Filtros : "Biomedical Signal Processing and Control" Removido: "2021" Limpar

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  • Source: Biomedical Signal Processing and Control. Unidades: IFSC, ICMC

    Subjects: REDES COMPLEXAS, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, OSTEOARTRITE DO JOELHO

    Versão AceitaAcesso à fonteDOIHow to cite
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    • ABNT

      RIBAS, Lucas Correia et al. A complex network based approach for knee osteoarthritis detection: data from the Osteoarthritis initiative. Biomedical Signal Processing and Control, v. 222, n. Ja 2022, p. 103133-1-103133-10, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.bspc.2021.103133. Acesso em: 05 dez. 2025.
    • APA

      Ribas, L. C., Riad, R., Jennane, R., & Bruno, O. M. (2022). A complex network based approach for knee osteoarthritis detection: data from the Osteoarthritis initiative. Biomedical Signal Processing and Control, 222( Ja 2022), 103133-1-103133-10. doi:10.1016/j.bspc.2021.103133
    • NLM

      Ribas LC, Riad R, Jennane R, Bruno OM. A complex network based approach for knee osteoarthritis detection: data from the Osteoarthritis initiative [Internet]. Biomedical Signal Processing and Control. 2022 ; 222( Ja 2022): 103133-1-103133-10.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.bspc.2021.103133
    • Vancouver

      Ribas LC, Riad R, Jennane R, Bruno OM. A complex network based approach for knee osteoarthritis detection: data from the Osteoarthritis initiative [Internet]. Biomedical Signal Processing and Control. 2022 ; 222( Ja 2022): 103133-1-103133-10.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.bspc.2021.103133
  • Source: Biomedical Signal Processing and Control. Unidade: IB

    Subjects: FREQUÊNCIA CARDÍACA, SISTEMA NERVOSO SIMPÁTICO, FISIOLOGIA CARDIOVASCULAR

    Acesso à fonteDOIHow to cite
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    • ABNT

      NATALI, José Eduardo Soubhia e STARZYNSKI, Paulo Nogueira e CHAUI-BERLINCK, Jose Guilherme. Oscillatory patterns in heart rate variability and complexity: a meta-analysis. Biomedical Signal Processing and Control, v. 33, p. 66-71, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.bspc.2016.11.012. Acesso em: 05 dez. 2025.
    • APA

      Natali, J. E. S., Starzynski, P. N., & Chaui-Berlinck, J. G. (2016). Oscillatory patterns in heart rate variability and complexity: a meta-analysis. Biomedical Signal Processing and Control, 33, 66-71. doi:10.1016/j.bspc.2016.11.012
    • NLM

      Natali JES, Starzynski PN, Chaui-Berlinck JG. Oscillatory patterns in heart rate variability and complexity: a meta-analysis [Internet]. Biomedical Signal Processing and Control. 2016 ; 33 66-71.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.bspc.2016.11.012
    • Vancouver

      Natali JES, Starzynski PN, Chaui-Berlinck JG. Oscillatory patterns in heart rate variability and complexity: a meta-analysis [Internet]. Biomedical Signal Processing and Control. 2016 ; 33 66-71.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.bspc.2016.11.012
  • Source: Biomedical Signal Processing and Control. Unidade: EP

    Subjects: TOMOGRAFIA COMPUTADORIZADA DE EMISSÃO, DOENÇAS PULMONARES, ALGORITMOS PARA IMAGENS

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    • ABNT

      IWAO, Yuma et al. Integrated lung field segmentation of injured region with anatomical structure analysis by failure–recovery algorithm from chest CT images. Biomedical Signal Processing and Control, v. 12, p. 28-38, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.bspc.2013.10.005. Acesso em: 05 dez. 2025.
    • APA

      Iwao, Y., Gotoh, T., Kagei, S., Iwasawa, T., & Tsuzuki, M. de S. G. (2014). Integrated lung field segmentation of injured region with anatomical structure analysis by failure–recovery algorithm from chest CT images. Biomedical Signal Processing and Control, 12, 28-38. doi:10.1016/j.bspc.2013.10.005
    • NLM

      Iwao Y, Gotoh T, Kagei S, Iwasawa T, Tsuzuki M de SG. Integrated lung field segmentation of injured region with anatomical structure analysis by failure–recovery algorithm from chest CT images [Internet]. Biomedical Signal Processing and Control. 2014 ; 12 28-38.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.bspc.2013.10.005
    • Vancouver

      Iwao Y, Gotoh T, Kagei S, Iwasawa T, Tsuzuki M de SG. Integrated lung field segmentation of injured region with anatomical structure analysis by failure–recovery algorithm from chest CT images [Internet]. Biomedical Signal Processing and Control. 2014 ; 12 28-38.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.bspc.2013.10.005
  • Source: Biomedical Signal Processing and Control. Unidade: EP

    Subjects: RESSONÂNCIA MAGNÉTICA, IMAGEM POR RESSONÂNCIA MAGNÉTICA

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    • ABNT

      SATO, André Kubagawa et al. Registration of temporal sequences of coronal and sagittal MR images through respiratory patterns. Biomedical Signal Processing and Control, v. 6, p. 34-47, 2011Tradução . . Disponível em: https://doi.org/10.1016/j.bspc.2010.08.002. Acesso em: 05 dez. 2025.
    • APA

      Sato, A. K., Stevo, N. A., Tavares, R. S., Tsuzuki, M. de S. G., Kadota, E., & Gotoh, T. (2011). Registration of temporal sequences of coronal and sagittal MR images through respiratory patterns. Biomedical Signal Processing and Control, 6, 34-47. doi:10.1016/j.bspc.2010.08.002
    • NLM

      Sato AK, Stevo NA, Tavares RS, Tsuzuki M de SG, Kadota E, Gotoh T. Registration of temporal sequences of coronal and sagittal MR images through respiratory patterns [Internet]. Biomedical Signal Processing and Control. 2011 ; 6 34-47.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.bspc.2010.08.002
    • Vancouver

      Sato AK, Stevo NA, Tavares RS, Tsuzuki M de SG, Kadota E, Gotoh T. Registration of temporal sequences of coronal and sagittal MR images through respiratory patterns [Internet]. Biomedical Signal Processing and Control. 2011 ; 6 34-47.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.bspc.2010.08.002

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