Publications

Journals

1. [SD 2024] M. Cabezas, Y. Diez, C. Martinez-Diago, A. Maroto "A benchmark for 2D foetal brain ultrasound analysis". Scientific Data, Volume 11, 2024.
2. [AIM 2024] L. Bai, D. Wang, H. Wang, M. Barnett, M. Cabezas, W. Cai, F. Calamante, K. Kyle, D. Liu, L. Ly, A. Nguyen, Ch.-Ch. Shieh, R. Sullivan, G. Zhan, W. Ouyang, C. Wang "Improving multiple sclerosis lesion segmentation across clinical sites: A federated learning approach with noise-resilient training". Artificial Intelligence in Medicine, Volume 152, 2024.
3. [S 2024] M. Cabezas, Y. Diez "An Analysis of Loss Functions for Heavily Imbalanced Lesion Segmentation". Sensors, Volume 24(6), 2024.
4. [EI 2024] K. Moritake, M. Cabezas, T.T.C. Nhung, M.L.L. Caceres, Y. Diez "Sub-alpine shrub classification using UAV images: Performance of human observers vs DL classifiers". Ecological Informatics, Volume 80, 2024.
5. [BC 2023] C. Maher, Z. Tang, A. D’Souza, M. Cabezas, W. Cai, M. Barnett, O. Kavehei, C. Wang, A. Nikpour "Deep learning distinguishes connectomes from focal epilepsy patients and controls: feasibility and clinical implications". Brain Communications, Volume 5(6), 2023.
6. [npjDM 2023] M. Barnett, D. Wang, H. Beadnall, A. Bischof, D. Brunacci, H. Butzkueven, J.W.L. Brown, M. Cabezas, T. Das, T. Dugal, D. Guilfoyle, A. Klistorner, S. Krieger, K. Kyle, L. Ly, L. Masters, A. Shieh, Z. Tang, A. van der Walt, K. Ward, H. Wiendl, G. Zhan, R. Zivadinov, Y. Barnett, C. Wang "A real-world clinical validation for AI-based MRI monitoring in multiple sclerosis". npj Digital Medicine, Volume 6, 2023.
7. [FRadi 2023] Z. Tang, S. Chen, A. D'Souza, D. Liu, F. Calamante, M. Barnett, W. Cai, C. Wang, M. Cabezas. "High angular diffusion tensor imaging estimation from minimal evenly distributed diffusion gradient directions". Frontiers in Radiology, Volume 3, 2023.
8. [NI-CL 2023] S. Aja-Fernández, C. Martín-Martín, A. Planchuelo-Gómez, A. Faiyaz, M.N. Uddin, G. Schifitto, A. Tiwari, S.J. Shigwan, R.K. Singh, T. Zheng, Z. Cao, D. Wu, S.B. Blumberg, S. Sen, T. Goodwin-Allcock, P.J. Slator, M.Y. Avci, Z. Li, B. Bilgic, Q. Tian, X. Wang, Z. Tang, M. Cabezas, A. Rauland, D. Merhof, R.M. Maria, V.P. Campos, T. Santini, M. A. da Costa Vieira, S.K. HashemizadehKolowri, E. DiBella, C. Peng, Z. Shen, Z. Chen, I. Ullah, M. Mani, H. Abdolmotalleby, S. Eckstrom, S.H. Baete, P. Filipiak, T. Dong, Q. Fan, R. de Luis-García, A. Tristán-Vega, T. Pieciak. "Validation of Deep Learning techniques for quality augmentation in diffusion MRI for clinical studies". NeuroImage: Clinical, Volume 39, 2023. [JCR NI IF 4.2, Q2(4/14)]
9. [FNins 2023] G. Zhan, D. Wang, M. Cabezas, L. Bai, K. Kyle, W. Ouyang, M. Barnett, W. Cai, C. Wang. "Learning from pseudo-labels: deep networks improve consistency in longitudinal brain volume estimation" Frontiers in Neuroscience, Volume 17, 2023. [JCR NS IF 4.3, Q2(94/272)]
10. [FNins 2023] D. Liu, M. Cabezas, and D. Wang, Z. Tang, L. Bai, G. Zhan, Y. Luo, K. Kyle, L. Ly, J. Yu, C-C Shieh, A. Nguyen, E. Kandasamy Karuppiah, R. Sullivan, F. Calamante, M. Barnett, W. Ouyang, W. Cai, C. Wang. "Multiple sclerosis lesion segmentation: revisiting weighting mechanisms for federated learning". Frontiers in Neuroscience, Volume 17, 2023. [JCR NS IF 4.3, Q2(94/272)]
11. [FRobt 2022] Y. Diez, N. Gracias, M. Cabezas, C. Juergens, M.L. Lopez. "Editorial: AI Processing of UAV Acquired Images for Pattern Monitoring in Natural and Urban Environments". Frontiers in Robotics and AI, Volume 9, 2022. [JCR N IF 3.4, Q3(23/42)]
12. [MELBA 2022] R. Mehta, A. Filos, U. Baid, C. Sako, R. McKinley, M. Rebsamen, K. Dätwyler, R. Meier, P. Radojewski, G.K. Murugesan, S. Nalawade, C. Ganesh, B. Wagner, F.F. Yu, B. Fei, A.J. Madhuranthakam, J.A. Maldjian, L. Daza, C. Gómez, P. Arbeláez, C. Dai, S. Wang, H. Reynaud, Y. Mo, E. Angelini, Y. Guo, W. Bai, S. Banerjee, L. Pei, Murat AK, S. Rosas-González, I. Zemmoura, C. Tauber, M.H. Vu, T. Nyholm, T. Löfstedt, L.M. Ballestar, V. Vilaplana, H. McHugh, G.M. Talou, A. Wang, J. Patel, K. Chang, K. Hoebel, M. Gidwani, N. Arun, S. Gupta, M. Aggarwal, P. Singh, E.R. Gerstner, J. Kalpathy-Cramer, N. Boutry, A. Huard, L. Vidyaratne, M.M. Rahman, K.M. Iftekharuddin, J. Chazalon, E. Puybareau, G. Tochon, J. Ma, Mariano Cabezas, X. Llado, A. Oliver, L. Valencia, S. Valverde, M. Amian, M. Soltaninejad, A. Myronenko, A. Hatamizadeh, X. Feng, Q. Dou, N. Tustison, C. Meyer, N.A. Shah, S. Talbar, M.-A. Weber, A. Mahajan, A. Jakab, R. Wiest, H.M. Fathallah-Shaykh, A. Nazeri, M. Milchenko, D. Marcus, A. Kotrotsou, R. Colen, J. Freymann, J. Kirby, C. Davatzikos, B. Menze, S. Bakas, Y. Gal, T. Arbel. "QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation-Analysis of Ranking Scores and Benchmarking Results". Journal of Machine Learning for Biomedical Imaging, Volume 1, 2022.
13. [JBHI 2022] Y. Ma, C. Zhang, M. Cabezas, Y. Song, Z. Tang, D. Liu, W. Cai, M. Barnett, C. Wang. "Multiple Sclerosis Lesion Analysis in Brain Magnetic Resonance Images: Techniques and Clinical Applications". IEEE Journal of Biomedical and Health Informatics, Volume 26(6), 2022. [JCR CSIA IF 7.7, Q1(18/110)]
14. [RS 2021] Y. Diez, S. Kentsch, M. Fukuda, M.L.L. Caceres, K. Moritake, M. Cabezas. "Deep Learning in Forestry Using UAV-Acquired RGB Data: A Practical Review". Remote Sensing, Volume 13(14), 2837, 2021. [JCR GM IF 5.349, Q1(31/201)]
15. [NINF 2021] J. Bernal, S. Valverde, K. Kushibar, M. Cabezas, A. Oliver, X. Lladó & The Alzheimer’s Disease Neuroimaging Initiative. "Generating Longitudinal Atrophy Evaluation Datasets on Brain Magnetic Resonance Images Using Convolutional Neural Networks and Segmentation Priors". Neuroinformatics, Volume 19, 477–492, 2021. [JCR NS IF 2.864, Q3(163/272)]
16. [S 2021] S. Kentsch, M. Cabezas, L. Tomhave, J. Groß, B. Burkhard, M.L. Lopez Caceres, K. Waki and Y. Diez. "Analysis of UAV-Acquired Wetland Orthomosaics Using GIS, Computer Vision, Computational Topology and Deep Learning". Sensors, Volume 21(2), 471, 2021. [JCR EEE IF 3.847, Q2(100/275)]
17. [RS 2020] M. Cabezas, S. Kentsch, L. Tomhave, J. Gross, M.L. Lopez Caceres and Y. Diez. "Detection of Invasive Species in Wetlands: Practical DL with Heavily Imbalanced Data". Remote Sensing, Volume 12(20), 3431, 2020. [JCR GM IF 4.848, Q1(27/200)]
18. [NI-CL 2020] M. Salem, S. Valverde, M. Cabezas, D. Pareto, A. Oliver, J. Salvi, À. Rovira, and X. Lladó. "A fully convolutional neural network for new T2-w lesion detection in multiple sclerosis". NeuroImage: Clinical, Volume 25, 102149, 2020. [JCR N IF 3.943, Q1(3/14)]
19. [NI-CL 2020] M. Rakic, M. Cabezas, K. Kushibar, A. Oliver, X. Lladó. "Improving the Detection of Autism Spectrum Disorder by Combining Structural and Functional MRI Information". NeuroImage: Clinical, 25, 102181, 2020. [JCR N IF 3.943, Q1(3/14)]
20. [SREP 2019] K. Kushibar, S. Valverde, S. González-Villà, J. Bernal, M. Cabezas, A. Oliver, and X. Lladó. "Supervised domain adaptation for automatic sub-cortical brain structure segmentation with minimal user interaction". Nature. Scientific Reports 9(6742), 2019. [JCR MS IF 4.011, Q1(15/69)]
21. [IEEE ACCESS 2019] M. Salem, S. Valverde, M. Cabezas, D. Pareto, A. Oliver, J. Salvi, À. Rovira, and X. Lladó. "Multiple Sclerosis Lesion Synthesis in MRI using an encoder-decoder U-NET". IEEE Access, 7, pp. 25171-25185, 2019. [JCR CSIS IF 3.557, Q1(24/148)]
22. [NI-CL 2019] S. Valverde, M. Salem, M. Cabezas, D. Pareto, J. C. Vilanova, Ll. Ramió-Torrentà, À. Rovira, and J. Salvi, A. Oliver, X. Lladó. "One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks". NeuroImage: Clinical, 21. 2019. [JCR N IF 3.869, Q1(3/14)]
23. [SREP 2018] O. Commowick, A. Istace, M. Kain, B. Laurent, F. Leray, M. Simon, S. C. Pop, P. Girard, R. Améli, J.-C. Ferré, A. Kerbrat, T. Tourdias, F. Cervenansky, T. Glatard, J. Beaumont, S. Doyle, F. Forbes, J. Knight, A. Khademi, A. Mahbod, C. Wang, R. McKinley, F. Wagner, J. Muschelli, E. Sweeney, E. Roura, X. Lladó, M. M. Santos, W. P. Santos, A. G. Silva-Filho, X. Tomas-Fernandez, H. Urien, I. Bloch, S. Valverde, M. Cabezas, F. J. Vera-Olmos, N. Malpica, C. Guttmann, S. Vukusic, G. Edan, M. Dojat, M. Styner, S. K. Warfield, F. Cotton & C. Barillot "Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure". Nature. Scientific Reports, 8. 2018. [JCR MS IF 4.122, Q1(12/64)]
24. [MIA 2018] K. Kushibar, S. Valverde, S. González-Villà, J. Bernal, M. Cabezas, A. Oliver, X. Lladó. "Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features". Medical Image Analysis, 48, pp. 177-186, 2018. [JCR CSAI IF 5.356, Q1(6/105)]
25. [NI-CL 2018] M. Salem, M. Cabezas, S. Valverde, D. Pareto, A. Oliver, J. Salvi, À. Rovira, and X. Lladó. "A supervised framework with intensity subtraction and deformation field features for the detection of new T2-w lesions in multiple sclerosis". NeuroImage: Clinical, 17C, pp. 607-615, 2018. [JCR N IF 3.869, Q1(3/14)]
26. [NI-Cl 2017] S. González-Villà, S. Valverde, M. Cabezas, D. Pareto, J.C. Vilanova, Ll. Ramió-Torrentà, À. Rovira, A. Oliver, X. LLadó. "Evaluating the effect of multiple sclerosis lesions on automatic brain structure segmentation". NeuroImage: Clinical, 15, pp. 228-238, 2017. [JCR N IF 3.857, Q1(3/14)]
27. [NI 2017] S. Valverde, M. Cabezas, E. Roura, S. González-Villà, D. Pareto, J.C. Vilanova, Ll. Ramió-Torrentà, À. Rovira, A. Oliver, and X. Lladó. "Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach". NeuroImage, 155, pp. 159-168, 2017. [JCR NI IF 5.463, Q1(1/14)]
28. [AJNR 2016] M. Cabezas, J.F. Corral, A. Oliver, Y. Diez, M. Tintoré, C. Auger, X. Montalban, X. Lladó, D. Pareto, and À. Rovira. "Improved automatic detection of new T2 lesions in multiple sclerosis using deformation fields". American Journal of Neuroradiology, 37(11), pp. 1816-1823, 2016. [JCR RNMMI IF 3.589, Q1(19/125)]
29. [AJNR 2015] S. Valverde, A. Oliver, Y. Díez, M. Cabezas, J.C. Vilanova, Ll. Ramió-Torrentà, À. Rovira, and X. Lladó. "Evaluating the effects of white matter multiple sclerosis lesions on the volume estimation of six brain tissue segmentation methods". American Journal of Neuroradiology, 36(6), pp. 1109-115, 2015. [JCR RNMMI IF 3.675, Q1(18/122)]
30. [NRAD 2015] E. Roura, A. Oliver, M. Cabezas, S. Valverde, D. Pareto, J.C. Vilanova, Ll. Ramió-Torrentà, À. Rovira, and X. Lladó. "A toolbox for multiple sclerosis lesion segmentation". Neuroradiology, 57(10), pp. 1031-1043, 2015. [JCR RNMMI IF 2.485, Q2(41/125)] (pdf KB)
31. [JMRI 2015] S. Valverde, A. Oliver, M. Cabezas, E. Roura, X. Lladó. "Comparison of ten brain tissue segmentation methods using revisited IBSR annotations". Journal of Magnetic Resonance Imaging, 41(1), pp. 93-101. 2015. [JCR RNMMI IF: 2.788 Q1(29/121)]
32. [JNM 2014] M. Cabezas, A. Oliver, S. Valverde, B. Beltran, J. Freixenet, J.C. Vilanova, Ll. Ramió-Torrentà, À. Rovira, and X. Lladó. "BOOST: a supervised approach for multiple sclerosis lesion segmentation". Journal of Neuroscience Methods, 237, pp. 108-117, 2014. [JCR N IF 1.959, Q3(182/251)]
33. [CMPB 2014] M. Cabezas, A. Oliver, E. Roura, J. Freixenet; J.C Vilanova, Ll. Ramió-Torrentà, A. Rovira, X. Lladó. "Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding". Computer Methods and Programs in Biomedicine, 115(3), pp. 147-161. 2014. [JCR CSTM IF 1.897, Q1(15/102)]
34. [NINF 2014] Y. Diez, A. Oliver, M. Cabezas, S. Valverde, R. Martí, J.C. Vilanova, Ll. Ramió-Torrentà, A. Rovira, and X. Lladó. "Intensity based methods for brain MRI longitudinal registration. A study on multiple sclerosis patients". Neuroinformatics, 12(3), pp. 365-379. 2014. [JCR CSTM IF 3.102, Q1(12/102)]
35. [CMPB 2014] E. Roura, A. Oliver, M. Cabezas, J.C. Vilanova, A. Rovira and Ll. Ramió-Torrentà, X. Lladó. "MARGA: Multispectral adaptive region growing algorithm for brain extraction on axial MRI". Computer Methods and Programs in Biomedicine, 113(2), pp. 655-673. 2014. [JCR CSTM IF 1.897, Q1(15/102)]
36. [INFSCI 2012] X. Lladó, A. Oliver, M. Cabezas, J. Freixenet, J.C. Vilanova, A. Quiles, L. Valls, Ll. Ramió-Torrentà, A. Rovira. "Segmentation of multiple sclerosis lesions in brain MRI: a review of automated approaches". Information Sciences, 186(1), pp. 164-185. 2012. [JCR CSIS IF 3.643, Q1(6/132)]
37. [CMPB 2011] M. Cabezas, A. Oliver, X. Lladó, J. Freixenet, M. Bach-Cuadra. "A review of atlas-based segmentation for magnetic resonance brain images". Computer Methods and Programs in Biomedicine, 104(3), pp. e158-e177. 2011. [JCR CSTM IF 1.516, Q1(14/99),]

Conferences

1. [DICTA 2023] Y. Shi, C. Wang, D. Liu, W. Cai, M. Cabezas. "Understanding the role of saliency maps for biomarker research in 3D medical imaging classification". International Conference on Digital Image Computing: Techniques and Applications. Port Macquarie, Australia. November 2023.
2. [MICCAI 2023-DeCaF] G. Zhan, J. Deng, D. Wang, M. Cabezas, W. Ouyang, M. Barnett, C. Wang. "Fed-CoT: Co-Teachers for Federated Semi-Supervised MS Lesion Segmentation". MICCAI 2023 Workshop on Distributed, Collaborative and Federated Learning. Vancouver, Canada. 2023.
3. [ISMRM 2023] S. Aja-Fernandez, C. Martin-Martin, T. Pieciak, A. Planchuelo-Gomez, A. Faiyaz, N, Uddin, A. Tiwari, S.J. Shigwan, T. Zheng, Z. Cao, S.B. Blumberg, S. Sen, M.Y. Avci, Z. Li, X. Wang, Z. Tang, A. Rauland, D. Merhof, R.M. Maria, V.P. Campos, S. HashemizadehKolowri, E. DiBella, C. Peng, Z. Chen, I. Ullah, M. Mani, S. Eckstrom, S.H. Baete, S. Scifitto, R. Kumar, D. Wu, T. Goodwin-Allcock, P.J. Slator, B. Bilgic, Q. Tian, M. Cabezas, T. Santini, M.A. da Costa Vieira, Z. Shen, H. ABdolmotalleby, P. Filipiak, A. Tristan-Vega, R. de Luis-Garcia. "Validation of Deep Learning techniques for quality augmentation in diffusion MRI for clinical studies". Joint Annual Meeting ISMRM-ESMRMB & ISMRT 32nd Annual Meeting 2023. Toronto, Canada. 6th June 2023.
4. [ISMRM 2023] D. Liu, M. Cabezas, D. Wang, Z. Tang, G. Zhan, K. Kyle, L. Ly, J. Yu, C.-C. Shieh, R. Sullivan, F. Calamante, M. Barnett, W. Ouyang, W. Cai, C. Wang. "A novel Federated Learning framework for accurate and secure multi-center MS lesion Segmentation". Joint Annual Meeting ISMRM-ESMRMB & ISMRT 32nd Annual Meeting 2023. Toronto, Canada. 7th June 2023.
5. [ISMRM 2023] X. Wang, Z. Tang, M. Cabezas, A. D’Souza, F. Calamante, D. Liu, M. Barnett, S. Tu, C. Wang, W. Cai. "FOD-Net 2.0: End-to-end FOD enhancement for low angular diffusion acquisitions using deep learning". Joint Annual Meeting ISMRM-ESMRMB & ISMRT 32nd Annual Meeting 2023. Toronto, Canada. 7th June 2023.
6. [ISMRM 2023] Z. Tang, X. Wang, M. Cabezas, L. Zhu, D. Liu, M. Barnett, W. Cai, C. Wang. "Reducing the impact of disrupted brain regions in Diffusion Tensor Imaging with inpainting". Joint Annual Meeting ISMRM-ESMRMB & ISMRT 32nd Annual Meeting 2023. Toronto, Canada. 5th June 2023.
7. [ISBI 2023] S. Chen, Z. Tang, D. Liu, C. Fornusek, M. Barnett, C. Wang, M. Cabezas, W. Cai. "Precise few-shot fat-free thigh muscle segmentation in T1-weighted MRI". International Symposium on Biomedical Imaging (ISBI). Cartagena de Indias, Colombia. April 2023.
8. [DICTA 2022] Z. Tang, X. Wang, L. Zhu, M. Cabezas, D. Liu, M. Barnett, W. Cai, C. Wang. "TW-BAG: Tensor-wise brain-aware gate network for inpainting disrupted diffusion tensor imaging". International Conference on Digital Image Computing: Techniques and Applications. Sydney, Australia. November 2022.
9. [MS 2022] G. Zhan, D. Wang, M. Cabezas, M. Barnett, C. Wang. "Learning from pseudo-labels: deep networks improve classical longitudinal brain volume change estimation for patients with MS". Multiple Sclerosis. Amsterdam, Netherlands. October 2022.
10. [MICCAI 2022-CDMRI] Z. Tang, X. Wang, M. Cabezas, A. D’Souza, F. Calamante, D. Liu, M. Barnett, C. Wang, W. Cai. "Diffusion MRI Fibre Orientation Distribution Inpainting". MICCAI 2022 International Workshop on Computational Diffusion MRI. Singapore, Singapore. 22nd September 2022.
11. [ISMRM 2022] Z. Tang, M. Cabezas, K. Kyle, A. D'Souza, S. Tisch, B. Jonker, Y. Barnett, J. Maamary, J. Maller, M. Barnett, W. Cai, and C. Wang. "Towards a personalized MRgFUS treatment for tremor disorders: A study on the number of ablations using deep learning and structural connectivity". Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting 2022. London, United Kingdom. 7th May 2022.
12. [ISMRM 2022] S. Wacher, J. Lv, M. Cabezas. "Understanding Alzheimer's disease through fMRI and deep learning". Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting 2022. London, United Kingdom. 7th May 2022.
13. [MS 2022] D. Liu, M. Cabezas, G. Zhan, D. Wang, L. Ly, K. Kyle, H. Beadnall, H. Butzkueven, A. Van Der Walt, M. Gresle, K. Buzzard, T. Kalincik, J. Lechner-Scott, B. Taylor, R. Hyde, M. Barnett, W. Cai, C. Wang. "DAMS-Net: A Domain Adaptive Lesion Segmentation Framework in Patients with Multiple Sclerosis from Multiple Imaging Centers". American Academy of Neurology, Seattle. July 2022.
14. [PACTRIMS 2021] M. Cabezas, Y. Luo, K. Kyle, L. Ly, C. Wang, M. Barnett. "A dual headed Unet approach for automatic lesion activity assessment". Pan-Asian Committee on Treatment and Research in Multiple Sclerosis (PACTRIMS), Singapore. November 2021.
15. [MICCAI 2021] Z. Tang, M. Cabezas, D. Liu, M. Barnett, W. Cai, C. Wang. "LG-Net: Lesion Gate Network for Multiple Sclerosis Lesion Inpainting". International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2021. Strasbourg, France. 23rd September 2021.
16. [MICCAI-MSSEG2 2021] M. Cabezas, Y. Luo, K. Kyle, L. Ly, C. Wang, M. Barnett. "Estimating lesion activity through feature similarity: A dual path Unet approach for the MSSEG2 MICCAI challenge". MSSEG-2 challenge proceedings: Multiple sclerosis new lesions segmentation challenge using a data management and processing infrastructure. MICCAI 2021. Strasbourg, France. 16th September 2021.
17. [MICCAI-BRATS 2018] M. Cabezas, S. Valverde, S. González-Villà, A. Clèrigues, M. Salem, K. Kushibar, J. Bernal, A. Oliver, J. Salvi and X. Lladó. "Survival prediction using ensemble tumor segmentation and transfer learning ". Multimodal Brain Tumor Segmentation Challenge 2018 (BRATS) in Medical Imaging. MICCAI 2018. Granada, Spain. 16th September 2018.
18. [MICCAI-MRBRAINS 2018] J. Bernal, M. Salem, K. Kushibar, A. Clérigues, S. Valverde, M. Cabezas, S. Gonzàlez-Villà, J. Salvi, A. Oliver, and X. Lladó. "MR Brain segmentation using an ensemble of multi-path u-shaped convolutional neural networks and tissue segmetnation priors". MR Brain tissue segmentation Challenge in Medical Imaging. MICCAI 2018. Granada, Spain. 16th September 2018.
19. [MICCAI-ISLES 2018] A. Clérigues, S. Valverde, J. Bernal, K. Kushibar, M. Cabezas, A. Oliver, and X. Lladó. "Ensemble of convolution neural networks for acute stroke anatomy differentiation". Ischiemic Stroke Lesion Segmentation (ISLES) in Medical Imaging. MICCAI 2018. Granada, Spain. 16th September 2018.
20. [MICCAI-iSeg 2017] J. Bernal, K. Kushibar, S. Valverde, M.Cabezas, S. González-Villà, M. Salem, J. Salvi, A. Oliver, Xavier Lladó. "Six-month infant brain tissue segmentation using three dimensional fully convolutional neural networks and pseudo-labelling". MICCAI Grand Challenge on 6-month infant brain MRI segmentation iSeg-2017. MICCAI 2017. Quebec, Canada. 14 September 2017.
21. [MICCAI-WMH 2017] S. Valverde, M.Cabezas, J. Bernal, K. Kushibar, S. González-Villà, M. Salem, J. Salvi, A. Oliver, Xavier Lladó. "White matter hyperintensities segmentation using a cascade of three convolutional neural networks". MICCAI Grand Challenge on White Matter Hyperintensties Segmentation. MICCAI 2017. Quebec, Canada. 14 September 2017.
22. [MS 2017] S. Valverde, M. Cabezas, E. Roura, S. González-Villà, D. Pareto, J.C. Vilanova, Ll. Ramió-Torrentà, A. Rovira, A. Oliver, X. Lladó. "A deep learning approach for multiple sclerosis lesion segmentation". Multiple Sclerosis, Paris. October 2017.
23. [MS 2017] S. González-Villà, S. Valverde, M. Cabezas, D. Pareto, J.C. Vilanova, Ll. Ramió-Torrentà, A. Rovira, A. Oliver, X. Lladó. "Do multiple sclerosis lesions affect automatic brain structure segmentation?". Multiple Sclerosis, Paris. October 2017.
24. [MS 2017] M. Salem, M. Cabezas, S. Valverde, D. Pareto, A. Rovira, A. Oliver, J. Salvi, A. Rovira, X. Lladó. "Supervised detection of newly appearing T2-w multiple sclerosis lesions with subtraction and deformation fields features". Multiple Sclerosis, Paris. October 2017. [JCR CN IF:4.840 Q1(27/194)]
25. [MS 2016] M. Cabezas, D. Pareto, A. Oliver, J.F. Corral, C. Auger, X. Aymerich, J. Sastre-Garriga, M. Tintoré, X. Montalban, X. Lladó, A. Rovira. "Detection of new multiple sclerosis lesions on longitudinal brain MRI". Multiple Sclerosis. 22(S3), pp 215-216. London. September 2016.
26. [MSSEG 2016] E. Roura, M. Cabezas, S. Valverde, S. González-Villà, J. Salvi, A. Oliver, and X. Lladó. "Unsupervised Multiple Sclerosis Lesion Detection and Segmentation using Rules and Level Sets". Multiple Sclerosis Lesions segmentation (MSSEG) Challenge. MICCAI 2016. Athens, Greece. 21 October 2016.
27. [MSSEG 2016] S. Valverde, M. Cabezas, E. Roura, S. González-Villà, J. Salvi, A. Oliver, and X. Lladó. "Multiple Sclerosis Lesion Detection and Segmentation using a Convolutional Neural Network of 3D Patches". Multiple Sclerosis Lesions segmentation (MSSEG) Challenge. MICCAI 2016. Athens, Greece. 21 October 2016.
28. [SPIE 2016] E. Roura, A. Oliver, M. Cabezas, S. Valverde, D. Pareto, J.C. Vilanova, Ll. Ramió-Torrentà, À. Rovira, and X. Lladó. "An SPM12 extension for multiple sclerosis lesion segmentation". SPIE Medical Imaging, San Diego (US), Vol. 9784 97842N-1/N-6 Feb 27- March 3, 2016.
29. [SERAM 2016] M. Cabezas, A. Oliver, X. Lladó, D. Pareto, and A. Rovira. "Analisis del uso de la imagen de sustraccion para detectar nuevas lesiones de T2 en pacientes de esclerosis multiple". 33 Congreso Nacional de la SERAM 2016, Bilbao, Basque Country, May 19-22, 2016.
30. [MS 2015] E. Roura, A. Oliver, M. Cabezas, S. Valverde, D. Pareto, J.C. Vilanova, Ll. Ramió-Torrentà, À. Rovira, and X. Lladó. "A toolbox for segmenting multiple sclerosis lesions using T1w and FLAIR images". Multiple Sclerosis. 21(S11), pp 678. Barcelona. October 2015.
31. [MS 2015] M. Cabezas, A. Oliver, X. Lladó, C. Auger, J. Sastre-Garriga, D. Pareto, X, Montalban, À. Rovira. "A pipeline for detecting new multiple sclerosis lesions on longitudinal brain magnetic resonance imaging". Multiple Sclerosis. 21(S11), pp 179-180.Barcelona. October 2015.
32. [MS 2015] M. Cabezas, J.F. Corral, A. Oliver, X. Lladó, C. Auger, J. Sastre-Garriga, M. Tintore, D. Pareto, X, Montalban, À. Rovira. "Evaluating the sensitivity of subtraction imaging for the detection of new T2 multiple sclerosis lesions when using visual analysis, semiautomatic and automatic approaches". Multiple Sclerosis. 21(S11), pp 175.Barcelona. October 2015.
33. [JEMGI 2015] S. Valverde, A.Oliver, J.Freixenet, M.Cabezas, O. Ganiler, Y. Diez, E. Roura, S. González, X.Lladó. "Passat, present i futur en la quantificació automàtica del teixit cerebral en pacients d'esclerosi múltiple". Ponència invitada a la 5 Jornada d'Esclerosis Múltiple de Girona celebrada a Girona, el 10/07/2015. Ponent: S. Valverde.
34. [JEMGI 2014] A. Oliver, J. Freixenet, M. Cabezas, O. Ganiler, Y. Diez, E. Roura, S. Valverde, X.Lladó. "Neuroimatge en EM: de les noves tecnologies a la capçalera del pacient". Ponència invitada a la I4 Jornada d'Esclerosis Múltiple de Girona celebrada a Pals (Girona), el 4/07/2014. Ponent: A. Oliver.
35. [IDIBGI 2014] S. Valverde, A. Oliver, J. Freixenet, M.Cabezas, O. Ganiler, Y. Diez, E. Roura, S. Valverde, X.Lladó. "Neuroimatge en Esclerosi Múltiple: Anàlisi Automàtic". Ponència invitada a la Jornada Científica de l'IDIBGI de Girona celebrada a Sant Feliu de Guíxols (Girona), el 11/07/2014. Ponent: S. Valverde.
36. [MS 2013] E. Roura, A. Oliver, M. Cabezas, J. Freixenet, X. Lladó, J.C. Vilanova, A. Rovira and Ll. Ramió-Torrentà. "Extracting the brain in axial MR images with an adaptive segmentation technique". Multiple Sclerosis. 19(S1), pp 417-418. Copenhagen, Denmark. 2-5 October 2013.
37. [MS 2013] S.Valverde, A. Oliver, M. Cabezas, Y. Díez, J. Freixenet, X. Lladó, J.C. Vilanova, A. Rovira and Ll. Ramió-Torrentà. "A quantitative study of the effects of White Matter MS Lesions on tissue segmentation methods". Multiple Sclerosis. 19(S1), pp 407-408. Copenhagen, Denmark. 2-5 October 2013.
38. [IbPRIA2013] M. Cabezas, A. Oliver, J. Freixenet and X. Lladó. "A supervised approach for multiple sclerosis lesion segmentation using context features and an outlier map". Iberian Conference on Pattern Recognition and Image Analysis. LNCS, To appear. Madeira, Portugal, 2013.
39. [ECTRIMS 2012] M. Cabezas, A. Oliver, X. Lladó, Y. Díez, J. Freixenet, J.C. Vilanova, A. Quiles, G. Laguillo, Ll. Ramió-Torrentà, D. Pareto, and A. Rovira. "A supervised approach to segment multiple sclerosis lesions using context-rich features and a boosting classifier". European Committee for Treatment and Research in Multiple Sclerosis conference. Multiple Sclerosis, 18(4S), pp 157. Lyon, France. October 2012.
40. [ECTRIMS 2012] Y. Díez, X. Lladó, A. Oliver, R. Martí, E. Roura, M. Cabezas, O. Ganiler, J. Freixenet, J.C. Vilanova, L. Valls, Ll. Ramió-Torrentà, D. Pareto, and A. Rovira. "Registration of serial brain MRI scans from multiple sclerosis patients. Analysis of 3D intensity-based methods". European Committee for Treatment and Research in Multiple Sclerosis conference. Multiple Sclerosis, 18(4S), pp 384-385. Lyon, France. October 2012.
41. [SPIE 2012] G. Pons, J. Martí, R. Martí, M. Cabezas, A. Di Battista and J.A. Noble. "Lesion Segmentation and Bias Correction in Breast Ultrasound B-mode Images Including Elastography Information". SPIE Conference on Medical Imaging, 8314, pp. 83141E1-1E6. San Diego, California, USA, February 2012.
42. [ECTRIMS 2011] X. Lladó, O. Ganiler, A. Oliver, M. Cabezas, J. Freixenet, J.C. Vilanova, L. Valls, Ll. Ramió-Torrentà, and A. Rovira. "Computer-assisted strategies to automated quantification of multiple sclerosis lesion evolution on brain magnetic resonance imaging". European Committee for Treatment and Research in Multiple Sclerosis conference. Multiple Sclerosis, 17(10S), pp 161-162. Amsterdam, Holland, 2011
43. [ECTRIMS 2011] M. Cabezas, M. Bach-Cuadra, A. Oliver, X. Lladó, J. Freixenet, J.C. Vilanova, L. Valls, Ll. Ramió-Torrentà, E. Huerga, D. Pareto, and A. Rovira. "A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging". European Committee for Treatment and Research in Multiple Sclerosis conference. Multiple Sclerosis, 17(10S), pp 381. Amsterdam, Holland, 2011.
44. [ECTRIMS 2010] X. Lladó, M. Cabezas, O. Ganiler, A. Oliver, J. Freixenet, J.C. Vilanova, A. Quiles, Ll. Ramió-Torrenta, A. Rovira. "Strategies for Automated Segmentation of Multiple Sclerosis Lesions on Brain Magnetic Resonance Imaging". European Committee for Treatment and Research in Multiple Sclerosis conference. Multiple Sclerosis, 16(10), pp S256. Gothenburg, Sweden, 2010.

Theses

• [PhDThesis 2013] M. Cabezas. "Atlas-based segmentation of multiple sclerosis lesions in magnetic resonance imaging", PhD thesis. July 2013.
• [MscThesis 2010] M. Cabezas. "Atlas-based segmentation of brain MRI: Application to multiple sclerosis", Master thesis. September 2010.

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