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Mariana P. Bento
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2020 – today
- 2024
- [j7]Mahsa Dibaji, Johanna Ospel, Roberto Souza, Mariana P. Bento:
Sex differences in brain MRI using deep learning toward fairer healthcare outcomes. Frontiers Comput. Neurosci. 18 (2024) - [j6]Kauê T. N. Duarte, Abhijot S. Sidhu, Murilo Costa de Barros, David G. Gobbi, Cheryl R. McCreary, Feryal Saad, Richard Camicioli, Eric E. Smith, Mariana P. Bento, Richard Frayne:
Multi-stage semi-supervised learning enhances white matter hyperintensity segmentation. Frontiers Comput. Neurosci. 18 (2024) - [i6]Farzaneh Dehghani, Mahsa Dibaji, Fahim Anzum, Lily Dey, Alican Basdemir, Sayeh Bayat, Jean-Christophe Boucher, Steve Drew, Sarah Elaine Eaton, Richard Frayne, Gouri Ginde, Ashley Harris, Yani Ioannou, Catherine Lebel, John Lysack, Leslie Salgado Arzuaga, Emma Stanley, Roberto Souza, Ronnie Souza, Lana Wells, Tyler Williamson, Matthias Wilms, Zaman Wahid, Mark Ungrin, Marina Gavrilova, Mariana P. Bento:
Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems. CoRR abs/2408.15550 (2024) - 2023
- [c13]Mahsa Dibaji, Neha Gianchandani, Akhil Nair, Mansi Singhal, Roberto Souza, Mariana P. Bento:
Studying the Effects of Sex-Related Differences on Brain Age Prediction Using Brain MR Imaging. CLIP/FAIMI/EPIMI@MICCAI 2023: 205-214 - [i5]Neha Gianchandani, Mahsa Dibaji, Mariana P. Bento, M. Ethan MacDonald, Roberto Souza:
Reframing the Brain Age Prediction Problem to a More Interpretable and Quantitative Approach. CoRR abs/2308.12416 (2023) - [i4]Neha Gianchandani, Mahsa Dibaji, Johanna Ospel, Fernando Vega, Mariana P. Bento, M. Ethan MacDonald, Roberto Souza:
A voxel-level approach to brain age prediction: A method to assess regional brain aging. CoRR abs/2310.11385 (2023) - [i3]Mahsa Dibaji, Neha Gianchandani, Akhil Nair, Mansi Singhal, Roberto Souza, Mariana P. Bento:
Studying the Effects of Sex-related Differences on Brain Age Prediction using brain MR Imaging. CoRR abs/2310.11577 (2023) - 2022
- [c12]William J. Herrera, Simone Appenzeller, Fabiano Reis, Danilo Pereira, Mariana P. Bento, Letícia Rittner:
Automated quality check of corpus callosum segmentation using deep learning. Image Processing 2022 - 2021
- [j5]Irene Fantini, Clarissa L. Yasuda, Mariana P. Bento, Letícia Rittner, Fernando Cendes, Roberto A. Lotufo:
Automatic MR image quality evaluation using a Deep CNN: A reference-free method to rate motion artifacts in neuroimaging. Comput. Medical Imaging Graph. 90: 101897 (2021) - [j4]Mariana P. Bento, Irene Fantini, Justin Park, Letícia Rittner, Richard Frayne:
Deep Learning in Large and Multi-Site Structural Brain MR Imaging Datasets. Frontiers Neuroinformatics 15: 805669 (2021)
2010 – 2019
- 2019
- [j3]Hugo J. Kuijf, Adrià Casamitjana, D. Louis Collins, Mahsa Dadar, Achilleas Georgiou, Mohsen Ghafoorian, Dakai Jin, April Khademi, Jesse Knight, Hongwei Li, Xavier Lladó, J. Matthijs Biesbroek, Miguel Luna, Qaiser Mahmood, Richard McKinley, Alireza Mehrtash, Sébastien Ourselin, Bo-yong Park, Hyunjin Park, Sang Hyun Park, Simon Pezold, Élodie Puybareau, Jeroen de Bresser, Letícia Rittner, Carole H. Sudre, Sergi Valverde, Verónica Vilaplana, Roland Wiest, Yongchao Xu, Ziyue Xu, Guodong Zeng, Jianguo Zhang, Guoyan Zheng, Rutger Heinen, Christopher Chen, Wiesje M. van der Flier, Frederik Barkhof, Max A. Viergever, Geert Jan Biessels, Simon Andermatt, Mariana P. Bento, Matt Berseth, Mikhail Belyaev, M. Jorge Cardoso:
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge. IEEE Trans. Medical Imaging 38(11): 2556-2568 (2019) - [c11]Mariana P. Bento, Roberto Souza, Marina Salluzzi, Richard Frayne:
Reliability of computer-aided diagnosis tools with multi-center MR datasets: impact of training protocol. Computer-Aided Diagnosis 2019: 1095008 - [c10]Roberto Souza, Oeslle Lucena, Mariana P. Bento, Julia Garrafa, Letícia Rittner, Simone Appenzeller, Roberto A. Lotufo, Richard Frayne:
Brain Extraction Network Trained with "Silver Standard" Data and Fine-Tuned with Manual Annotation for Improved Segmentation. SIBGRAPI 2019: 234-240 - [i2]Hugo J. Kuijf, J. Matthijs Biesbroek, Jeroen de Bresser, Rutger Heinen, Simon Andermatt, Mariana P. Bento, Matt Berseth, Mikhail Belyaev, M. Jorge Cardoso, Adrià Casamitjana, D. Louis Collins, Mahsa Dadar, Achilleas Georgiou, Mohsen Ghafoorian, Dakai Jin, April Khademi, Jesse Knight, Hongwei Li, Xavier Lladó, Miguel Luna, Qaiser Mahmood, Richard McKinley, Alireza Mehrtash, Sébastien Ourselin, Bo-yong Park, Hyunjin Park, Sang Hyun Park, Simon Pezold, Élodie Puybareau, Letícia Rittner, Carole H. Sudre, Sergi Valverde, Verónica Vilaplana, Roland Wiest, Yongchao Xu, Ziyue Xu, Guodong Zeng, Jianguo Zhang, Guoyan Zheng, Christopher Chen, Wiesje M. van der Flier, Frederik Barkhof, Max A. Viergever, Geert Jan Biessels:
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge. CoRR abs/1904.00682 (2019) - [i1]Roberto Souza, Mariana P. Bento, Nikita Nogovitsyn, Kevin J. Chung, R. Marc Lebel, Richard Frayne:
Dual-domain Cascade of U-nets for Multi-channel Magnetic Resonance Image Reconstruction. CoRR abs/1911.01458 (2019) - 2018
- [j2]Giovana Cover, William Garcia Herrera, Mariana P. Bento, Simone Appenzeller, Letícia Rittner:
Computational methods for corpus callosum segmentation on MRI: A systematic literature review. Comput. Methods Programs Biomed. 154: 25-35 (2018) - [c9]Mariana P. Bento, Roberto Souza, Marina Salluzzi, Richard Frayne:
Normal Brain Aging: Prediction of Age, Sex and White Matter Hyperintensities Using a MR Image-Based Machine Learning Technique. ICIAR 2018: 538-545 - [c8]Roberto Souza, Oeslle Lucena, Mariana P. Bento, Julia Garrafa, Simone Appenzeller, Letícia Rittner, Roberto A. Lotufo, Richard Frayne:
Reliability of using single specialist annotation for designing and evaluating automatic segmentation methods: A skull stripping case study. ISBI 2018: 1344-1347 - [c7]Gustavo R. Pinheiro, Giovana S. Cover, Mariana P. Bento, Letícia Rittner:
Automatic callosal fiber convergence plane computation through DTI-based divergence map. Biomedical Applications in Molecular, Structural, and Functional Imaging 2018: 1057815 - [c6]Gustavo Retuci Pinheiro, Raphael Voltoline, Mariana P. Bento, Letícia Rittner:
V-Net and U-Net for Ischemic Stroke Lesion Segmentation in a Small Dataset of Perfusion Data. BrainLes@MICCAI (1) 2018: 301-309 - [c5]Mariana P. Bento, Roberto Souza, Richard Frayne:
Multicenter Imaging Studies: Automated Approach to Evaluating Data Variability and the Role of Outliers. SIBGRAPI 2018: 182-188 - 2017
- [j1]Giovana Cover, Mariana Pereira, Mariana P. Bento, Simone Appenzeller, Letícia Rittner:
Data-Driven Corpus Callosum Parcellation Method Through Diffusion Tensor Imaging. IEEE Access 5: 22421-22432 (2017) - [c4]Mariana P. Bento, Yan Sym, Richard Frayne, Roberto A. Lotufo, Letícia Rittner:
Probabilistic Segmentation of Brain White Matter Lesions Using Texture-Based Classification. ICIAR 2017: 71-78 - [c3]Mariana P. Bento, Roberto Medeiros de Souza, Roberto A. Lotufo, Richard Frayne, Letícia Rittner:
WMH Segmentation Challenge: A Texture-Based Classification Approach. BrainLes@MICCAI 2017: 489-500 - 2013
- [c2]Mariana P. Bento, Letícia Rittner, Simone Appenzeller, Aline Lapa, Roberto A. Lotufo:
Analysis of brain white matter hyperintensities using pattern recognition techniques. Image Processing 2013: 86693P - 2011
- [c1]Letícia Rittner, André Vital Saúde, Alexandre Gonçalves Silva, Rubens Campos Machado, Mariana P. Bento, Roberto A. Lotufo:
Adessowiki: Collaborative Scientific Programming Environment. SIBGRAPI Tutorials 2011: 56-62
Coauthor Index
aka: Roberto Medeiros de Souza
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