World's Best Scientists 2026 revealed!

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Computer Science

D-Index
37
Citations
4623
World Ranking
10917
National Ranking
38

Overview

Marcelo Gattass is affiliated with the Pontifical Catholic University of Rio de Janeiro in Brazil. Their research spans multiple fields, including Engineering, Computer Science, and Medicine, with a notable focus on areas such as Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, and Ocean Engineering.

Their work encompasses significant topics such as Reservoir Engineering and Simulation Methods, Radiomics and Machine Learning in Medical Imaging, Seismic Imaging and Inversion Techniques, AI in cancer detection, Advanced Neural Network Applications, 3D Shape Modeling and Analysis, and Hydrocarbon exploration and reservoir analysis.

Marcelo Gattass has contributed to several recent papers, demonstrating a focus on medical imaging and computational methods. These papers include:

  • "Kidney segmentation from computed tomography images using deep neural network," 2020, Computers in Biology and Medicine
  • "Breast cancer diagnosis from histopathological images using textural features and CBIR," 2020, Artificial Intelligence in Medicine
  • "Crowd-SLAM: Visual SLAM Towards Crowded Environments using Object Detection," 2021, Journal of Intelligent & Robotic Systems
  • "Kidney tumor segmentation from computed tomography images using DeepLabv3+ 2.5D model," 2021, Expert Systems with Applications
  • "Automatic method for classifying COVID-19 patients based on chest X-ray images, using deep features and PSO-optimized XGBoost," 2021, Expert Systems with Applications

Frequent collaborators with Marcelo Gattass include Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva, João Otávio Bandeira Diniz, Luana Batista da Cruz, and João Dallyson Sousa de Almeida. These coauthors have contributed to several joint publications.

The scientist's research is published mainly in specialized venues that include:

  • Expert Systems with Applications
  • Computers in Biology and Medicine
  • Journal of Intelligent & Robotic Systems
  • Multimedia Tools and Applications
  • Computers & Geosciences

Best Publications

  • Convolutional neural network-based PSO for lung nodule false positive reduction on CT images.

    Giovanni Lucca França da Silva;Thales Levi Azevedo Valente;Aristófanes Corrêa Silva;Anselmo Cardoso de Paiva

  • Detection of masses in mammogram images using CNN, geostatistic functions and SVM

    Wener Borges Sampaio;Edgar Moraes Diniz;Aristófanes Corrêa Silva;Anselmo Cardoso de Paiva

  • TerraLib: Technology in Support of GIS Innovation

    Gilberto Câmara;Ricardo Cartaxo Modesto;Bianca Maria Pedrosa;Lúbia Vinhas

  • Seismic fault detection in real data using transfer learning from a convolutional neural network pre-trained with synthetic seismic data

    Augusto Cunha;Axelle Pochet;Hélio Lopes;Marcelo Gattass

  • Detection of Masses in Digital Mammograms using K-Means and Support Vector Machine

    Leonardo de Oliveira Martins;Geraldo Braz Junior;Aristófanes Correa Silva;Anselmo Cardoso de Paiva

  • Automatic segmentation of lung nodules with growing neural gas and support vector machine

    Stelmo Magalhães Barros Netto;Aristófanes Corrêa Silva;Rodolfo Acatauassú Nunes;Marcelo Gattass

  • Automatic detection of solitary lung nodules using quality threshold clustering, genetic algorithm and diversity index.

    Antonio Oseas de Carvalho Filho;Wener Borges de Sampaio;Aristófanes Corrêa Silva;Anselmo Cardoso de Paiva

  • Automatic detection of small lung nodules in 3D CT data using Gaussian mixture models, Tsallis entropy and SVM

    Alex Martins Santos;Antonio Oseas de Carvalho Filho;Aristófanes Corrêa Silva;Anselmo Cardoso de Paiva

  • Kidney segmentation from computed tomography images using deep neural network.

    Luana Batista da Cruz;José Denes Lima Araújo;Jonnison Lima Ferreira;João Otávio Bandeira Diniz

  • Classification of breast regions as mass and non-mass based on digital mammograms using taxonomic indexes and SVM

    Fernando Soares Sérvulo de Oliveira;Antonio Oseas de Carvalho Filho;Aristófanes Corrêa Silva;Anselmo Cardoso de Paiva

  • Kidney tumor segmentation from computed tomography images using DeepLabv3+ 2.5D model

    Unknown

  • Breast cancer diagnosis from histopathological images using textural features and CBIR.

    Edson Damasceno Carvalho;Antonio Oseas de Carvalho Filho;Romuere R. V. e Silva;Flávio H. D. Araújo

  • Liver segmentation from computed tomography images using cascade deep learning

    Unknown

  • Node and element resequencing using the Laplacian of a finite element graph: Part I—General concepts and algorithm

    Glaucio H. Paulino;Ivan F. M. Menezes;Marcelo Gattass;Subrata Mukherjee

  • Lung nodules diagnosis based on evolutionary convolutional neural network

    Giovanni L. Silva;Otílio P. Silva Neto;Aristófanes C. Silva;Anselmo C. Paiva

  • Seismic Fault Detection Using Convolutional Neural Networks Trained on Synthetic Poststacked Amplitude Maps

    Axelle Pochet;Pedro H. B. Diniz;Helio Lopes;Marcelo Gattass

  • Crowd-SLAM: Visual SLAM Towards Crowded Environments using Object Detection

    João Carlos Virgolino Soares;Marcelo Gattass;Marco Antonio Meggiolaro

  • Convolutional neural network and texture descriptor-based automatic detection and diagnosis of glaucoma

    Marcos Vinícius dos Santos Ferreira;Antonio Oseas de Carvalho Filho;Alcilene Dalília de Sousa;Aristófanes Corrêa Silva

  • Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks

    João Otávio Bandeira Diniz;Pedro Henrique Bandeira Diniz;Thales Levi Azevedo Valente;Aristófanes Corrêa Silva

  • INTERSECTING AND TRIMMING PARAMETRIC MESHES ON FINITE-ELEMENT SHELLS

    Luiz Cristovão G. Coelho;Marcelo Gattass;Luiz Henrique de Figueiredo

  • Classification of patterns of benignity and malignancy based on CT using topology-based phylogenetic diversity index and convolutional neural network

    Antonio Oseas de Carvalho Filho;Aristofanes Corrêa Silva;Anselmo Cardoso de Paiva;Rodolfo Acatauassú Nunes

  • Automatic embryonic stem cells detection and counting method in fluorescence microscopy images

    Geisa M. Faustino;Marcelo Gattass;Stevens Rehen;Carlos J. P. de Lucena

  • Lung nodule classification using artificial crawlers, directional texture and support vector machine

    Bruno Rodrigues Froz;Antonio Oseas de Carvalho Filho;Aristófanes Corrêa Silva;Anselmo Cardoso de Paiva

Frequent Co-Authors

Aristófanes Corrêa Silva
Aristófanes Corrêa Silva Federal University of Maranhão
Glaucio H. Paulino
Glaucio H. Paulino Princeton University
Carlos José Pereira de Lucena
Carlos José Pereira de Lucena Pontifical Catholic University of Rio de Janeiro
Luiz Velho
Luiz Velho Instituto Nacional de Matemática Pura e Aplicada
Stevens K. Rehen
Stevens K. Rehen Federal University of Rio de Janeiro

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