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ORCIDRoberto Souza 0001
Roberto M. Souza 0001 – Roberto Medeiros de Souza
Person information
- affiliation: University of Calgary, Department of Electrical and Software Engineering, Canada
- affiliation: University of Campinas, Faculty of Electrical Engineering and Computing, Brazil
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2020 – today
- 2024
[c32]Peyman Tahghighi, Yunyan Zhang, Roberto Souza, Amin Komeili:
Enhancing New Multiple Sclerosis Lesion Segmentation via Self-supervised Pre-training and Synthetic Lesion Integration. MICCAI (8) 2024: 263-272- [c31]Abbas Omidi, Aida Mohammadshahi, Neha Gianchandani, Regan King, Lara Leijser, Roberto Souza:
Unsupervised Domain Adaptation of MRI Skull-stripping Trained on Adult Data to Newborns. WACV 2024: 7703-7712 - [i12]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 Bento:
Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems. CoRR abs/2408.15550 (2024) - 2023
- [j14]Amin Eslami Abyane
, Derui Zhu, Roberto Souza, Lei Ma, Hadi Hemmati:
Towards understanding quality challenges of the federated learning for neural networks: a first look from the lens of robustness. Empir. Softw. Eng. 28(2): 44 (2023) - [j13]Esmaeil Shakeri, Trafford Crump, Ezekiel Weis, Emad Mohammed, Roberto Souza, Behrouz H. Far:
Explaining Eye Diseases Detected by Machine Learning Using SHAP: A Case Study of Diabetic Retinopathy and Choroidal Nevus. SN Comput. Sci. 4(5): 433 (2023) - [c30]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 - [c29]Neha Gianchandani, Johanna Ospel, M. Ethan MacDonald, Roberto Souza:
A Multitask Deep Learning Model for Voxel-Level Brain Age Estimation. MLMI@MICCAI (2) 2023: 283-292 - [i11]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) - [i10]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) - [i9]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) - [i8]Gabriel Santos Martins Dias, Rodrigo Pommot Berto, Mateus Oliveira, Lucas H. Ueda, Sergio Dertkigil, Paula D. P. Costa, Amirmohammad Shamaei, Roberto Souza, Ashley Harris, Letícia Rittner:
Spectro-ViT: A Vision Transformer Model for GABA-edited MRS Reconstruction Using Spectrograms. CoRR abs/2311.15386 (2023) - [i7]Reza Kakavand, Mehrdad Palizi, Peyman Tahghighi, Reza Ahmadi, Neha Gianchandani, Samer Adeeb, Roberto Souza, W. Brent Edwards, Amin Komeili:
Integration of Swin UNETR and statistical shape modeling for a semi-automated segmentation of the knee and biomechanical modeling of articular cartilage. CoRR abs/2312.00169 (2023) - 2022
- [j12]Alexandre Lopes, Roberto Souza, Hélio Pedrini:
A survey on RGB-D datasets. Comput. Vis. Image Underst. 222: 103489 (2022) - [j11]Parisa Saat, Nikita Nogovitsyn, Muhammad Yusuf Hassan, Muhammad Athar Ganaie, Roberto Souza, Hadi Hemmati:
A domain adaptation benchmark for T1-weighted brain magnetic resonance image segmentation. Frontiers Neuroinformatics 16 (2022) - [c28]Amrit Kumar Jethi, Roberto Souza, Keerthi Ram, Mohanasankar Sivaprakasam:
Improving Fast MRI Reconstructions with Pretext Learning in Low-Data Regime. EMBC 2022: 2080-2083 - [c27]Esmaeil Shakeri, Trafford Crump, Ezekiel Weis, Roberto Souza, Behrouz Homayoun Far:
Using SHAP Analysis to Detect Areas Contributing to Diabetic Retinopathy Detection. IRI 2022: 166-171 - [c26]Esmaeil Shakeri, Anja Slama, Roberto Souza, Behrouz Homayoun Far:
COVID-19 Vaccine Infodemiology using Unsupervised Natural Language Processing. IRI 2022: 178-183 - [c25]Youssef Beauferris, Mike Lasby, Roberto Souza:
Leveraging Multi-Visit Information for Magnetic Resonance Image Reconstruction: Pilot Study on a Cohort of Glioblastoma Subjects. ISBI 2022: 1-5 - [i6]Amin Eslami Abyane, Derui Zhu, Roberto Medeiros de Souza, Lei Ma, Hadi Hemmati:
Towards Understanding Quality Challenges of the Federated Learning: A First Look from the Lens of Robustness. CoRR abs/2201.01409 (2022) - [i5]Alexandre Lopes, Roberto Souza, Hélio Pedrini:
A Survey on RGB-D Datasets. CoRR abs/2201.05761 (2022) - 2020
- [j10]Roberto Souza, Youssef Beauferris, Wallace Loos, Robert Marc Lebel, Richard Frayne:
Enhanced Deep-Learning-Based Magnetic Resonance Image Reconstruction by Leveraging Prior Subject-Specific Brain Imaging: Proof-of-Concept Using a Cohort of Presumed Normal Subjects. IEEE J. Sel. Top. Signal Process. 14(6): 1126-1136 (2020) - [j9]Kevin J. Chung, Roberto Souza, Richard Frayne:
Restoration of Lossy JPEG-Compressed Brain MR Images Using Cross-Domain Neural Networks. IEEE Signal Process. Lett. 27: 141-145 (2020) - [i4]Youssef Beauferris, Jonas Teuwen, Dimitrios Karkalousos, Nikita Moriakov, Matthan W. A. Caan, Lívia Rodrigues, Alexandre Lopes, Hélio Pedrini, Letícia Rittner, Maik Dannecker, Viktor Studenyak, Fabian Gröger, Devendra Vyas, Shahrooz Faghih-Roohi, Amrit Kumar Jethi, JayaChandra Raju, Mohanasankar Sivaprakasam, Wallace Loos, Richard Frayne, Roberto Souza:
Multi-channel MR Reconstruction (MC-MRRec) Challenge - Comparing Accelerated MR Reconstruction Models and Assessing Their Genereralizability to Datasets Collected with Different Coils. CoRR abs/2011.07952 (2020)
2010 – 2019
- 2019
- [j8]Oeslle Lucena, Roberto Souza, Letícia Rittner, Richard Frayne, Roberto de Alencar Lotufo:
Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks. Artif. Intell. Medicine 98: 48-58 (2019) - [j7]Nikita Nogovitsyn, Roberto Souza, Meghan Muller, Amelia Srajer, Stefanie Hassel, Stephen R. Arnott, Andrew D. Davis, Geoffrey B. C. Hall, Jacqueline K. Harris, Mojdeh Zamyadi, Paul D. Metzak, Zahinoor Ismail, Signe L. Bray, Catherine Lebel, Jean M. Addington, Roumen Milev, Kate L. Harkness, Benicio N. Frey, Glenda M. MacQueen:
Testing a deep convolutional neural network for automated hippocampus segmentation in a longitudinal sample of healthy participants. NeuroImage 197: 589-597 (2019) - [c24]Juliana Fontolan, Danilo Pereira, Roberto Souza, Simone Appenzeller, Letícia Rittner:
Improving estimates of brain metabolite concentrations in MR spectroscopic imaging (MRSI) through MRI content. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 109530V - [c23]Mariana P. Bento, Roberto Souza, Marina Salluzzi, Richard Frayne:
Reliability of computer-aided diagnosis tools with multi-center MR datasets: impact of training protocol. Medical Imaging: Computer-Aided Diagnosis 2019: 1095008 - [c22]Roberto Souza, R. Marc Lebel, Richard Frayne:
A Hybrid, Dual Domain, Cascade of Convolutional Neural Networks for Magnetic Resonance Image Reconstruction. MIDL 2019: 437-446 - [c21]Roberto Souza, Oeslle Lucena, Mariana P. Bento, Julia Garrafa, Letícia Rittner, Simone Appenzeller, Roberto de Alencar Lotufo, Richard Frayne:
Brain Extraction Network Trained with "Silver Standard" Data and Fine-Tuned with Manual Annotation for Improved Segmentation. SIBGRAPI 2019: 234-240 - [c20]Roberto Souza, Richard Frayne:
A Hybrid Frequency-Domain/Image-Domain Deep Network for Magnetic Resonance Image Reconstruction. SIBGRAPI 2019: 257-264 - [i3]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
- [j6]Roberto Souza, Oeslle Lucena, Julia Garrafa, David G. Gobbi, Marina Salluzzi, Simone Appenzeller, Letícia Rittner, Richard Frayne, Roberto de Alencar Lotufo:
An open, multi-vendor, multi-field-strength brain MR dataset and analysis of publicly available skull stripping methods agreement. NeuroImage 170: 482-494 (2018) - [c19]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 - [c18]Roberto Souza, Saul C. Leite, Wagner Meira Jr., Eduardo R. Hruschka:
Online Orthogonal Regression Based on a Regularized Squared Loss. ICMLA 2018: 925-930 - [c17]Oeslle Lucena, Roberto Souza, Letícia Rittner, Richard Frayne, Roberto de Alencar Lotufo:
Silver standard masks for data augmentation applied to deep-learning-based skull-stripping. ISBI 2018: 1114-1117 - [c16]Roberto Souza, Oeslle Lucena, Mariana P. Bento, Julia Garrafa, Simone Appenzeller, Letícia Rittner, Roberto de Alencar 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 - [c15]Lívia Rodrigues, Roberto Souza, Letícia Rittner, Richard Frayne, Roberto de Alencar Lotufo:
Common Carotid Artery Lumen Automatic Segmentation from Cine Fast Spin Echo Magnetic Resonance Imaging. SaMBa@MICCAI 2018: 16-24 - [c14]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 - [c13]Roberto Souza:
Detecting Spatial Clusters of Infection Risk with Geo-Located Social Media Data. PhD@VLDB 2018 - [i2]Oeslle Lucena, Roberto Souza, Letícia Rittner, Richard Frayne, Roberto de Alencar Lotufo:
Convolutional Neural Networks for Skull-stripping in Brain MR Imaging using Consensus-based Silver standard Masks. CoRR abs/1804.04988 (2018) - [i1]Roberto Souza, Richard Frayne:
A Hybrid Frequency-domain/Image-domain Deep Network for Magnetic Resonance Image Reconstruction. CoRR abs/1810.12473 (2018) - 2017
- [j5]Pedro Ribeiro Mendes Júnior, Roberto Medeiros de Souza, Rafael de Oliveira Werneck, Bernardo V. Stein, Daniel V. Pazinato, Waldir R. de Almeida, Otávio A. B. Penatti, Ricardo da Silva Torres, Anderson Rocha:
Nearest neighbors distance ratio open-set classifier. Mach. Learn. 106(3): 359-386 (2017) - [j4]Roberto Souza, Letícia Rittner, Rubens Machado, Roberto de Alencar Lotufo:
iamxt: Max-tree toolbox for image processing and analysis. SoftwareX 6: 81-84 (2017) - [c12]Oeslle Lucena, Amadeu Junior, Vitor Moia, Roberto Souza, Eduardo Valle, Roberto de Alencar Lotufo:
Transfer Learning Using Convolutional Neural Networks for Face Anti-spoofing. ICIAR 2017: 27-34 - [c11]Mariana P. Bento, Roberto Medeiros de Souza, Roberto de Alencar Lotufo, Richard Frayne, Letícia Rittner:
WMH Segmentation Challenge: A Texture-Based Classification Approach. BrainLes@MICCAI 2017: 489-500 - [c10]Lívia Rodrigues, Roberto Medeiros de Souza, Letícia Rittner, Richard Frayne, Roberto de Alencar Lotufo:
Common Carotid Artery Lumen Segmentation from Cardiac Cycle-Resolved Cine Fast Spin Echo Magnetic Resonance Imaging. SIBGRAPI 2017: 442-449 - 2016
- [j3]Pedram Ghamisi, Roberto Souza, Jón Atli Benediktsson, Letícia Rittner, Roberto de Alencar Lotufo, Xiao Xiang Zhu:
Hyperspectral Data Classification Using Extended Extinction Profiles. IEEE Geosci. Remote. Sens. Lett. 13(11): 1641-1645 (2016) - [j2]Pedram Ghamisi, Roberto Souza, Jón Atli Benediktsson, Xiao Xiang Zhu, Letícia Rittner, Roberto de Alencar Lotufo:
Extinction Profiles for the Classification of Remote Sensing Data. IEEE Trans. Geosci. Remote. Sens. 54(10): 5631-5645 (2016) - [c9]Pedram Ghamisi, Roberto Souza, Letícia Rittner, Jón Atli Benediktsson, Roberto de Alencar Lotufo, Xiao Xiang Zhu:
Extinction profiles: A novel approach for the analysis of remote sensing data. IGARSS 2016: 5122-5125 - [c8]Roberto Souza, Luis A. Tavares, Letícia Rittner, Roberto de Alencar Lotufo:
An Overview of Max-Tree Principles, Algorithms and Applications. SIBGRAPI Tutorials 2016: 15-23 - [c7]Luis A. Tavares, Roberto M. Souza, Letícia Rittner, Rubens Campos Machado, Roberto de Alencar Lotufo:
A Max-Tree Simplification Proposal and Applications for the Interactive Max-Tree Visualization Tool. SIBGRAPI 2016: 313-320 - [c6]Pedram Ghamisi, Roberto Souza, Jón Atli Benediktsson, Xiao Xiang Zhu, Letícia Rittner, Roberto de Alencar Lotufo:
Extended extinction profile for the classification of hyperspectral images. WHISPERS 2016: 1-4 - 2015
- [c5]Roberto Souza, Letícia Rittner, Roberto de Alencar Lotufo, Rubens Campos Machado:
An array-based node-oriented max-tree representation. ICIP 2015: 3620-3624 - [c4]Luis A. Tavares, Roberto M. Souza, Letícia Rittner, Rubens Campos Machado, Roberto de Alencar Lotufo:
Interactive max-tree visualization tool for image processing and analysis. IPTA 2015: 119-124 - [c3]Roberto Souza, Letícia Rittner, Rubens Campos Machado, Roberto de Alencar Lotufo:
A Comparison Between Extinction Filters and Attribute Filters. ISMM 2015: 63-74 - 2014
- [j1]Roberto Souza, Letícia Rittner, Roberto de Alencar Lotufo:
A comparison between k-Optimum Path Forest and k-Nearest Neighbors supervised classifiers. Pattern Recognit. Lett. 39: 2-10 (2014) - [c2]Roberto Souza, Letícia Rittner, Rubens Campos Machado, Roberto de Alencar Lotufo:
Maximal Max-Tree Simplification. ICPR 2014: 3132-3137 - 2012
- [c1]Roberto Souza, Roberto de Alencar Lotufo, Letícia Rittner:
A Comparison between Optimum-Path Forest and k-Nearest Neighbors Classifiers. SIBGRAPI 2012: 260-267
Coauthor Index
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