuroImage 62(1): 367-380 (2012) - [c60]Brecht Heyde, Piet Claus, Ruta Jasaityte, Daniel Barbosa, Stefaan Bouchez, Michael Vandenheuvel, Patrick Wouters, Frederik Maes, Jan D'hooge:
Motion and deformation estimation of cardiac ultrasound sequences using an anatomical B-spline transformation model. ISBI 2012: 266-269 - [c59]David Robben, Dirk Smeets, Daniel Ruijters, McElory Hoffmann, Laura Antanas, Frederik Maes, Paul Suetens:
Intra-patient Non-rigid Registration of 3D Vascular Cerebral Images. CLIP 2012: 106-113 - [c58]Brecht Heyde, Daniel Barbosa, Piet Claus, Frederik Maes, Jan D'hooge:
Three-Dimensional Cardiac Motion Estimation Based on Non-rigid Image Registration Using a Novel Transformation Model Adapted to the Heart. STACOM 2012: 142-150 - 2011
- [c57]Janaki Raman Rangarajan, Dirk Loeckx, Greetje Vande Velde, Tom Dresselaers, Uwe Himmelreich, Frederik Maes, Paul Suetens:
Impact of RF inhomogeneity correction on image registration of micro MRI rodent brain images. ISBI 2011: 570-573 - [c56]Thijs Dhollander, Jelle Veraart, Wim Van Hecke, Frederik Maes, Stefan Sunaert, Jan Sijbers, Paul Suetens:
Feasibility and Advantages of Diffusion Weighted Imaging Atlas Construction in Q-Space. MICCAI (2) 2011: 166-173 - [c55]An Elen, Jeroen Hermans, Hadewich Hermans, Frederik Maes, Paul Suetens:
A 3D+Time Spatio-temporal Model for Joint Segmentation and Registration of Sparse Cardiac Cine MR Image Stacks. STACOM 2011: 198-206 - [c54]Annemie Ribbens, Jeroen Hermans, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Probabilistic framework for subject-specific and population-based analysis of longitudinal changes and disease progression in brain MR images. Image Processing 2011: 796219 - 2010
- [j24]Dirk Loeckx, Pieter Slagmolen, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Nonrigid Image Registration Using Conditional Mutual Information. IEEE Trans. Medical Imaging 29(1): 19-29 (2010) - [j23]An Elen, Jeroen Hermans, Javier Ganame, Dirk Loeckx, Jan Bogaert, Frederik Maes, Paul Suetens:
Automatic 3-D Breath-Hold Related Motion Correction of Dynamic Multislice MRI. IEEE Trans. Medical Imaging 29(3): 868-878 (2010) - [c53]Dirk Loeckx, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Voxel based nonrigid image registration using local and partial volume similarity measures. ISBI 2010: 348-351 - [c52]Annemie Ribbens, Jeroen Hermans, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
SPARC: unified framework for automatic segmentation, probabilistic atlas construction, registration and clustering of brain MR images. ISBI 2010: 856-859 - [c51]Annemie Ribbens, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Semisupervised Probabilistic Clustering of Brain MR Images Including Prior Clinical Information. MCV 2010: 184-194
2000 – 2009
- 2009
- [c50]Maarten Depypere, Johan Nuyts, Kjell Laperre, Geert Carmeliet, Frederik Maes, Paul Suetens:
The Minimal Entropy Prior for Simultaneous Reconstruction and Segmentation of in Vivo Microct Trabecular Bone Images. ISBI 2009: 586-589 - [c49]Pieter Slagmolen, Sarah Roels, Dirk Loeckx, Karin Haustermans, Frederik Maes:
Validation of nonrigid registration for multi-tracer PET-CT treatment planning in rectal cancer radiotherapy. Image Processing 2009: 725936 - 2008
- [j22]Wim Van Hecke, Jan Sijbers, Emiliano D'Agostino, Frederik Maes, Steve De Backer, Everhard Vandervliet, Paul M. Parizel, Alexander Leemans:
On the construction of an inter-subject diffusion tensor magnetic resonance atlas of the healthy human brain. NeuroImage 43(1): 69-80 (2008) - [j21]An Elen, Hon Fai Choi, Dirk Loeckx, Hang Gao, Piet Claus, Paul Suetens, Frederik Maes, Jan D'hooge:
Three-Dimensional Cardiac Strain Estimation Using Spatio-Temporal Elastic Registration of Ultrasound Images: A Feasibility Study. IEEE Trans. Medical Imaging 27(11): 1580-1591 (2008) - [c48]Jeroen Hermans, Johan Bellemans, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
A statistical framework for the registration of 3D knee implant components to single-plane X-ray images. CVPR Workshops 2008: 1-8 - [c47]Dieter Seghers, Jeroen Hermans, Dirk Loeckx, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Model-Based Segmentation Using Graph Representations. MICCAI (1) 2008: 393-400 - [c46]Liesbet Roose, Dirk Loeckx, Wouter Mollemans, Frederik Maes, Paul Suetens:
Adaptive Boundary Conditions for Physically Based Follow-Up Breast MR Image Registration. MICCAI (2) 2008: 839-846 - 2007
- [j20]Wouter Mollemans, Filip Schutyser, Nasser Nadjmi, Frederik Maes, Paul Suetens:
Predicting soft tissue deformations for a maxillofacial surgery planning system: From computational strategies to a complete clinical validation. Medical Image Anal. 11(3): 282-301 (2007) - [j19]Bart Machilsen, Emiliano D'Agostino, Frederik Maes, Dirk Vandermeulen, Horst K. Hahn, Lieven Lagae, Peter Stiers:
Linear normalization of MR brain images in pediatric patients with periventricular leukomalacia. NeuroImage 35(2): 686-697 (2007) - [j18]Dieter Seghers, Dirk Loeckx, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Minimal Shape and Intensity Cost Path Segmentation. IEEE Trans. Medical Imaging 26(8): 1115-1129 (2007) - [c45]Emiliano D'Agostino, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Atlas-to-Image Non-rigid Registration by Minimization of Conditional Local Entropy. IPMI 2007: 320-332 - [c44]Dirk Loeckx, Pieter Slagmolen, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Nonrigid Image Registration Using Conditional Mutual Information. IPMI 2007: 725-737 - [c43]Stijn De Buck, Frederik Maes, André D'Hoore, Paul Suetens:
Evaluation of a Novel Calibration Technique for Optically Tracked Oblique Laparoscopes. MICCAI (1) 2007: 467-474 - [c42]Dieter Seghers, Dirk Loeckx, Frederik Maes, Paul Suetens:
Visual enhancement of interval changes using a temporal subtraction technique. Image Processing 2007: 65124R - 2006
- [j17]Emiliano D'Agostino, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
An information theoretic approach for non-rigid image registration using voxel class probabilities. Medical Image Anal. 10(3): 413-431 (2006) - [c41]Lennart Scheys, Ilse Jonkers, Dirk Loeckx, Frederik Maes, Arthur Spaepen, Paul Suetens:
Image Based Musculoskeletal Modeling Allows Personalized Biomechanical Analysis of Gait. ISBMS 2006: 58-66 - [c40]Wouter Mollemans, Filip Schutyser, Nasser Nadjmi, Frederik Maes, Paul Suetens:
Parameter Optimisation of a Linear Tetrahedral Mass Tensor Model for a Maxillofacial Soft Tissue Simulator. ISBMS 2006: 159-168 - [c39]Liesbet Roose, Wim De Maerteleire, Wouter Mollemans, Frederik Maes, Paul Suetens:
Simulation of Soft-Tissue Deformations for Breast Augmentation Planning. ISBMS 2006: 197-205 - [c38]Liesbet Roose, Wouter Mollemans, Dirk Loeckx, Frederik Maes, Paul Suetens:
Biomechanically Based Elastic Breast Registration Using Mass Tensor Simulation. MICCAI (2) 2006: 718-725 - [c37]Liesbet Roose, Wim De Maerteleire, Wouter Mollemans, Frederik Maes, Paul Suetens:
Pre-operative simulation and post-operative validation of soft-tissue deformations for breast implantation planning. Image-Guided Procedures 2006: 61410Z - [c36]Wouter Mollemans, Filip Schutyser, Nasser Nadjmi, Frederik Maes, Paul Suetens:
3D soft tissue predictions with a tetrahedral mass tensor model for a maxillofacial planning system: a quantitative validation study. Image-Guided Procedures 2006: 614118 - [c35]Qian Wang, Emiliano D'Agostino, Dieter Seghers, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Large-scale validation of non-rigid registration algorithms for atlas-based brain image segmentation. Image Processing 2006: 61440S - [c34]Dieter Seghers, Dirk Loeckx, Frederik Maes, Paul Suetens:
Image segmentation using local shape and gray-level appearance models. Image Processing 2006: 614401 - [c33]Jeroen Wouters, Emiliano D'Agostino, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Non-rigid brain image registration using a statistical deformation model. Image Processing 2006: 614411 - [c32]Emiliano D'Agostino, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
A Unified Framework for Atlas Based Brain Image Segmentation and Registration. WBIR 2006: 136-143 - [c31]Dirk Loeckx, Frederik Maes, Dirk Vandermeulen, Paul Suetens:
Comparison Between Parzen Window Interpolation and Generalised Partial Volume Estimation for Nonrigid Image Registration Using Mutual Information. WBIR 2006: 206-213 - [c30]