Publications
Here you'll find a list of selected publications (last four years). The complete list of publications is available at my Lattes CV.
Other available sources are Google Scholar and ResearchGate.
CALDEIRA, T.; JULIO, P.; APPENZELLER, S; RITTNER, L. inCCsight: A software for exploration and visualization of DT-MRI data of the Corpus Callosum. Computers & Graphics, 99, 259-271, 2021.
CARMO, D.; CAMPIOTI, I.; RODRIGUES, L.; FANTINI, I.; PINHEIRO, G.; MORAES, D.; RITTNER, L.; LOTUFO, R. Rapidly deploying a COVID-19 decision support system in one of the largest Brazilian hospitals. Health Informatics Journal, 27(3), 14604582211033017, 2021.
FANTINI, I.; YASUDA, C.; BENTO, M.; RITTNER, L.; CENDES, F.; LOTUFO, R. Automatic MR image quality evaluation using a Deep CNN: A reference-free method to rate motion artifacts in neuroimaging. Computerized Medical Imaging and Graphics, 101897, 2021.
CARMO, D.; SILVA, B.; YASUDA, C.; RITTNER L.; LOTUFO, R. Alzheimer's Disease Neuroimaging Initiative. Hippocampus segmentation on epilepsy and Alzheimer's disease studies with multiple convolutional neural networks. Heliyon, 7(2), e06226, 2021.
FRITTOLI, R.; PEREIRA, D.; RITTNER, L.; APPENZELLER, S. Proton magnetic resonance spectroscopy (1H-MRS) in rheumatic autoimmune diseases: A systematic review. Lupus, p.0961203320961466, 2020.
HERRERA, W.; PEREIRA, M.; BENTO, M.; LAPA, A.; APPENZELLER, S.; RITTNER, L. A framework for quality control of corpus callosum segmentation in large-scale studies. Journal of Neuroscience Methods, v. 334, p. 108593, 2020.
LUCENA, O.; SOUZA, R.; RITTNER, L.; FRAYNE, R.; LOTUFO, R. Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks, Artificial Intelligence in Medicine, v. 98, 2019, pp 48-58.
KUIJF, H.; BIESBROEK, J.; BRESSER, J.; HEINEN, R.; ANDERMATT, S.; ..., RITTNER, L.; ..., VIERGEVER, M.; BIESSELS, G. Standardized assessment of automatic segmentation of white matter hyperintensities; results of the WMH segmentation challenge. IEEE transactions on medical imaging, 2019.
FONTOLAN, J.; PEREIRA, D.; SOUZA, R.; APPENZELLER, S.; RITTNER L. (2019, March). Improving estimates of brain metabolite concentrations in MR spectroscopic imaging (MRSI) through MRI content. In Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging , 2019. v. 10953, pp. 109530V.
CARMO, D.; SILVA, B.; YASUDA, C.; RITTNER, L.; LOTUFO, R.A. Extended 2D Volumetric Consensus Hippocampus Segmentation. arXiv preprint arXiv:1902.0448. 2018
PINHEIRO, G.R.; VOLTOLINE, R.; BENTO, M.; RITTNER, L. V-Net and U-Net for Ischemic Stroke Lesion Segmentation in a Small Dataset of Perfusion Data. In International MICCAI Brainlesion Workshop, 2018. pp. 301-309.
FANTINI, I.; RITTNER, L.; YASUDA, C.; LOTUFO, R. Automatic detection of motion artifacts on MRI using Deep CNN. In 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI) , 2018.
SOUZA, R.; LUCENA, O.; GARRAFA, J.; GOBBI, D.; SALUZZI, M., APPENZELLER, S.; RITTNER, L. ; FRAYNE, R.; LOTUFO, R.A. An open, multi-vendor, multi-field-strength brain MR dataset and analysis of publicly available skull stripping methods agreement. NeuroImage, 2018. v.170, pp. 482-494.
LUCENA, O.; SOUZA, R.; RITTNER, L.; FRAYNE, R.; LOTUFO, R. Convolutional Neural Networks for Skull-stripping in Brain MR Imaging using Consensus-based Silver standard Masks. arXiv preprint arXiv:1804.04988. 2018.
ISHII, F.T.; FLORES, F.C.; RITTNER, L. Tensorial Lucas-Kanade: An Optical Flow Estimator Based on Tensorial Color Representation and Tensorial Algebra. In: 2018 IEEE Symposium on Computers and Communications (ISCC), 2018. p. 00633-00639.
SOUZA, R.; LUCENA, O.; Bento, M., GARRAFA, J.; APPENZELLER, S.; RITTNER, L. ; LOTUFO, R.A.; FRAYNE, R. Reliability of using single specialist annotation for designing and evaluating automatic segmentation methods: A skull stripping case study. In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) , 2018. pp. 1344-1347.
LUCENA, O.; SOUZA, R.; RITTNER, L. ; FRAYNE, R.; LOTUFO, R.A.. Silver standard masks for data augmentation applied to deep-learning-based skull-stripping. In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) , 2018. pp. 1114-1117.
BOMBINI, M.F.; PERES, F.A.; LAPA, A.T.; SINICATO, N.A.; QUENTAL, B.; PINCELLI, A.S.M.; AMARAL, T.N.; GOMES, C.C.; RIO, A.P.; MARQUES-NETO, J.F.; COSTALLAT, L.T.L.; FERNANDES, P.T.; CENDES, F.; RITTNER, L.; APPENZELLER, S. Olfactory function in systemic lupus erythematosus and systemic sclerosis. A longitudinal study and review of the literature. Autoimmunity reviews, 2018. 17(4), 405-412.
COVER, G.S.; HERRERA, W.G.; BENTO, M.P.; APPENZELLER, S.; RITTNER, L. Computational methods for corpus callosum segmentation on MRI: A systematic literature review. Computer methods and programs in biomedicine, 2018. v.154, 25-35.
COSTALLAT, B.L.; FERREIRA, D.M.; LAPA, A.T.; RITTNER, L.; COSTALLAT, L.T.L.; APPENZELLER, S. Brain diffusion tensor MRI in systematic lupus erythematosus: A systematic review. Autoimmunity reviews, 2018. 17(1), 36-43.
PINHEIRO, G.R.; COVER, G.S.; BENTO, M.P.; RITTNER, L. Automatic callosal fiber convergence plane computation through DTI-based divergence map. In Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2018. Vol. 10578, p. 1057815.
PEREIRA, M.; COVER, G.; APPENZELLER, S.; RITTNER, L. Corpus callosum parcellation methods: a quantitative comparative study. In Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2018. Vol. 10578, p. 1057817.
Here you'll find a list of selected publications (last four years). The complete list of publications is available at my Lattes CV.
Other available sources are Google Scholar and ResearchGate.
CALDEIRA, T.; JULIO, P.; APPENZELLER, S; RITTNER, L. inCCsight: A software for exploration and visualization of DT-MRI data of the Corpus Callosum. Computers & Graphics, 99, 259-271, 2021.
CARMO, D.; CAMPIOTI, I.; RODRIGUES, L.; FANTINI, I.; PINHEIRO, G.; MORAES, D.; RITTNER, L.; LOTUFO, R. Rapidly deploying a COVID-19 decision support system in one of the largest Brazilian hospitals. Health Informatics Journal, 27(3), 14604582211033017, 2021.
FANTINI, I.; YASUDA, C.; BENTO, M.; RITTNER, L.; CENDES, F.; LOTUFO, R. Automatic MR image quality evaluation using a Deep CNN: A reference-free method to rate motion artifacts in neuroimaging. Computerized Medical Imaging and Graphics, 101897, 2021.
CARMO, D.; SILVA, B.; YASUDA, C.; RITTNER L.; LOTUFO, R. Alzheimer's Disease Neuroimaging Initiative. Hippocampus segmentation on epilepsy and Alzheimer's disease studies with multiple convolutional neural networks. Heliyon, 7(2), e06226, 2021.
FRITTOLI, R.; PEREIRA, D.; RITTNER, L.; APPENZELLER, S. Proton magnetic resonance spectroscopy (1H-MRS) in rheumatic autoimmune diseases: A systematic review. Lupus, p.0961203320961466, 2020.
HERRERA, W.; PEREIRA, M.; BENTO, M.; LAPA, A.; APPENZELLER, S.; RITTNER, L. A framework for quality control of corpus callosum segmentation in large-scale studies. Journal of Neuroscience Methods, v. 334, p. 108593, 2020.
LUCENA, O.; SOUZA, R.; RITTNER, L.; FRAYNE, R.; LOTUFO, R. Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks, Artificial Intelligence in Medicine, v. 98, 2019, pp 48-58.
KUIJF, H.; BIESBROEK, J.; BRESSER, J.; HEINEN, R.; ANDERMATT, S.; ..., RITTNER, L.; ..., VIERGEVER, M.; BIESSELS, G. Standardized assessment of automatic segmentation of white matter hyperintensities; results of the WMH segmentation challenge. IEEE transactions on medical imaging, 2019.
FONTOLAN, J.; PEREIRA, D.; SOUZA, R.; APPENZELLER, S.; RITTNER L. (2019, March). Improving estimates of brain metabolite concentrations in MR spectroscopic imaging (MRSI) through MRI content. In Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging , 2019. v. 10953, pp. 109530V.
CARMO, D.; SILVA, B.; YASUDA, C.; RITTNER, L.; LOTUFO, R.A. Extended 2D Volumetric Consensus Hippocampus Segmentation. arXiv preprint arXiv:1902.0448. 2018
PINHEIRO, G.R.; VOLTOLINE, R.; BENTO, M.; RITTNER, L. V-Net and U-Net for Ischemic Stroke Lesion Segmentation in a Small Dataset of Perfusion Data. In International MICCAI Brainlesion Workshop, 2018. pp. 301-309.
FANTINI, I.; RITTNER, L.; YASUDA, C.; LOTUFO, R. Automatic detection of motion artifacts on MRI using Deep CNN. In 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI) , 2018.
SOUZA, R.; LUCENA, O.; GARRAFA, J.; GOBBI, D.; SALUZZI, M., APPENZELLER, S.; RITTNER, L. ; FRAYNE, R.; LOTUFO, R.A. An open, multi-vendor, multi-field-strength brain MR dataset and analysis of publicly available skull stripping methods agreement. NeuroImage, 2018. v.170, pp. 482-494.
LUCENA, O.; SOUZA, R.; RITTNER, L.; FRAYNE, R.; LOTUFO, R. Convolutional Neural Networks for Skull-stripping in Brain MR Imaging using Consensus-based Silver standard Masks. arXiv preprint arXiv:1804.04988. 2018.
ISHII, F.T.; FLORES, F.C.; RITTNER, L. Tensorial Lucas-Kanade: An Optical Flow Estimator Based on Tensorial Color Representation and Tensorial Algebra. In: 2018 IEEE Symposium on Computers and Communications (ISCC), 2018. p. 00633-00639.
SOUZA, R.; LUCENA, O.; Bento, M., GARRAFA, J.; APPENZELLER, S.; RITTNER, L. ; LOTUFO, R.A.; FRAYNE, R. Reliability of using single specialist annotation for designing and evaluating automatic segmentation methods: A skull stripping case study. In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) , 2018. pp. 1344-1347.
LUCENA, O.; SOUZA, R.; RITTNER, L. ; FRAYNE, R.; LOTUFO, R.A.. Silver standard masks for data augmentation applied to deep-learning-based skull-stripping. In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) , 2018. pp. 1114-1117.
BOMBINI, M.F.; PERES, F.A.; LAPA, A.T.; SINICATO, N.A.; QUENTAL, B.; PINCELLI, A.S.M.; AMARAL, T.N.; GOMES, C.C.; RIO, A.P.; MARQUES-NETO, J.F.; COSTALLAT, L.T.L.; FERNANDES, P.T.; CENDES, F.; RITTNER, L.; APPENZELLER, S. Olfactory function in systemic lupus erythematosus and systemic sclerosis. A longitudinal study and review of the literature. Autoimmunity reviews, 2018. 17(4), 405-412.
COVER, G.S.; HERRERA, W.G.; BENTO, M.P.; APPENZELLER, S.; RITTNER, L. Computational methods for corpus callosum segmentation on MRI: A systematic literature review. Computer methods and programs in biomedicine, 2018. v.154, 25-35.
COSTALLAT, B.L.; FERREIRA, D.M.; LAPA, A.T.; RITTNER, L.; COSTALLAT, L.T.L.; APPENZELLER, S. Brain diffusion tensor MRI in systematic lupus erythematosus: A systematic review. Autoimmunity reviews, 2018. 17(1), 36-43.
PINHEIRO, G.R.; COVER, G.S.; BENTO, M.P.; RITTNER, L. Automatic callosal fiber convergence plane computation through DTI-based divergence map. In Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2018. Vol. 10578, p. 1057815.
PEREIRA, M.; COVER, G.; APPENZELLER, S.; RITTNER, L. Corpus callosum parcellation methods: a quantitative comparative study. In Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2018. Vol. 10578, p. 1057817.
Leticia Rittner, Assistant Professor (MS-3.2) - DCA/FEEC/UNICAMP
"These pages are not an official publication of the University of Campinas (UNICAMP), the responsibility for their content rests solely with the author."
"These pages are not an official publication of the University of Campinas (UNICAMP), the responsibility for their content rests solely with the author."
