A Comparison between Optimum-Path Forest and k-Nearest Neighbors Classifiers. - Roberto Souza 001; Roberto A. Lotufo; Letícia Rittner (SIBGRAPI, 2012)

Maximal Max-Tree Simplification. - Roberto Souza 001; Letícia Rittner; Rubens Campos Machado; Roberto A. Lotufo (ICPR, 2014)

A comparison between k-Optimum Path Forest and k-Nearest Neighbors supervised classifiers. - Roberto Souza 001; Letícia Rittner; Roberto A. Lotufo (Pattern Recognit. Lett., 2014)

An array-based node-oriented max-tree representation. - Roberto Souza 001; Letícia Rittner; Roberto A. Lotufo; Rubens Campos Machado (ICIP, 2015)

Interactive max-tree visualization tool for image processing and analysis. - Luis A. Tavares; Roberto M. Souza 001; Letícia Rittner; Rubens Campos Machado; Roberto A. Lotufo (IPTA, 2015)

A Comparison Between Extinction Filters and Attribute Filters. - Roberto Souza 001; Letícia Rittner; Rubens Campos Machado; Roberto A. Lotufo (ISMM, 2015)

Extinction profiles: A novel approach for the analysis of remote sensing data. - Pedram Ghamisi; Roberto Souza 001; Letícia Rittner; Jón Atli Benediktsson; Roberto A. Lotufo; Xiao Xiang Zhu 001 (IGARSS, 2016)

An Overview of Max-Tree Principles, Algorithms and Applications. - Roberto Souza 001; Luis A. Tavares; Letícia Rittner; Roberto A. Lotufo (SIBGRAPI Tutorials, 2016)

A Max-Tree Simplification Proposal and Applications for the Interactive Max-Tree Visualization Tool. - Luis A. Tavares; Roberto M. Souza 001; Letícia Rittner; Rubens Campos Machado; Roberto A. Lotufo (SIBGRAPI, 2016)

Extended extinction profile for the classification of hyperspectral images. - Pedram Ghamisi; Roberto Souza 001; Jón Atli Benediktsson; Xiao Xiang Zhu 001; Letícia Rittner; Roberto A. Lotufo (WHISPERS, 2016)

Hyperspectral Data Classification Using Extended Extinction Profiles. - Pedram Ghamisi; Roberto Souza 001; Jón Atli Benediktsson; Letícia Rittner; Roberto A. Lotufo; Xiao Xiang Zhu 001 (IEEE Geosci. Remote. Sens. Lett., 2016)

Extinction Profiles for the Classification of Remote Sensing Data. - Pedram Ghamisi; Roberto Souza 001; Jón Atli Benediktsson; Xiao Xiang Zhu 001; Letícia Rittner; Roberto A. Lotufo (IEEE Trans. Geosci. Remote. Sens., 2016)

Transfer Learning Using Convolutional Neural Networks for Face Anti-spoofing. - Oeslle Lucena; Amadeu Junior; Vitor Moia; Roberto Souza 001; Eduardo Valle; Roberto A. Lotufo (ICIAR, 2017)

WMH Segmentation Challenge: A Texture-Based Classification Approach. - Mariana P. Bento; Roberto Medeiros de Souza; Roberto A. Lotufo; Richard Frayne; Letícia Rittner (BrainLes@MICCAI, 2017)

Common Carotid Artery Lumen Segmentation from Cardiac Cycle-Resolved Cine Fast Spin Echo Magnetic Resonance Imaging. - Lívia Rodrigues 001; Roberto Medeiros de Souza; Letícia Rittner; Richard Frayne; Roberto de Alencar Lotufo (SIBGRAPI, 2017)

Nearest neighbors distance ratio open-set classifier. - 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 001 (Mach. Learn., 2017)

iamxt: Max-tree toolbox for image processing and analysis. - Roberto Souza 001; Letícia Rittner; Rubens Machado; Roberto A. Lotufo (SoftwareX, 2017)

Normal Brain Aging: Prediction of Age, Sex and White Matter Hyperintensities Using a MR Image-Based Machine Learning Technique. - Mariana P. Bento; Roberto Souza 001; Marina Salluzzi; Richard Frayne (ICIAR, 2018)

Online Orthogonal Regression Based on a Regularized Squared Loss. - Roberto Souza 001; Saul C. Leite; Wagner Meira Jr.; Eduardo R. Hruschka (ICMLA, 2018)

Silver standard masks for data augmentation applied to deep-learning-based skull-stripping. - Oeslle Lucena; Roberto Souza 001; Letícia Rittner; Richard Frayne; Roberto A. Lotufo (ISBI, 2018)

Reliability of using single specialist annotation for designing and evaluating automatic segmentation methods: A skull stripping case study. - Roberto Souza 001; Oeslle Lucena; Mariana P. Bento; Julia Garrafa; Simone Appenzeller; Letícia Rittner; Roberto A. Lotufo; Richard Frayne (ISBI, 2018)

Common Carotid Artery Lumen Automatic Segmentation from Cine Fast Spin Echo Magnetic Resonance Imaging. - Lívia Rodrigues 001; Roberto Souza 001; Letícia Rittner; Richard Frayne; Roberto A. Lotufo (SaMBa@MICCAI, 2018)

Multicenter Imaging Studies: Automated Approach to Evaluating Data Variability and the Role of Outliers. - Mariana P. Bento; Roberto Souza 001; Richard Frayne (SIBGRAPI, 2018)

Detecting Spatial Clusters of Infection Risk with Geo-Located Social Media Data. - Roberto Souza 001 (PhD@VLDB, 2018)

Convolutional Neural Networks for Skull-stripping in Brain MR Imaging using Consensus-based Silver standard Masks. - Oeslle Lucena; Roberto Souza 001; Letícia Rittner; Richard Frayne; Roberto A. Lotufo (CoRR, 2018)

An open, multi-vendor, multi-field-strength brain MR dataset and analysis of publicly available skull stripping methods agreement. - Roberto Souza 001; Oeslle Lucena; Julia Garrafa; David G. Gobbi; Marina Salluzzi; Simone Appenzeller; Letícia Rittner; Richard Frayne; Roberto A. Lotufo (NeuroImage, 2018)

Improving estimates of brain metabolite concentrations in MR spectroscopic imaging (MRSI) through MRI content. - Juliana Fontolan; Danilo Pereira; Roberto Souza 001; Simone Appenzeller; Letícia Rittner (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Reliability of computer-aided diagnosis tools with multi-center MR datasets: impact of training protocol. - Mariana P. Bento; Roberto Souza 001; Marina Salluzzi; Richard Frayne (Computer-Aided Diagnosis, 2019)

A Hybrid, Dual Domain, Cascade of Convolutional Neural Networks for Magnetic Resonance Image Reconstruction. - Roberto Souza 001; R. Marc Lebel; Richard Frayne (MIDL, 2019)

A Hybrid Frequency-Domain/Image-Domain Deep Network for Magnetic Resonance Image Reconstruction. - Roberto Souza 001; Richard Frayne (SIBGRAPI, 2019)

Brain Extraction Network Trained with "Silver Standard" Data and Fine-Tuned with Manual Annotation for Improved Segmentation. - Roberto Souza 001; Oeslle Lucena; Mariana P. Bento; Julia Garrafa; Letícia Rittner; Simone Appenzeller; Roberto A. Lotufo; Richard Frayne (SIBGRAPI, 2019)

Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks. - Oeslle Lucena; Roberto Souza 001; Letícia Rittner; Richard Frayne; Roberto A. Lotufo (Artif. Intell. Medicine, 2019)

Dual-domain Cascade of U-nets for Multi-channel Magnetic Resonance Image Reconstruction. - Roberto Souza 001; Mariana P. Bento; Nikita Nogovitsyn; Kevin J. Chung; R. Marc Lebel; Richard Frayne (CoRR, 2019)

Testing a deep convolutional neural network for automated hippocampus segmentation in a longitudinal sample of healthy participants. - Nikita Nogovitsyn; Roberto Souza 001; 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; et al. (NeuroImage, 2019)

Multi-channel MR Reconstruction (MC-MRRec) Challenge - Comparing Accelerated MR Reconstruction Models and Assessing Their Genereralizability to Datasets Collected with Different Coils. - Youssef Beauferris; Jonas Teuwen; Dimitrios Karkalousos; Nikita Moriakov; Matthan W. A. Caan; Lívia Rodrigues 001; Alexandre Lopes; Hélio Pedrini; Letícia Rittner; Maik Dannecker; Viktor Studenyak; Fabian Gröger; et al. (CoRR, 2020)

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. - Roberto Souza 001; Youssef Beauferris; Wallace Loos; Robert Marc Lebel; Richard Frayne (IEEE J. Sel. Top. Signal Process., 2020)

Restoration of Lossy JPEG-Compressed Brain MR Images Using Cross-Domain Neural Networks. - Kevin J. Chung; Roberto Souza 001; Richard Frayne (IEEE Signal Process. Lett., 2020)

Improving Fast MRI Reconstructions with Pretext Learning in Low-Data Regime. - Amrit Kumar Jethi; Roberto Souza 001; Keerthi Ram; Mohanasankar Sivaprakasam (EMBC, 2022)

Using SHAP Analysis to Detect Areas Contributing to Diabetic Retinopathy Detection. - Esmaeil Shakeri; Trafford Crump; Ezekiel Weis; Roberto Souza 001; Behrouz Homayoun Far (IRI, 2022)

COVID-19 Vaccine Infodemiology using Unsupervised Natural Language Processing. - Esmaeil Shakeri; Anja Slama; Roberto Souza 001; Behrouz Homayoun Far (IRI, 2022)

Leveraging Multi-Visit Information for Magnetic Resonance Image Reconstruction: Pilot Study on a Cohort of Glioblastoma Subjects. - Youssef Beauferris; Mike Lasby; Roberto Souza 001 (ISBI, 2022)

Towards Understanding Quality Challenges of the Federated Learning: A First Look from the Lens of Robustness. - Amin Eslami Abyane; Derui Zhu; Roberto Medeiros de Souza; Lei Ma 003; Hadi Hemmati (CoRR, 2022)

A survey on RGB-D datasets. - Alexandre Lopes; Roberto Souza 001; Hélio Pedrini (Comput. Vis. Image Underst., 2022)

A domain adaptation benchmark for T1-weighted brain magnetic resonance image segmentation. - Parisa Saat; Nikita Nogovitsyn; Muhammad Yusuf Hassan; Muhammad Athar Ganaie; Roberto Souza 001; Hadi Hemmati (Frontiers Neuroinformatics, 2022)

Studying the Effects of Sex-Related Differences on Brain Age Prediction Using Brain MR Imaging. - Mahsa Dibaji; Neha Gianchandani; Akhil Nair; Mansi Singhal; Roberto Souza 001; Mariana P. Bento (CLIP/FAIMI/EPIMI@MICCAI, 2023)

A Multitask Deep Learning Model for Voxel-Level Brain Age Estimation. - Neha Gianchandani; Johanna Ospel; M. Ethan MacDonald; Roberto Souza 001 (MLMI@MICCAI (2), 2023)

Reframing the Brain Age Prediction Problem to a More Interpretable and Quantitative Approach. - Neha Gianchandani; Mahsa Dibaji; Mariana P. Bento; M. Ethan MacDonald; Roberto Souza 001 (CoRR, 2023)

A voxel-level approach to brain age prediction: A method to assess regional brain aging. - Neha Gianchandani; Mahsa Dibaji; Johanna Ospel; Fernando Vega; Mariana P. Bento; M. Ethan MacDonald; Roberto Souza 001 (CoRR, 2023)

Spectro-ViT: A Vision Transformer Model for GABA-edited MRS Reconstruction Using Spectrograms. - Gabriel Santos Martins Dias; Rodrigo Pommot Berto; Mateus Oliveira; Lucas H. Ueda; Sergio Dertkigil; Paula D. P. Costa; Amirmohammad Shamaei; Roberto Souza 001; Ashley D. Harris; Letícia Rittner (CoRR, 2023)

Integration of Swin UNETR and statistical shape modeling for a semi-automated segmentation of the knee and biomechanical modeling of articular cartilage. - Reza Kakavand; Mehrdad Palizi; Peyman Tahghighi; Reza Ahmadi; Neha Gianchandani; Samer Adeeb; Roberto Souza 001; W. Brent Edwards; Amin Komeili (CoRR, 2023)

Towards understanding quality challenges of the federated learning for neural networks: a first look from the lens of robustness. - Amin Eslami Abyane; Derui Zhu; Roberto Souza 001; Lei Ma 003; Hadi Hemmati (Empir. Softw. Eng., 2023)

Explaining Eye Diseases Detected by Machine Learning Using SHAP: A Case Study of Diabetic Retinopathy and Choroidal Nevus. - Esmaeil Shakeri; Trafford Crump; Ezekiel Weis; Emad Mohammed 001; Roberto Souza 001; Behrouz H. Far (SN Comput. Sci., 2023)

UNET and UNETR Based Frameworks for Predicting the Short-Term Spatiotemporal Demand of E-Scooter Sharing Services. - Mohammad Sahnoon; Aaron Manuel; Merkebe Getachew Demissie; Roberto Souza 001 (ITSC, 2024)

Enhancing New Multiple Sclerosis Lesion Segmentation via Self-supervised Pre-training and Synthetic Lesion Integration. - Peyman Tahghighi; Yunyan Zhang; Roberto Souza 001; Amin Komeili (MICCAI (8), 2024)

Unsupervised Domain Adaptation of Brain MRI Skull Stripping Trained on Adult Data to Newborns: Combining Synthetic Data with Domain Invariant Features. - Abbas Omidi; Amirmohammad Shamaei; Anouk Verschuu; Regan King; Lara Leijser; Roberto Souza 001 (MIDL, 2024)

Unsupervised Domain Adaptation of MRI Skull-stripping Trained on Adult Data to Newborns. - Abbas Omidi; Aida Mohammadshahi; Neha Gianchandani; Regan King; Lara Leijser; Roberto Souza 001 (WACV, 2024)

Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems. - 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 D. Harris; et al. (CoRR, 2024)

Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems. - 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 D. Harris; et al. (CoRR, 2024)

Sex differences in brain MRI using deep learning toward fairer healthcare outcomes. - Mahsa Dibaji; Johanna Ospel; Roberto Souza 001; Mariana P. Bento (Frontiers Comput. Neurosci., 2024)

Accelerating Water Removal in MRSI Using Domain Knowledge-Based Deep Learning. - Amir Buchali; Roberto Souza 001; Stanislav Motyka; Eva Niess; Bernhard Strasser; Wolfgang Bogner; Amirmohammed Shamaei (ISBI, 2025)

Generalize or Specialize? The Effect of Coil Combining in Deep Learning Based MR Image Reconstruction. - Natalia Dubljevic; Richard Frayne; Roberto Souza 001 (ISBI, 2025)

Quantifying White Matter Hyperintensities: Predicting Periventricular Fazekas Scores with Uncertainty Estimation. - Susanne Schmid; Amirmohammad Shamaei; Roberto Souza 001; Richard Frayne (ISBI, 2025)

Automated quantitative analysis of peri-articular bone microarchitecture in HR-pQCT knee images. - Nathan Neeteson; Sasha M. Hasick; Roberto Souza 001; Steven K. Boyd (Comput. Methods Programs Biomed., 2025)

Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems. - 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 D. Harris; et al. (Trans. Mach. Learn. Res., 2025)

Enhancing and Accelerating Brain MRI through Deep Learning Reconstruction Using Prior Subject-Specific Imaging. - Amirmohammad Shamaei; Alexander Stebner; Salome Bosshart; Johanna Ospel; Gouri Ginde; Mariana P. Bento; Roberto Souza 001 (CoRR, 2025)