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Segmentation and quantification of COVID-19 infections in CT using pulmonary vessels extraction and deep learning.

J. Diniz, D. Quintanilha, A. dos Santos Neto, G. da Silva, J. Ferreira, S. Netto, J. Araújo, L. da Cruz, T. Fontenele, C. da S. Martins, M. Ferreira, V. Garcia, J. Boaro, C. Cipriano, A. Silva, A. de Paiva, G. Junior, J. de Almeida, R. Nunes, R. Mogami, and M. Gattass. Multim. Tools Appl., 80 (19): 29367-29399 (2021)

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Kerstin da Silva

Rodrigo Corrêa da Silva

Adriano João Da Silva

Carolina Ferraz da Silva

Antonio Da Silva Mello

Other publications of authors with the same name

Classification of malignant and benign lung nodules using taxonomic diversity index and phylogenetic distance.R. de Sousa Costa, G. da Silva, A. de Carvalho Filho, A. Silva, A. de Paiva, and M. Gattass. Medical Biol. Eng. Comput., 56 (11): 2125-2136 (2018)Automatic method for classifying COVID-19 patients based on chest X-ray images, using deep features and PSO-optimized XGBoost.D. Júnior, L. da Cruz, J. Diniz, G. da Silva, G. Junior, A. Silva, A. de Paiva, R. Nunes, and M. Gattass. Expert Syst. Appl., (2021)An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks.J. Souza, J. Diniz, J. Ferreira, G. da Silva, A. Silva, and A. de Paiva. Comput. Methods Programs Biomed., (2019)Lung nodules diagnosis based on evolutionary convolutional neural network.G. da Silva, O. da Silva Neto, A. Silva, A. de Paiva, and M. Gattass. Multim. Tools Appl., 76 (18): 19039-19055 (2017)Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.G. da Silva, P. Diniz, J. Ferreira, J. França, A. Silva, A. de Paiva, and E. de Cavalcanti. Medical Biol. Eng. Comput., 58 (9): 1947-1964 (2020)Automatic Prostate Segmentation on 3D MRI Scans Using Convolutional Neural Networks with Residual Connections and Superpixels.G. da Silva, J. França, P. Diniz, A. Silva, A. de Paiva, and E. de Cavalcanti. IWSSIP, page 51-56. IEEE, (2020)Deployment of a Machine Learning System for Predicting Lawsuits Against Power Companies: Lessons Learned from an Agile Testing Experience for Improving Software Quality.L. Rivero, J. Diniz, G. da Silva, G. Borralho, G. Junior, A. de Paiva, E. Alves, and M. de Oliveira. SBQS, page 30. ACM, (2020)An ergonomic evaluation method using a mobile depth sensor and pose estimation.P. de Freitas, P. Mendes, A. Busson, Á. Guedes, G. da Silva, A. de Paiva, and S. Colcher. WebMedia, page 445-452. ACM, (2019)Convolutional neural network-based PSO for lung nodule false positive reduction on CT images.G. da Silva, T. Valente, A. Silva, A. de Paiva, and M. Gattass. Comput. Methods Programs Biomed., (2018)Heart segmentation in planning CT using 2.5D U-Net++ with attention gate.J. Diniz, D. Júnior, L. da Cruz, G. da Silva, J. Ferreira, D. Quintanilha, A. Silva, A. de Paiva, and M. Gattass. Comput. methods Biomech. Biomed. Eng. Imaging Vis., 11 (3): 317-325 (May 2023)

BibSonomy

Disambiguation of "da Silva, Giovanni Lucca França"

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Segmentation and quantification of COVID-19 infections in CT using pulmonary vessels extraction and deep learning.

Please choose a person to relate this publication to

Kerstin da Silva

Rodrigo Corrêa da Silva

Adriano João Da Silva

Carolina Ferraz da Silva

Antonio Da Silva Mello

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "da Silva, Giovanni Lucca França"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Segmentation and quantification of COVID-19 infections in CT using pulmonary vessels extraction and deep learning.

Please choose a person to relate this publication to

Kerstin da Silva

Rodrigo Corrêa da Silva

Adriano João Da Silva

Carolina Ferraz da Silva

Antonio Da Silva Mello

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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Segmentation and quantification of COVID-19 infections in CT using pulmonary vessels extraction and deep learning.