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Diana MATEUS

ENSEIGNANT-CHERCHEUR

Professeur des universités

Equipe : SIMS.

: Diana.Mateusatls2n.fr

: +33 (0)2 40 37 69 66

Adresse :

Centrale Nantes ( CN )
Petit Port
1, rue de la Noë
BP 92101
44321 NANTES Cedex 3

Batiment S, étage 3, bureau 309



Publications référencées sur HAL

Revues internationales avec comité de lecture (ART_INT)

    • [1] D. Al Chanti, V. Gonzalez Duque, M. Crouzier, A. Nordez, L. Lacourpaille, D. Mateus. IFSS-Net: Interactive Few-Shot Siamese Network for Faster Muscle Segmentation and Propagation in Volumetric Ultrasound. In IEEE Transactions on Medical Imaging ; éd. Institute of Electrical and Electronics Engineers, 2021.
      https://hal.archives-ouvertes.fr/hal-03197457
    • [2] M. Millardet, S. Moussaoui, D. Mateus, J. Idier, T. Carlier. Local-mean preserving post-processing step for non-negativity enforcement in PET imaging: application to 90 Y-PET. In IEEE Transactions on Medical Imaging ; éd. Institute of Electrical and Electronics Engineers, 2020, vol. 39.
      https://hal.archives-ouvertes.fr/hal-02565204
    • [3] A. Jiménez-Sánchez, A. Kazi, S. Albarqouni, C. Kirchhoff, P. Biberthaler, N. Navab, S. Kirchhoff, D. Mateus. Precise proximal femur fracture classification for interactive training and surgical planning. In International Journal of Computer Assisted Radiology and Surgery ; éd. Springer Verlag, 2020.
      https://hal.archives-ouvertes.fr/hal-02564696
    • [4] L. Morvan, T. Carlier, B. Jamet, C. Bailly, C. Bodet-Milin, P. Moreau, F. Kraeber-Bodere, D. Mateus. Leveraging RSF and PET images for prognosis of Multiple Myeloma at diagnosis. In International Journal of Computer Assisted Radiology and Surgery ; éd. Springer Verlag, 2019.
      https://hal.archives-ouvertes.fr/hal-02172435
    • [5] J. Renner, H. Phlipsen, B. Haller, F. Navarro-Avila, Y. Saint-Hill-Febles, D. Mateus, T. Ponchon, A. Poszler, M. Abdelhafez, R. Schmid, S. von Delius, P. Klare. Optical classification of neoplastic colorectal polyps – a computer-assisted approach (the COACH study). In Scandinavian Journal of Gastroenterology ; éd. Taylor & Francis, 2018, vol. 53, num. 9.
      https://hal.archives-ouvertes.fr/hal-02049344
    • [6] L. Peter, D. Mateus, P. Chatelain, D. Declara, N. Schworm, S. Stangl, G. Multhoff, N. Navab. Assisting the examination of large histopathological slides with adaptive forests. In Medical Image Analysis ; éd. Elsevier, 2017, vol. 35.
      https://hal.inria.fr/hal-01695986
    • [7] B. Gutiérrez-Becker, D. Mateus, L. Peter, N. Navab. Guiding multimodal registration with learned optimization updates. In Medical Image Analysis ; éd. Elsevier, 2017, vol. 41.
      https://hal.inria.fr/hal-01695990
    • [8] J. Perez-Gonzalez, F. Arámbula-Cosío, M. Guzmán, L. Camargo, B. Gutierrez, D. Mateus, N. Navab, V. Medina-Bañuelos. Spatial Compounding of 3-D Fetal Brain Ultrasound Using Probabilistic Maps. In Ultrasound in Medicine & Biology ; éd. Elsevier, 2017, vol. 44, num. 1.
      https://hal.inria.fr/hal-01695992
    • [9] F. Cuzzolin, D. Mateus, R. Horaud. Robust Temporally Coherent Laplacian Protrusion Segmentation of 3D Articulated Bodies. In International Journal of Computer Vision ; éd. Springer Verlag, 2015, vol. 112, num. 1.
      https://hal.archives-ouvertes.fr/hal-01053737
    • [10] D. Volpi, M. Sarhan, R. Ghotbi, N. Navab, D. Mateus, S. Demirci. Online tracking of interventional devices for endovascular aortic repair. In International Journal of Computer Assisted Radiology and Surgery ; éd. Springer Verlag, 2015, vol. 10, num. 6.
      https://hal.inria.fr/hal-01695949
    • [11] V. Castaneda, D. Mateus, N. Navab. Stereo Time-of-Flight with Constructive Interference. In IEEE Transactions on Pattern Analysis and Machine Intelligence ; éd. Institute of Electrical and Electronics Engineers, 2014, vol. 36, num. 7.
      https://hal.inria.fr/hal-01694247
    • [12] D. Mateus, L. Schwarz, N. Navab. Recognizing multiple human activities and tracking full-body pose in unconstrained environments. In Pattern Recognition ; éd. Elsevier, 2012, vol. 45, num. 1.
      https://hal.inria.fr/hal-01690285
    • [13] L. Schwarz, A. Mkhitaryan, D. Mateus, N. Navab. Human skeleton tracking from depth data using geodesic distances and optical flow. In Image and Vision Computing ; éd. Elsevier, 2012, vol. 30, num. 3.
      https://hal.inria.fr/hal-01692292
    • [14] S. Atasoy, D. Mateus, A. Meining, G. Yang, N. Navab. Endoscopic Video Manifolds for Targeted Optical Biopsy. In IEEE Transactions on Medical Imaging ; éd. Institute of Electrical and Electronics Engineers, 2012, vol. 31, num. 3.
      https://hal.inria.fr/hal-01693178

Conférences internationales avec comité de lecture et actes (COMM_INT)

    • [15] M. Tardy, D. Mateus. Lightweight U-Net for high-resolution breast imaging. In 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), avril 2020, Iowa City, états-Unis.
      https://hal.archives-ouvertes.fr/hal-02565347
    • [16] A. Jiménez-Sánchez, A. Kazi, S. Albarqouni, C. Kirchhoff, P. Biberthaler, N. Navab, S. Kirchhoff, D. Mateus. Precise Proximal Femur Fracture Classification for Interactive Training and Surgical Planning. In International Conference on Information Processing in Computer-Assisted Interventions (IPCAI), juin 2020, Munich, Allemagne.
      https://hal.archives-ouvertes.fr/hal-02564707
    • [18] C. Fourcade, L. Ferrer, G. Santini, N. Moreau, C. Rousseau, M. Lacombe, C. Guillerminet, M. Colombié, M. Campone, D. Mateus, M. Rubeaux. Combining Superpixels and Deep Learning Approaches to Segment Active Organs in Metastatic Breast Cancer PET Images *. In EMBC - Engineering in Medecine and Biology Conference, juillet 2020, Montréal, Canada.
      https://hal.archives-ouvertes.fr/hal-02565092
    • [19] M. Tardy, B. Scheffer, D. Mateus. Breast Density Quantification Using Weakly Annotated Dataset. In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI), avril 2019, Venice, Italie.
      https://hal.archives-ouvertes.fr/hal-02463086
    • [20] L. Morvan, T. Carlier, C. Bailly, B. Jamet, C. Bodet-Milin, P. Moreau, C. Touzeau, F. Kraeber-Bodere, D. Mateus. Leveraging Random Survival Forest (RSF) and PET images for prognosis of Multiple Myeloma at diagnosis. In International Conference on Information Processing in Computer-Assisted Interventions (IPCAI), juin 2019, Rennes, France.
      https://hal.archives-ouvertes.fr/hal-02174921
    • [21] M. Tardy, B. Scheffer, D. Mateus. A closer look onto breast density with weakly supervised dense-tissue masks. In CARS 2019—Computer Assisted Radiology and Surgery Proceedings of the 33rd International Congress and Exhibition, Rennes, France, June 18–21, 2019, juin 2019, Rennes, France.
      https://hal.archives-ouvertes.fr/hal-02565263
    • [22] M. Tardy, B. Scheffer, D. Mateus. A closer look onto breast density with weakly supervised dense-tissue masks. In Medical Imaging with Deep Learning MIDL 2019, juillet 2019, London, Royaume-Uni.
      https://hal.archives-ouvertes.fr/hal-02463094
    • [23] A. Jiménez-Sánchez, D. Mateus, S. Kirchhoff, C. Kirchhoff, P. Biberthaler, N. Navab, M. González Ballester, G. Piella. Medical-based Deep Curriculum Learning for Improved Fracture Classification. In International Conference on Medical Image Computing and Computer Aided Interventions, octobre 2019, Shenzen, Chine.
      https://hal.archives-ouvertes.fr/hal-02458516
    • [24] A. Jiménez-Sánchez, S. Albarqouni, D. Mateus. Capsule Networks against Medical Imaging Data Challenges. In MICCAI Workshop LABELS (Large-Scale Annotation of Biomedical Data and Expert Label Synthesis), septembre 2018, Granada, Espagne.
      https://hal.archives-ouvertes.fr/hal-02049352
    • [25] M. Millardet, S. Moussaoui, D. Mateus, J. Idier, M. Conti, T. Carlier. A comparative study of AML, NEGML and OSEM based on experimental and clinical 90Y-PET data using the CASToR platform. In Medical Imaging Conference, novembre 2018, Sydney, Australie.
      https://hal.archives-ouvertes.fr/hal-01953013
    • [26] F. Navarro-Avila, Y. Saint-Hill-Febles, J. Renner, P. Klare, S. von Delius, N. Navab, D. Mateus. Computer assisted optical biopsy for colorectal polyps. In SPIE Medical Imaging, mars 2017, Orlando, états-Unis.
      https://hal.inria.fr/hal-01695984
    • [27] B. Gutiérrez-Becker, D. Mateus, L. Peter, N. Navab. Learning Optimization Updates for Multimodal Registration. In International Conference on Medical Image Computing and Computer Aided Interventions (MICCAI), octobre 2016, Athenes, Grèce.
      https://hal.inria.fr/hal-01695963
    • [28] J. Perez-Gonzalez, F. Arámbula Cosío, M. Guzman, L. Camargo, B. Gutierrez, D. Mateus, N. Navab, V. Medina-Bañuelos. Ultrasound Fetal Brain Registration Using Weighted Coherent Point Drift. In International Symposium on Medical Information Processing and Analysis, décembre 2016, Tandil, Argentine.
      https://hal.inria.fr/hal-01695979
    • [29] M. Simonovsky, B. Gutiérrez-Becker, D. Mateus, N. Navab, N. Komodakis. A Deep Metric for Multimodal Registration. In 19th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2016), octobre 2016, Athènes, Grèce.In Sebastien Ourselin, Leo Joskowicz, Mert R. Sabuncu, Gozde Unal, William Wells (éds.), . Springer, 2016.
      https://hal.archives-ouvertes.fr/hal-01576914
    • [30] C. Hennersperger, M. Baust, D. Mateus, N. Navab. Computational Sonography. In International Conference on Medical Image Computing and Computer Aided Interventions (MICCAI), octobre 2015, Munich, Allemagne.
      https://hal.inria.fr/hal-01695952
    • [31] M. Zweng, P. Fallavolita, S. Demirci, M. Kowarschik, N. Navab, D. Mateus. Automatic guide-wire detection for neurointerventions using low-rank sparse matrix decomposition and denoising. In AE-CAI Workshop at the International Conference on Medical Image Computing and Computer Aided Interventions, octobre 2015, Munich, Allemagne.
      https://hal.inria.fr/hal-01695947
    • [32] L. Peter, O. Pauly, P. Chatelain, D. Mateus, N. Navab. Scale-Adaptive Forest Training via an Efficient Feature Sampling Scheme. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, octobre 2015, Munich, Allemagne.In Nassir Navab (éds.), . Springer International Publishing, 2015.
      https://hal.inria.fr/hal-01241978
    • [33] B. Gutierrez, D. Mateus, E. Shiban, B. Meyer, J. Lehmberg, N. Navab. A sparse approach to build shape models with routine clinical data. In 11th International Symposium on Biomedical Imaging (ISBI), avril 2014, Beijing, Chine.
      https://hal.inria.fr/hal-01693187
    • [34] N. Rieke, C. Hennersperger, D. Mateus, N. Navab. Ultrasound interactive segmentation with tensor-graph methods. In 11th International Symposium on Biomedical Imaging (ISBI), avril 2014, Beijing, Chine.
      https://hal.inria.fr/hal-01694226
    • [35] L. Peter, D. Mateus, P. Chatelain, N. Schworn, S. Stangl, G. Multhoff, N. Navab. Leveraging Random Forests for Interactive Exploration of Large Histological Images. In Int. Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014, septembre 2014, Boston, états-Unis.
      https://hal.inria.fr/hal-01056993
    • [36] C. Hennersperger, D. Mateus, M. Baust, N. Navab. A quadratic energy minimization framework for signal loss estimation from arbitrarily sampled ultrasound data.. In International Conference on Medical Image Computing and Computer Aided Interventions (MICCAI), septembre 2014, Boston, états-Unis.
      https://hal.inria.fr/hal-01694235
    • [37] Y. Chen, T. Hrabe, S. Pfeffer, O. Pauly, D. Mateus, N. Navab, F. Forster. Detection and identification of macromolecular complexes in cryo-electron tomograms using support vector machines. In 9th International Symposium on Biomedical Imaging (ISBI), mai 2012, Barcelona, Espagne.
      https://hal.inria.fr/hal-01692295
    • [38] S. Atasoy, D. Mateus, A. Meining, G. Yang, N. Navab. Targeted optical biopsies for surveillance endoscopies.. In International Conference on Medical Image Computing and Computer Aided Interventions (MICCAI), octobre 2012, Nice, France.
      https://hal.inria.fr/hal-01693180
    • [39] T. Birdal, D. Mateus, S. Ilic. Towards A Complete Framework For Deformable Surface Recovery Using RGBD Cameras. In International Robots and Systems (IRoS), Workshop on Color-Depth Fusion in Robotics, octobre 2012, Vila Moura, Portugal.
      https://hal.inria.fr/hal-01692294
    • [40] L. Schwarz, J. Lallemand, D. Mateus, N. Navab. Tracking planes with Time of Flight cameras and J-linkage. In Workshop on Applications of Computer Vision (WACV), janvier 2011, Kona, états-Unis.
      https://hal.inria.fr/hal-01690331
    • [41] V. Castaneda, D. Mateus, N. Navab. SLAM combining ToF and high-resolution cameras. In 2011 IEEE Workshop on Applications of Computer Vision (WACV), janvier 2011, Kona, états-Unis.
      https://hal.inria.fr/hal-01690320
    • [42] A. Safi, V. Castaneda, T. Lasser, D. Mateus, N. Navab. Manifold learning for dimensionality reduction and clustering of skin spectroscopy data. In SPIE Medical Imaging, mars 2011, Lake Buena Vista, états-Unis.
      https://hal.inria.fr/hal-01690329
    • [43] O. Pauly, B. Glocker, A. Criminisi, D. Mateus, A. Möller, S. Nekolla, N. Navab. Fast multiple organ detection and localization in whole-body MR dixon sequences.. In International Conference on Medical Image Computing and Computer Aided Interventions (MICCAI), septembre 2011, Toronto, Canada.
      https://hal.inria.fr/hal-01690326
    • [44] O. Pauly, D. Mateus, N. Navab. Building Implicit Dictionaries based on Extreme Random Clustering for Modality Recognition. In Medical Content-Based Retrieval for Clinical Decision Support MCBR-CDS 2011, septembre 2011, Toronto, Canada.
      https://hal.inria.fr/hal-01690325
    • [45] D. Mateus, V. Castaneda, N. Navab. Stereo time-of-flight. In IEEE International Conference on Computer Vision (ICCV), novembre 2011, Barcelona, Espagne.
      https://hal.inria.fr/hal-01694248
    • [46] D. Mateus, C. Wachinger, A. Keil, N. Navab. Manifold learning for patient position detection in MRI. In 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, avril 2010, Rotterdam, France.
      https://hal.inria.fr/hal-01690309
    • [47] L. Schwarz, D. Mateus, N. Navab. Multiple-Activity Human Body Tracking in Unconstrained Environments. In Articulated Motion and Deformable Objects, 6th International Conference, AMDO 2010, juillet 2010, Port d'Andratx, Espagne.
      https://hal.inria.fr/hal-01690293
    • [48] L. Schwarz, D. Mateus, V. Castaneda, N. Navab. Manifold Learning for ToF-based Human Body Tracking and Activity Recognition. In British Machine Vision Conference (BMVC) 2010, août 2010, Aberystwyth, Royaume-Uni.
      https://hal.inria.fr/hal-01690306
    • [49] S. Atasoy, D. Mateus, J. Lallemand, A. Meining, G. Yang, N. Navab. Endoscopic video manifolds.. In International Conference in Medical Imaging and Computer Aided Interventions (MICCAI), septembre 2010, Beijing, Chine.
      https://hal.inria.fr/hal-01690318
    • [50] D. Mateus, S. Atasoy, A. Georgiou, N. Navab, G. Yang. Wave Interference for Pattern Description. In ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II Pages 41-54, novembre 2010, Queensland, Nouvelle-Zélande.
      https://hal.inria.fr/hal-01690301
    • [51] A. Bronstein, M. Bronstein, U. Castellani, A. Dubrovina, L. Guibas, R. Horaud, R. Kimmel, D. Knossow, E. Von Lavante, D. Mateus, M. Ovsjanikov, A. Sharma. SHREC'10 track: correspondence finding. In 3DOR2010 - Eurographics Workshop on 3D Object Retrieval, mai 2010, Norrköping, Suède.In Mohamed Daoudi and Tobias Schreck and Michela Spagnuolo and Ioannis Pratikakis and Remco C. Veltkamp and Theoharis Theoharis (éds.), . Eurographics Association, 2010.
      https://hal.inria.fr/inria-00590262
    • [52] S. Atasoy, B. Glocker, S. Giannarou, D. Mateus, A. Meining, G. Yang, N. Navab. Probabilistic region matching in narrow-band endoscopy for targeted optical biopsy.. In International Conference on Medical Image Computing and Computer Assisted Intervention, septembre 2009, Londres, Royaume-Uni.
      https://hal.inria.fr/hal-01689590
    • [53] N. Padoy, D. Mateus, D. Weinland, M. Berger, N. Navab. Workflow Monitoring based on 3D Motion Features. In Workshop on Video-Oriented Object and Event Classification in Conjunction with ICCV 2009, septembre 2009, Kyoto, Japon.
      https://hal.inria.fr/inria-00429355
    • [54] L. Schwarz, D. Mateus, N. Navab. Discriminative Human Full-Body Pose Estimation from Wearable Inertial Sensor Data. In Modelling the Physiological Human. 3DPH 2009., novembre 2009, Zermatt, Suisse.
      https://hal.inria.fr/hal-01689321
    • [55] D. Knossow, A. Sharma, D. Mateus, R. Horaud. Inexact Matching of Large and Sparse Graphs Using Laplacian Eigenvectors. In 7th International Workshop on Graph-Based Representations in Pattern Recognition, mai 2009, Venice, Italie.In Andrea Torsello and Francisco Escolano and Luc Brun (éds.), Graph-Based Representations in Pattern Recognition. Springer, 2009.
      https://hal.inria.fr/inria-00446989
    • [56] D. Mateus, R. Horaud, D. Knossow, F. Cuzzolin, E. Boyer. Articulated Shape Matching Using Laplacian Eigenfunctions and Unsupervised Point Registration. In CVPR 2008 - IEEE Conference on Computer Vision and Pattern Recognition, juin 2008, Anchorage, états-Unis.
      https://hal.inria.fr/inria-00590251
    • [57] F. Cuzzolin, D. Mateus, D. Knossow, E. Boyer, R. Horaud. Coherent Laplacian 3-D Protrusion Segmentation. In CVPR 2008 - IEEE Conference on Computer Vision and Pattern Recognition, juin 2008, Anchorage, états-Unis.
      https://hal.inria.fr/inria-00590250
    • [58] D. Mateus, R. Horaud. Spectral Methods for 3-D Motion Segmentation of Sparse Scene-Flow. In WMVC 2007 - IEEE Workshop on Motion and Video Computing, février 2007, Austin, états-Unis.
      https://hal.inria.fr/inria-00590241
    • [59] D. Mateus, F. Cuzzolin, R. Horaud, E. Boyer. Articulated Shape Matching Using Locally Linear Embedding and Orthogonal Alignment. In NRTL 2007 - Workshop on Non-rigid Registration and Tracking through Learning, octobre 2007, Rio de Janeiro, Brésil.
      https://hal.inria.fr/inria-00590237
    • [60] D. Mateus, F. Cuzzolin, R. Horaud, E. Boyer. Articulated Shape Matching by Robust Alignment of Embedded Representations. In 3DRR 2007 - IEEE Workshop on 3D Representation for Recognition, octobre 2007, Rio de Janeiro, Brésil.
      https://hal.inria.fr/inria-00590238
    • [61] F. Cuzzolin, D. Mateus, E. Boyer, R. Horaud. Robust Spectral 3D-bodypart Segmentation along Time. In 2nd Workshop on Human Motion, Understanding, Modeling, Capture and Animation, octobre 2007, Rio de Janeiro, Brésil.In Ahmed Elgammal and Bodo Rosenhahn and Reinhard Klette (éds.), . Springer-Verlag, 2007.
      https://hal.inria.fr/inria-00590229
    • [62] F. Devernay, D. Mateus, M. Guilbert. Multi-Camera Scene Flow by Tracking 3-D Points and Surfels. In International Conference on Computer Vision and Pattern Recognition, 2006, New York, états-Unis.
      https://hal.inria.fr/inria-00262285
    • [63] D. Mateus, J. Avina Cervantes, M. Devy. Robot Visual Navigation in Semi-structured Outdoor Environments. In 2005 IEEE International Conference on Robotics and Automation, avril 2005, Barcelona, Espagne.
      https://hal.inria.fr/hal-01689316

Conférences nationales avec comité de lecture et actes (COMM_NAT)

    • [64] L. Morvan, T. Carlier, D. Mateus. The Limitations of Deep Learning: A Focus on Survival Analysis with PET Images.. In 4th Nuclear Technologies for Health Symposium (NTHS 2020), février 2020, Nantes, France.
      https://hal.archives-ouvertes.fr/hal-02569261
    • [65] L. Morvan, D. Mateus, C. Bailly, B. Jamet, C. Bode-Milin, P. Moreau, C. Touzeau, F. Kraeber-Bodéré, T. Carlier. Prédiction de la progression chez des patients atteints de myélome multiple par "Random Survival Forest. In SFMN, mars 2019, Paris, France.
      https://hal.archives-ouvertes.fr/hal-02175296

Ouvrages - Chapitres d‘ouvrages et directions d‘ouvrages (OUV)

    • [66] A. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. Zuluaga, S. Zhou, L. Joskowicz, D. Racoceanu. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part I (machine learning methodologies). 04-10-2020
      https://hal.archives-ouvertes.fr/hal-03144837
    • [67] A. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. Zuluaga, S. Zhou, L. Joskowicz, D. Racoceanu. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part II (image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks). 04-10-2020
      https://hal.archives-ouvertes.fr/hal-03144838
    • [68] A. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. Zuluaga, S. Zhou, L. Joskowicz, D. Racoceanu. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part III (CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis). 04-10-2020
      https://hal.archives-ouvertes.fr/hal-03144839
    • [69] A. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. Zuluaga, S. Zhou, L. Joskowicz, D. Racoceanu. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part IV (segmentation; shape models and landmark detection). 04-10-2020
      https://hal.archives-ouvertes.fr/hal-03144840
    • [70] A. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. Zuluaga, S. Zhou, L. Joskowicz, D. Racoceanu. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part V (biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology). 04-10-2020
      https://hal.archives-ouvertes.fr/hal-03144842
    • [71] A. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. Zuluaga, S. Zhou, L. Joskowicz, D. Racoceanu. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part VI (angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging). 04-10-2020
      https://hal.archives-ouvertes.fr/hal-03144844
    • [72] A. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. Zuluaga, S. Zhou, L. Joskowicz, D. Racoceanu. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part VII (brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography). 04-10-2020
      https://hal.archives-ouvertes.fr/hal-03144845
    • [73] L. Zhou, N. Heller, Y. Shi, Y. Xiao, R. Sznitman, V. Cheplygina, D. Mateus, E. Trucco, X. Hu, D. Chen, M. Chabanas, H. Rivaz, I. Reinertsen. Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention. 10-2019
      https://hal.archives-ouvertes.fr/hal-02385145
    • [74] D. Stoyanov, Z. Taylor, S. Balocco, R. Sznitman, A. Martel, L. Maier-Hein, L. Duong, G. Zahnd, S. Demirci, S. Albarqouni, S. Lee, S. Moriconi, V. Cheplygina, D. Mateus, E. Trucco, E. Granger, P. Jannin. 7th Joint International Workshop, CVII-STENT (Intravascular Imaging and Computer Assisted Stenting) 2018 and Third International Workshop, LABELS (Large-Scale Annotation of Biomedical Data and Expert Label Synthesis) 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. 16-09-2018
      https://hal.archives-ouvertes.fr/hal-02568515
    • [75] A. Criminisi, D. Robertson, O. Pauly, B. Glocker, E. Konukoglu, J. Shotton, D. Mateus, G. Martinez Möller, S. Nekolla, N. Navab. Anatomy Detection and Localization in 3D Medical Images. In Decision Forests for Computer Vision and Medical Image Analysis. 01-2013
      https://hal.inria.fr/hal-01693184
    • [76] D. Mateus, C. Wachinger, S. Atasoy, L. Schwarz, N. Navab. Learning Manifolds: Design Analysis for Medical Applications. In Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis. Advances in Bioinformatics and Biomedical Engineering. Editor Suzuki, Kenji. Publisher IGI Global, 2012. ISBN1466600608, 9781466600607. 31-01-2012
      https://hal.inria.fr/hal-01690334
    • [77] A. Sharma, R. Horaud, D. Mateus. 3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching. In Image Processing and Analysing With Graphs: Theory and Practice. 07-2012
      https://hal.inria.fr/inria-00590273v2

Theses et HDR (THESE)

Autres publications (AUTRES)

    • [79] L. Morvan, D. Mateus, C. Bailly, B. Jamet, C. Bodet-Milin, P. Moreau, C. Touzeau, F. Kraeber-Bodéré, T. Carlier. Prédiction de la progression chez des patients atteints de myélome multiple par "Random Survival Forest. In ..., 2019, Paris, France.
      https://www.hal.inserm.fr/inserm-02100680
    • [80] M. Millardet, S. Moussaoui, D. Mateus, J. Idier, T. Carlier. Étude comparative d'AML, NEGML et OSEM sur des données 90Y-TEP expérimentales et cliniques en utilisant CASToR. In Journées du Cancéropôle Grand Ouest, juillet 2018, Vannes, France.
      https://hal.archives-ouvertes.fr/hal-01953061
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