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Artigo de periodico
Fast and accurate 3-D spine MRI segmentation using FastCleverSeg (2024)
Ramos, Jonathan da Silva ; Cazzolato, Mirela Teixeira ; Linares, Oscar Alonso Cuadros ; Maciel, Jamilly Gomes; Menezes-Reis, Rafael ; Azevedo-Marques, Paulo Mazzoncini de ; Nogueira-Barbosa, Marcello Henrique ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Magnetic Resonance Imaging. Unidades: FMRP, ICMC
Subjects: RECONHECIMENTO DE IMAGEM, BANCO DE DADOS MULTIMÍDIA, DIAGNÓSTICO POR COMPUTADOR, TECNOLOGIAS DA SAÚDE, RESSONÂNCIA MAGNÉTICA, COLUNA VERTEBRAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RAMOS, Jonathan da Silva et al. Fast and accurate 3-D spine MRI segmentation using FastCleverSeg. Magnetic Resonance Imaging, v. 109, p. 134-146, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.mri.2024.03.021. Acesso em: 15 jun. 2024.
APA
Ramos, J. da S., Cazzolato, M. T., Linares, O. A. C., Maciel, J. G., Menezes-Reis, R., Azevedo-Marques, P. M. de, et al. (2024). Fast and accurate 3-D spine MRI segmentation using FastCleverSeg. Magnetic Resonance Imaging, 109, 134-146. doi:10.1016/j.mri.2024.03.021
NLM
Ramos J da S, Cazzolato MT, Linares OAC, Maciel JG, Menezes-Reis R, Azevedo-Marques PM de, Nogueira-Barbosa MH, Traina Junior C, Traina AJM. Fast and accurate 3-D spine MRI segmentation using FastCleverSeg [Internet]. Magnetic Resonance Imaging. 2024 ; 109 134-146.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1016/j.mri.2024.03.021
Vancouver
Ramos J da S, Cazzolato MT, Linares OAC, Maciel JG, Menezes-Reis R, Azevedo-Marques PM de, Nogueira-Barbosa MH, Traina Junior C, Traina AJM. Fast and accurate 3-D spine MRI segmentation using FastCleverSeg [Internet]. Magnetic Resonance Imaging. 2024 ; 109 134-146.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1016/j.mri.2024.03.021
Artigo de periodico
Pushing diversity into higher dimensions: the LID effect on diversified similarity searching (2023)
Jasbick, Daniel L ; Santos, Lúcio Fernandes Dutra ; Azevedo-Marques, Paulo Mazzoncini de ; Traina, Agma Juci Machado ; Oliveira, Daniel de ; Bêdo, Marcos Vinícius Naves
Source: Information Systems. Unidades: FMRP, ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE PADRÕES, VISUALIZAÇÃO
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ABNT
JASBICK, Daniel L et al. Pushing diversity into higher dimensions: the LID effect on diversified similarity searching. Information Systems, v. 114, p. 1-16, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.is.2023.102166. Acesso em: 15 jun. 2024.
APA
Jasbick, D. L., Santos, L. F. D., Azevedo-Marques, P. M. de, Traina, A. J. M., Oliveira, D. de, & Bêdo, M. V. N. (2023). Pushing diversity into higher dimensions: the LID effect on diversified similarity searching. Information Systems, 114, 1-16. doi:10.1016/j.is.2023.102166
NLM
Jasbick DL, Santos LFD, Azevedo-Marques PM de, Traina AJM, Oliveira D de, Bêdo MVN. Pushing diversity into higher dimensions: the LID effect on diversified similarity searching [Internet]. Information Systems. 2023 ; 114 1-16.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1016/j.is.2023.102166
Vancouver
Jasbick DL, Santos LFD, Azevedo-Marques PM de, Traina AJM, Oliveira D de, Bêdo MVN. Pushing diversity into higher dimensions: the LID effect on diversified similarity searching [Internet]. Information Systems. 2023 ; 114 1-16.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1016/j.is.2023.102166
Artigo de periodico
Features of lumbar spine texture extracted from routine MRI correlate with bone mineral density and can potentially differentiate patients with and without fragility fractures in the spine (2023)
Maciel, J. G.; Salmon, Carlos Ernesto Garrido ; Hosseini, B. S.; Azevedo-Marques, Paulo Mazzoncini de ; Paula, Francisco Jose Albuquerque de; Nogueira-Barbosa, Marcello Henrique
Source: Brazilian Journal of Medical and Biological Research. Unidades: FFCLRP, FMRP
Subjects: DENSIDADE ÓSSEA, DOENÇAS ÓSSEAS, VÉRTEBRAS LOMBARES, DIAGNÓSTICO POR IMAGEM, IMAGEM POR RESSONÂNCIA MAGNÉTICA, OSTEOPOROSE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MACIEL, J. G. et al. Features of lumbar spine texture extracted from routine MRI correlate with bone mineral density and can potentially differentiate patients with and without fragility fractures in the spine. Brazilian Journal of Medical and Biological Research, v. 56, 2023Tradução . . Disponível em: https://doi.org/10.1590/1414-431X2023e12454. Acesso em: 15 jun. 2024.
APA
Maciel, J. G., Salmon, C. E. G., Hosseini, B. S., Azevedo-Marques, P. M. de, Paula, F. J. A. de, & Nogueira-Barbosa, M. H. (2023). Features of lumbar spine texture extracted from routine MRI correlate with bone mineral density and can potentially differentiate patients with and without fragility fractures in the spine. Brazilian Journal of Medical and Biological Research, 56. doi:10.1590/1414-431X2023e12454
NLM
Maciel JG, Salmon CEG, Hosseini BS, Azevedo-Marques PM de, Paula FJA de, Nogueira-Barbosa MH. Features of lumbar spine texture extracted from routine MRI correlate with bone mineral density and can potentially differentiate patients with and without fragility fractures in the spine [Internet]. Brazilian Journal of Medical and Biological Research. 2023 ; 56[citado 2024 jun. 15 ] Available from: https://doi.org/10.1590/1414-431X2023e12454
Vancouver
Maciel JG, Salmon CEG, Hosseini BS, Azevedo-Marques PM de, Paula FJA de, Nogueira-Barbosa MH. Features of lumbar spine texture extracted from routine MRI correlate with bone mineral density and can potentially differentiate patients with and without fragility fractures in the spine [Internet]. Brazilian Journal of Medical and Biological Research. 2023 ; 56[citado 2024 jun. 15 ] Available from: https://doi.org/10.1590/1414-431X2023e12454
Trabalho de evento
Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures (2022)
Bêdo, Marcos Vinícius Naves; Ramos, Jonathan da Silva ; Traina, Agma Juci Machado ; Traina Junior, Caetano ; Nogueira-Barbosa, Marcello Henrique ; Azevedo-Marques, Paulo Mazzoncini de
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidades: ICMC, FMRP
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, DIAGNÓSTICO POR IMAGEM, RESSONÂNCIA MAGNÉTICA, OSTEOGÊNESE IMPERFEITA, OSTEOPOROSE
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ABNT
BÊDO, Marcos Vinícius Naves et al. Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures. 2022, Anais.. Los Alamitos: IEEE, 2022. Disponível em: https://doi.org/10.1109/CBMS55023.2022.00020. Acesso em: 15 jun. 2024.
APA
Bêdo, M. V. N., Ramos, J. da S., Traina, A. J. M., Traina Junior, C., Nogueira-Barbosa, M. H., & Azevedo-Marques, P. M. de. (2022). Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS55023.2022.00020
NLM
Bêdo MVN, Ramos J da S, Traina AJM, Traina Junior C, Nogueira-Barbosa MH, Azevedo-Marques PM de. Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures [Internet]. Proceedings. 2022 ;[citado 2024 jun. 15 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00020
Vancouver
Bêdo MVN, Ramos J da S, Traina AJM, Traina Junior C, Nogueira-Barbosa MH, Azevedo-Marques PM de. Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures [Internet]. Proceedings. 2022 ;[citado 2024 jun. 15 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00020
Trabalho de evento-resumo periodico
Deep extracted features to support content-based image retrieval systems in the diagnosis of Covid-19 and interstitial diseases (2022)
Bêdo, Marcos Vinícius Naves; Lima, L; Koenigkam-Santos, Marcel ; Traina, Agma Juci Machado ; Azevedo-Marques, Paulo Mazzoncini de
Source: International Journal of Computer Assisted Radiology and Surgery. Conference titles: International Congress and Exhibition on Computer Assisted Radiology and Surgery - CARS. Unidades: FMRP, ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE IMAGEM, APRENDIZADO COMPUTACIONAL, REDES NEURAIS, COVID-19
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ABNT
BÊDO, Marcos Vinícius Naves et al. Deep extracted features to support content-based image retrieval systems in the diagnosis of Covid-19 and interstitial diseases. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Springer. Disponível em: https://doi.org/10.1007/s11548-022-02635-x. Acesso em: 15 jun. 2024. , 2022
APA
Bêdo, M. V. N., Lima, L., Koenigkam-Santos, M., Traina, A. J. M., & Azevedo-Marques, P. M. de. (2022). Deep extracted features to support content-based image retrieval systems in the diagnosis of Covid-19 and interstitial diseases. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Springer. doi:10.1007/s11548-022-02635-x
NLM
Bêdo MVN, Lima L, Koenigkam-Santos M, Traina AJM, Azevedo-Marques PM de. Deep extracted features to support content-based image retrieval systems in the diagnosis of Covid-19 and interstitial diseases [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2022 ; 17 S13-S14.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-022-02635-x
Vancouver
Bêdo MVN, Lima L, Koenigkam-Santos M, Traina AJM, Azevedo-Marques PM de. Deep extracted features to support content-based image retrieval systems in the diagnosis of Covid-19 and interstitial diseases [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2022 ; 17 S13-S14.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-022-02635-x
Artigo de periodico
Computer-aided diagnosis of vertebral compression fractures using convolutional neural networks and radiomics (2022)
Del Lama, Rafael Silva; Candido, Raquel Mariana ; Correia, Natália Santana Chiari; Nogueira-Barbosa, Marcello Henrique; Azevedo-Marques, Paulo Mazzoncini de ; Tinós, Renato
Source: Journal of Digital Imaging. Unidades: FMRP, FFCLRP
Subjects: ALGORITMOS GENÉTICOS, REDES NEURAIS, DIAGNÓSTICO POR COMPUTADOR, FRATURAS, COLUNA VERTEBRAL
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ABNT
DEL LAMA, Rafael Silva et al. Computer-aided diagnosis of vertebral compression fractures using convolutional neural networks and radiomics. Journal of Digital Imaging, v. 35, n. 3, p. 446-458, 2022Tradução . . Disponível em: https://doi.org/10.1007/s10278-022-00586-y. Acesso em: 15 jun. 2024.
APA
Del Lama, R. S., Candido, R. M., Correia, N. S. C., Nogueira-Barbosa, M. H., Azevedo-Marques, P. M. de, & Tinós, R. (2022). Computer-aided diagnosis of vertebral compression fractures using convolutional neural networks and radiomics. Journal of Digital Imaging, 35( 3), 446-458. doi:10.1007/s10278-022-00586-y
NLM
Del Lama RS, Candido RM, Correia NSC, Nogueira-Barbosa MH, Azevedo-Marques PM de, Tinós R. Computer-aided diagnosis of vertebral compression fractures using convolutional neural networks and radiomics [Internet]. Journal of Digital Imaging. 2022 ; 35( 3): 446-458.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s10278-022-00586-y
Vancouver
Del Lama RS, Candido RM, Correia NSC, Nogueira-Barbosa MH, Azevedo-Marques PM de, Tinós R. Computer-aided diagnosis of vertebral compression fractures using convolutional neural networks and radiomics [Internet]. Journal of Digital Imaging. 2022 ; 35( 3): 446-458.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s10278-022-00586-y
Artigo de periodico
Manual versus semiautomatic segmentation of soft-tissue sarcomas on magnetic resonance imaging: evaluation of similarity and comparison of segmentation times (2021)
Dionísio, Fernando Carrasco Ferreira; Oliveira, Larissa Santos; Hernandes, Mateus de Andrade; Engel, Edgard Eduard ; Azevedo-Marques, Paulo Mazzoncini de ; Nogueira-Barbosa, Marcello Henrique
Source: Radiologia Brasileira. Unidade: FMRP
Subjects: PROCESSAMENTO DE IMAGENS, SARCOMA, DIAGNÓSTICO POR IMAGEM, NEOPLASIAS DE TECIDOS MOLES, RESSONÂNCIA MAGNÉTICA, REPRODUTIBILIDADE DE RESULTADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DIONÍSIO, Fernando Carrasco Ferreira et al. Manual versus semiautomatic segmentation of soft-tissue sarcomas on magnetic resonance imaging: evaluation of similarity and comparison of segmentation times. Radiologia Brasileira, v. 54, n. 3, p. 155–164, 2021Tradução . . Disponível em: https://doi.org/10.1590/0100-3984.2020.0028. Acesso em: 15 jun. 2024.
APA
Dionísio, F. C. F., Oliveira, L. S., Hernandes, M. de A., Engel, E. E., Azevedo-Marques, P. M. de, & Nogueira-Barbosa, M. H. (2021). Manual versus semiautomatic segmentation of soft-tissue sarcomas on magnetic resonance imaging: evaluation of similarity and comparison of segmentation times. Radiologia Brasileira, 54( 3), 155–164. doi:10.1590/0100-3984.2020.0028
NLM
Dionísio FCF, Oliveira LS, Hernandes M de A, Engel EE, Azevedo-Marques PM de, Nogueira-Barbosa MH. Manual versus semiautomatic segmentation of soft-tissue sarcomas on magnetic resonance imaging: evaluation of similarity and comparison of segmentation times [Internet]. Radiologia Brasileira. 2021 ; 54( 3): 155–164.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1590/0100-3984.2020.0028
Vancouver
Dionísio FCF, Oliveira LS, Hernandes M de A, Engel EE, Azevedo-Marques PM de, Nogueira-Barbosa MH. Manual versus semiautomatic segmentation of soft-tissue sarcomas on magnetic resonance imaging: evaluation of similarity and comparison of segmentation times [Internet]. Radiologia Brasileira. 2021 ; 54( 3): 155–164.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1590/0100-3984.2020.0028
Artigo de periodico
The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine (2021)
Cazzolato, Mirela Teixeira ; Ramos, Jonathan da Silva ; Rodrigues, Lucas Santiago ; Scabora, Lucas de Carvalho ; Chino, Daniel Yoshinobu Takada ; Jorge, Ana Elisa Serafim ; Azevedo-Marques, Paulo Mazzoncini de ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Computers in Biology and Medicine. Unidades: FMRP, ICMC
Subjects: PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, TELEMEDICINA, ÚLCERA CUTÂNEA
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ABNT
CAZZOLATO, Mirela Teixeira et al. The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine. Computers in Biology and Medicine, v. 134, p. 1-17, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.compbiomed.2021.104489. Acesso em: 15 jun. 2024.
APA
Cazzolato, M. T., Ramos, J. da S., Rodrigues, L. S., Scabora, L. de C., Chino, D. Y. T., Jorge, A. E. S., et al. (2021). The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine. Computers in Biology and Medicine, 134, 1-17. doi:10.1016/j.compbiomed.2021.104489
NLM
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine [Internet]. Computers in Biology and Medicine. 2021 ; 134 1-17.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1016/j.compbiomed.2021.104489
Vancouver
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine [Internet]. Computers in Biology and Medicine. 2021 ; 134 1-17.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1016/j.compbiomed.2021.104489
Trabalho de evento-resumo periodico
Spine MRI texture analysis and prediction of osteoporotic vertebral fracture (2021)
Ramos, Jonathan da Silva ; Maciel, Jamilly Gomes; Traina, Agma Juci Machado ; Azevedo-Marques, Paulo Mazzoncini de ; Nogueira-Barbosa, Marcello Henrique
Source: International Journal of Computer Assisted Radiology and Surgery. Conference titles: International Congress and Exhibition on Computer Assisted Radiology and Surgery - CARS. Unidades: ICMC, FMRP
Subjects: BANCO DE DADOS MULTIMÍDIA, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR IMAGEM, OSTEOPOROSE, COLUNA VERTEBRAL, RESSONÂNCIA MAGNÉTICA, TECNOLOGIAS DA SAÚDE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RAMOS, Jonathan da Silva et al. Spine MRI texture analysis and prediction of osteoporotic vertebral fracture. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s11548-021-02375-4. Acesso em: 15 jun. 2024. , 2021
APA
Ramos, J. da S., Maciel, J. G., Traina, A. J. M., Azevedo-Marques, P. M. de, & Nogueira-Barbosa, M. H. (2021). Spine MRI texture analysis and prediction of osteoporotic vertebral fracture. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. doi:10.1007/s11548-021-02375-4
NLM
Ramos J da S, Maciel JG, Traina AJM, Azevedo-Marques PM de, Nogueira-Barbosa MH. Spine MRI texture analysis and prediction of osteoporotic vertebral fracture [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2021 ; 16 S115-S116.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-021-02375-4
Vancouver
Ramos J da S, Maciel JG, Traina AJM, Azevedo-Marques PM de, Nogueira-Barbosa MH. Spine MRI texture analysis and prediction of osteoporotic vertebral fracture [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2021 ; 16 S115-S116.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-021-02375-4
Artigo de periodico
A superpixel-driven deep learning approach for the analysis of dermatological wounds (2020)
Blanco, Gustavo; Traina, Agma Juci Machado ; Traina Junior, Caetano ; Azevedo-Marques, Paulo Mazzoncini de ; Jorge, Ana Elisa Serafim ; Oliveira, Daniel de; Bêdo, Marcos Vinícius Naves
Source: Computer Methods and Programs in Biomedicine. Unidades: ICMC, FMRP
Subjects: PROCESSAMENTO DE IMAGENS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, ÚLCERA CUTÂNEA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BLANCO, Gustavo et al. A superpixel-driven deep learning approach for the analysis of dermatological wounds. Computer Methods and Programs in Biomedicine, v. 183, n. Ja 2020, p. 1-9, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.cmpb.2019.105079. Acesso em: 15 jun. 2024.
APA
Blanco, G., Traina, A. J. M., Traina Junior, C., Azevedo-Marques, P. M. de, Jorge, A. E. S., Oliveira, D. de, & Bêdo, M. V. N. (2020). A superpixel-driven deep learning approach for the analysis of dermatological wounds. Computer Methods and Programs in Biomedicine, 183( Ja 2020), 1-9. doi:10.1016/j.cmpb.2019.105079
NLM
Blanco G, Traina AJM, Traina Junior C, Azevedo-Marques PM de, Jorge AES, Oliveira D de, Bêdo MVN. A superpixel-driven deep learning approach for the analysis of dermatological wounds [Internet]. Computer Methods and Programs in Biomedicine. 2020 ; 183( Ja 2020): 1-9.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1016/j.cmpb.2019.105079
Vancouver
Blanco G, Traina AJM, Traina Junior C, Azevedo-Marques PM de, Jorge AES, Oliveira D de, Bêdo MVN. A superpixel-driven deep learning approach for the analysis of dermatological wounds [Internet]. Computer Methods and Programs in Biomedicine. 2020 ; 183( Ja 2020): 1-9.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1016/j.cmpb.2019.105079
Trabalho de evento-resumo periodico
AI-based radiomic approach in high-resolution CT images for differential diagnosis of idiopathic pulmonary fibrosis (2020)
Dorileo, Éderson Antonio Gomes; Koenigkam-Santos, Marcel ; Fabro, Alexandre Todorovic ; Azevedo-Marques, Paulo Mazzoncini de
Source: International Journal of Computer Assisted Radiology and Surgery. Conference titles: International Congress and Exhibition on Computer Assisted Radiology and Surgery - CARS. Unidade: FMRP
Subjects: FIBROSE PULMONAR, BIOMARCADORES, INTELIGÊNCIA ARTIFICIAL, RADIOLOGIA, DIAGNÓSTICO POR COMPUTADOR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DORILEO, Éderson Antonio Gomes et al. AI-based radiomic approach in high-resolution CT images for differential diagnosis of idiopathic pulmonary fibrosis. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s11548-020-02171-6. Acesso em: 15 jun. 2024. , 2020
APA
Dorileo, É. A. G., Koenigkam-Santos, M., Fabro, A. T., & Azevedo-Marques, P. M. de. (2020). AI-based radiomic approach in high-resolution CT images for differential diagnosis of idiopathic pulmonary fibrosis. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1007/s11548-020-02171-6
NLM
Dorileo ÉAG, Koenigkam-Santos M, Fabro AT, Azevedo-Marques PM de. AI-based radiomic approach in high-resolution CT images for differential diagnosis of idiopathic pulmonary fibrosis [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 S120-S121.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-020-02171-6
Vancouver
Dorileo ÉAG, Koenigkam-Santos M, Fabro AT, Azevedo-Marques PM de. AI-based radiomic approach in high-resolution CT images for differential diagnosis of idiopathic pulmonary fibrosis [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 S120-S121.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-020-02171-6
Artigo de periodico
Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity (2020)
Dionísio, F. C. F.; Oliveira, L. S.; Hernandes, M. A.; Engel, Edgard Eduard ; Rangayyan, R. M.; Azevedo-Marques, Paulo Mazzoncini de ; Nogueira-Barbosa, Marcello Henrique
Source: Brazilian Journal of Medical and Biological Research. Unidade: FMRP
Subjects: RNA, OSTEOSSARCOMA, PROGNÓSTICO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DIONÍSIO, F. C. F. et al. Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity. Brazilian Journal of Medical and Biological Research, v. 53, n. 2, p. e8962, 2020Tradução . . Disponível em: https://doi.org/10.1590/1414-431X20198962. Acesso em: 15 jun. 2024.
APA
Dionísio, F. C. F., Oliveira, L. S., Hernandes, M. A., Engel, E. E., Rangayyan, R. M., Azevedo-Marques, P. M. de, & Nogueira-Barbosa, M. H. (2020). Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity. Brazilian Journal of Medical and Biological Research, 53( 2), e8962. doi:10.1590/1414-431X20198962
NLM
Dionísio FCF, Oliveira LS, Hernandes MA, Engel EE, Rangayyan RM, Azevedo-Marques PM de, Nogueira-Barbosa MH. Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity [Internet]. Brazilian Journal of Medical and Biological Research. 2020 ; 53( 2): e8962.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1590/1414-431X20198962
Vancouver
Dionísio FCF, Oliveira LS, Hernandes MA, Engel EE, Rangayyan RM, Azevedo-Marques PM de, Nogueira-Barbosa MH. Manual and semiautomatic segmentation of bone sarcomas on MRI have high similarity [Internet]. Brazilian Journal of Medical and Biological Research. 2020 ; 53( 2): e8962.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1590/1414-431X20198962
Trabalho de evento-anais periodico
Effect of denoising on the localization of microcalcification clusters in digital mammography (2020)
Borges, Lucas R; Caron, Renato F; Azevedo-Marques, Paulo Mazzoncini de ; Vieira, Marcelo Andrade da Costa
Source: Proceedings of the SPIE. Conference titles: International Workshop on Breast Imaging - IWBI. Unidades: EESC, FMRP
Subjects: MAMOGRAFIA, PROCESSAMENTO DE IMAGENS, IMAGEM DIGITAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BORGES, Lucas R et al. Effect of denoising on the localization of microcalcification clusters in digital mammography. Proceedings of the SPIE. Washington, DC: Escola de Engenharia de São Carlos, Universidade de São Paulo. Disponível em: http://dx.doi.org/10.1117/12.2564316. Acesso em: 15 jun. 2024. , 2020
APA
Borges, L. R., Caron, R. F., Azevedo-Marques, P. M. de, & Vieira, M. A. da C. (2020). Effect of denoising on the localization of microcalcification clusters in digital mammography. Proceedings of the SPIE. Washington, DC: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1117/12.2564316
NLM
Borges LR, Caron RF, Azevedo-Marques PM de, Vieira MA da C. Effect of denoising on the localization of microcalcification clusters in digital mammography [Internet]. Proceedings of the SPIE. 2020 ; 11513[citado 2024 jun. 15 ] Available from: http://dx.doi.org/10.1117/12.2564316
Vancouver
Borges LR, Caron RF, Azevedo-Marques PM de, Vieira MA da C. Effect of denoising on the localization of microcalcification clusters in digital mammography [Internet]. Proceedings of the SPIE. 2020 ; 11513[citado 2024 jun. 15 ] Available from: http://dx.doi.org/10.1117/12.2564316
Trabalho de evento-resumo periodico
Towards convolutional neural network on primary lung tumors to predict histophatological type, distant and lymph node metastasis (2020)
Lima, Lucas Lins de; Ferreiro Junior, J. R.; Fabro, Alexandre Todorovic ; Cipriano, Federico; Faccio, A.; Koenigkam-Santos, Marcel ; Azevedo-Marques, Paulo Mazzoncini de
Source: International Journal of Computer Assisted Radiology and Surgery. Conference titles: International Congress and Exhibition on Computer Assisted Radiology and Surgery - CARS. Unidade: FMRP
Subjects: NEOPLASIAS PULMONARES, METÁSTASE ANIMAL, REDES NEURAIS, DIAGNÓSTICO POR COMPUTADOR, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIMA, Lucas Lins de et al. Towards convolutional neural network on primary lung tumors to predict histophatological type, distant and lymph node metastasis. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s11548-020-02171-6. Acesso em: 15 jun. 2024. , 2020
APA
Lima, L. L. de, Ferreiro Junior, J. R., Fabro, A. T., Cipriano, F., Faccio, A., Koenigkam-Santos, M., & Azevedo-Marques, P. M. de. (2020). Towards convolutional neural network on primary lung tumors to predict histophatological type, distant and lymph node metastasis. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1007/s11548-020-02171-6
NLM
Lima LL de, Ferreiro Junior JR, Fabro AT, Cipriano F, Faccio A, Koenigkam-Santos M, Azevedo-Marques PM de. Towards convolutional neural network on primary lung tumors to predict histophatological type, distant and lymph node metastasis [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 S116-S117.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-020-02171-6
Vancouver
Lima LL de, Ferreiro Junior JR, Fabro AT, Cipriano F, Faccio A, Koenigkam-Santos M, Azevedo-Marques PM de. Towards convolutional neural network on primary lung tumors to predict histophatological type, distant and lymph node metastasis [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 S116-S117.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-020-02171-6
Artigo de periodico
Towards an information infrastructure for medical image sharing (2020)
Motta, Gustavo Henrique Matos Bezerra; Araújo, Danilo A. B.; Lucena-Neto, Juracy R.; Azevedo-Marques, Paulo Mazzoncini de ; Cordeiro, Saulo da Silva; Araújo-Neto, Severino A.
Source: Journal of Digital Imaging. Unidade: FMRP
Subjects: MEDICINA, IMAGEM DIGITAL, ARQUITETURA DE SOFTWARE, INFRAESTRUTURA DE DESENVOLVIMENTO DE SOFTWARE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MOTTA, Gustavo Henrique Matos Bezerra et al. Towards an information infrastructure for medical image sharing. Journal of Digital Imaging, v. 33, n. 1, p. 88-98, 2020Tradução . . Disponível em: https://doi.org/10.1007/s10278-019-00243-x. Acesso em: 15 jun. 2024.
APA
Motta, G. H. M. B., Araújo, D. A. B., Lucena-Neto, J. R., Azevedo-Marques, P. M. de, Cordeiro, S. da S., & Araújo-Neto, S. A. (2020). Towards an information infrastructure for medical image sharing. Journal of Digital Imaging, 33( 1), 88-98. doi:10.1007/s10278-019-00243-x
NLM
Motta GHMB, Araújo DAB, Lucena-Neto JR, Azevedo-Marques PM de, Cordeiro S da S, Araújo-Neto SA. Towards an information infrastructure for medical image sharing [Internet]. Journal of Digital Imaging. 2020 ; 33( 1): 88-98.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s10278-019-00243-x
Vancouver
Motta GHMB, Araújo DAB, Lucena-Neto JR, Azevedo-Marques PM de, Cordeiro S da S, Araújo-Neto SA. Towards an information infrastructure for medical image sharing [Internet]. Journal of Digital Imaging. 2020 ; 33( 1): 88-98.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s10278-019-00243-x
Trabalho de evento
Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine (2020)
Cazzolato, Mirela Teixeira ; Ramos, Jonathan da Silva ; Rodrigues, Lucas Santiago ; Scabora, Lucas de Carvalho ; Chino, Daniel Yoshinobu Takada ; Jorge, Ana Elisa Serafim ; Azevedo-Marques, Paulo Mazzoncini de ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidades: FMRP, ICMC
Subjects: COMPUTAÇÃO MÓVEL, PROCESSAMENTO DE IMAGENS, ÚLCERA CUTÂNEA, TECNOLOGIAS DA SAÚDE, TELEMEDICINA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/CBMS49503.2020.00073. Acesso em: 15 jun. 2024.
APA
Cazzolato, M. T., Ramos, J. da S., Rodrigues, L. S., Scabora, L. de C., Chino, D. Y. T., Jorge, A. E. S., et al. (2020). Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS49503.2020.00073
NLM
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine [Internet]. Proceedings. 2020 ;[citado 2024 jun. 15 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00073
Vancouver
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine [Internet]. Proceedings. 2020 ;[citado 2024 jun. 15 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00073
Trabalho de evento
Impact of feature selection on clustering images of vertebral compression fractures (2020)
Candido, Raquel Mariana ; Lama, Rafael Silva Del; Chiari, Natália Santana; Nogueira-Barbosa, Marcello Henrique; Azevedo-Marques, Paulo Mazzoncini de ; Tinós, Renato
Source: Anais. Conference titles: Encontro Nacional de Inteligência Artificial e Computacional - ENIAC. Unidades: FMRP, FFCLRP
Subjects: FRATURAS, OSTEOPOROSE, DIAGNÓSTICO POR COMPUTADOR, APRENDIZADO COMPUTACIONAL, ALGORITMOS GENÉTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CANDIDO, Raquel Mariana et al. Impact of feature selection on clustering images of vertebral compression fractures. 2020, Anais.. Porto Alegre: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 2020. Disponível em: https://doi.org/10.5753/eniac.2020.12176. Acesso em: 15 jun. 2024.
APA
Candido, R. M., Lama, R. S. D., Chiari, N. S., Nogueira-Barbosa, M. H., Azevedo-Marques, P. M. de, & Tinós, R. (2020). Impact of feature selection on clustering images of vertebral compression fractures. In Anais. Porto Alegre: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.5753/eniac.2020.12176
NLM
Candido RM, Lama RSD, Chiari NS, Nogueira-Barbosa MH, Azevedo-Marques PM de, Tinós R. Impact of feature selection on clustering images of vertebral compression fractures [Internet]. Anais. 2020 ;[citado 2024 jun. 15 ] Available from: https://doi.org/10.5753/eniac.2020.12176
Vancouver
Candido RM, Lama RSD, Chiari NS, Nogueira-Barbosa MH, Azevedo-Marques PM de, Tinós R. Impact of feature selection on clustering images of vertebral compression fractures [Internet]. Anais. 2020 ;[citado 2024 jun. 15 ] Available from: https://doi.org/10.5753/eniac.2020.12176
Trabalho de evento-resumo periodico
Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences (2020)
Tenório, Ariane Priscilla Magalhães; Faleiros, M. C.; Ferreira-Junior, J. R.; Dalto, V. F.; Assad, R. L.; Nogueira-Barbosa, Marcello Henrique ; Azevedo-Marques, Paulo Mazzoncini de
Source: International Journal of Computer Assisted Radiology and Surgery. Conference titles: International Congress and Exhibition on Computer Assisted Radiology and Surgery - CARS. Unidade: FMRP
Subjects: DIAGNÓSTICO POR COMPUTADOR, APRENDIZADO COMPUTACIONAL, RADIOLOGIA, REUMATOLOGIA, RESSONÂNCIA MAGNÉTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TENÓRIO, Ariane Priscilla Magalhães et al. Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s11548-020-02171-6. Acesso em: 15 jun. 2024. , 2020
APA
Tenório, A. P. M., Faleiros, M. C., Ferreira-Junior, J. R., Dalto, V. F., Assad, R. L., Nogueira-Barbosa, M. H., & Azevedo-Marques, P. M. de. (2020). Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1007/s11548-020-02171-6
NLM
Tenório APM, Faleiros MC, Ferreira-Junior JR, Dalto VF, Assad RL, Nogueira-Barbosa MH, Azevedo-Marques PM de. Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 S129-S130.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-020-02171-6
Vancouver
Tenório APM, Faleiros MC, Ferreira-Junior JR, Dalto VF, Assad RL, Nogueira-Barbosa MH, Azevedo-Marques PM de. Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 S129-S130.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-020-02171-6
Artigo de periodico
CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms (2020)
Ferreira Junior, José Raniery; Santos, Marcel Koenigkam ; Tenório, Ariane Priscilla Magalhães; Faleiros, Matheus Calil; Cipriano, Federico Enrique Garcia; Fabro, Alexandre Todorovic ; Näppi, Janne; Yoshida, Hiroyuki; Azevedo-Marques, Paulo Mazzoncini de
Source: International Journal of Computer Assisted Radiology and Surgery. Unidade: FMRP
Subjects: RADIOMETRIA, NEOPLASIAS PULMONARES, BIOMARCADORES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERREIRA JUNIOR, José Raniery et al. CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms. International Journal of Computer Assisted Radiology and Surgery, v. 15, p. 163-172, 2020Tradução . . Disponível em: https://doi.org/10.1007/s11548-019-02093-y. Acesso em: 15 jun. 2024.
APA
Ferreira Junior, J. R., Santos, M. K., Tenório, A. P. M., Faleiros, M. C., Cipriano, F. E. G., Fabro, A. T., et al. (2020). CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms. International Journal of Computer Assisted Radiology and Surgery, 15, 163-172. doi:10.1007/s11548-019-02093-y
NLM
Ferreira Junior JR, Santos MK, Tenório APM, Faleiros MC, Cipriano FEG, Fabro AT, Näppi J, Yoshida H, Azevedo-Marques PM de. CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 163-172.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-019-02093-y
Vancouver
Ferreira Junior JR, Santos MK, Tenório APM, Faleiros MC, Cipriano FEG, Fabro AT, Näppi J, Yoshida H, Azevedo-Marques PM de. CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 163-172.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1007/s11548-019-02093-y
Artigo de periodico
Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging (2020)
Faleiros, Matheus Calil; Nogueira-Barbosa, Marcello Henrique ; Dalto, Vitor Faeda ; Júnior, José Raniery Ferreira ; Tenório, Ariane Priscilla Magalhães; Luppino-Assad, Rodrigo; Louzada Júnior, Paulo ; Rangayyan, Rangaraj Mandayam; Azevedo-Marques, Paulo Mazzoncini de
Source: Advances in Rheumatology. Unidade: FMRP
Subjects: DIAGNÓSTICO POR COMPUTADOR, ARTICULAÇÕES, DOENÇAS REUMÁTICAS, APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FALEIROS, Matheus Calil et al. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging. Advances in Rheumatology, v. 60, p. 1-10, 2020Tradução . . Disponível em: https://doi.org/10.1186/s42358-020-00126-8. Acesso em: 15 jun. 2024.
APA
Faleiros, M. C., Nogueira-Barbosa, M. H., Dalto, V. F., Júnior, J. R. F., Tenório, A. P. M., Luppino-Assad, R., et al. (2020). Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging. Advances in Rheumatology, 60, 1-10. doi:10.1186/s42358-020-00126-8
NLM
Faleiros MC, Nogueira-Barbosa MH, Dalto VF, Júnior JRF, Tenório APM, Luppino-Assad R, Louzada Júnior P, Rangayyan RM, Azevedo-Marques PM de. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging [Internet]. Advances in Rheumatology. 2020 ; 60 1-10.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1186/s42358-020-00126-8
Vancouver
Faleiros MC, Nogueira-Barbosa MH, Dalto VF, Júnior JRF, Tenório APM, Luppino-Assad R, Louzada Júnior P, Rangayyan RM, Azevedo-Marques PM de. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging [Internet]. Advances in Rheumatology. 2020 ; 60 1-10.[citado 2024 jun. 15 ] Available from: https://doi.org/10.1186/s42358-020-00126-8

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