Uma solução de aprendizagem de máquina para detecção de ceratocone
Resumo
Ceratocone é um problema que provoca alterações no formato e espessura da córnea, deixando-a mais fina e menos resistente. Pacientes que foram submetidos a cirurgia refrativa a laser tem uma chance maior de desenvolver a doença pelo afinamento corneano, podendo causar cegueira e exigir o transplante de córnea. Este artigo apresenta uma proposta para detectar estágios iniciais de ceratocone em pacientes candidatos a cirurgia refrativa, aplicando algoritmos de aprendizagem de máquina em dados oculares e biomecânicos da córnea de forma a diferenciar córneas normais de portadores de ceratocone.
Palavras-chave:
Aprendizgem de Máquina, Ceratocone, Cirurgia refrativa
Referências
Kennedy et al, Am J Ophthalmol 1986; 100:267-73. A 48-year clinical and epidemiologic study of keratoconus. Kanellopoulos AJ. Post-LASIK ectasia. Ophthalmology. 2007.
Klein SR, Epstein RJ, Randleman JB, Stulting RD. Corneal ectasia after laser in situ keratomileusis in patients without apparent preoperative risk factors. Cornea. 2006;25:388–403.
Randleman JB, Woodward M, Lynn MJ, Stulting RD. Risk assessment for ectasia after corneal refractive surgery. Ophthalmology. 2008;115:37–50.
Rohm, M. et al. Predicting visual acuity by using machine learning in patients treated for neovascular age-related macular degeneration. Ophthalmology 125, 1028–1036 (2018).
Oh, E., Yoo, T. K. & Hong, S. Artificial neural network approach for differentiating open-angle glaucoma from glaucoma suspect without a visual field test. Invest. Ophthalmol. Vis. Sci. 56, 3957–3966 (2015).
Jiménez, J. R., Alarcón, A., Anera, R. G. & Jiménez Del Barco, L. Q-optimized algorithms: theoretical analysis of factors influencing visual quality after myopic corneal refractive surgery. J. Refract. Surg. Thorofare NJ 1995 32, 612–617 (2016).
Alexandru Lavric and Popa Valentin. KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks- https://doi.org/10.1155/2019/8162567.
R. Ambrósio, B.T. Lopes et al. Integration of scheimpflug-based corneal tomography and biomechanical assessments for enhancing ectasia detection J. Refract. Surg., 33 (7) (2017), pp. 434-443, 10.3928/1081597X-20170426-02.
P. A. Accardo and S. Pensiero, “Neural network-based system for early keratoconus detection from corneal topography,” Journal of biomedical informatics, vol. 35, no. 3, pp. 151–159, 2002.
Klein SR, Epstein RJ, Randleman JB, Stulting RD. Corneal ectasia after laser in situ keratomileusis in patients without apparent preoperative risk factors. Cornea. 2006;25:388–403.
Randleman JB, Woodward M, Lynn MJ, Stulting RD. Risk assessment for ectasia after corneal refractive surgery. Ophthalmology. 2008;115:37–50.
Rohm, M. et al. Predicting visual acuity by using machine learning in patients treated for neovascular age-related macular degeneration. Ophthalmology 125, 1028–1036 (2018).
Oh, E., Yoo, T. K. & Hong, S. Artificial neural network approach for differentiating open-angle glaucoma from glaucoma suspect without a visual field test. Invest. Ophthalmol. Vis. Sci. 56, 3957–3966 (2015).
Jiménez, J. R., Alarcón, A., Anera, R. G. & Jiménez Del Barco, L. Q-optimized algorithms: theoretical analysis of factors influencing visual quality after myopic corneal refractive surgery. J. Refract. Surg. Thorofare NJ 1995 32, 612–617 (2016).
Alexandru Lavric and Popa Valentin. KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks- https://doi.org/10.1155/2019/8162567.
R. Ambrósio, B.T. Lopes et al. Integration of scheimpflug-based corneal tomography and biomechanical assessments for enhancing ectasia detection J. Refract. Surg., 33 (7) (2017), pp. 434-443, 10.3928/1081597X-20170426-02.
P. A. Accardo and S. Pensiero, “Neural network-based system for early keratoconus detection from corneal topography,” Journal of biomedical informatics, vol. 35, no. 3, pp. 151–159, 2002.
Publicado
03/11/2020
Como Citar
RUBIN, Francis Spiegel; ALVIM, Adriana; MELLO, Carlos.
Uma solução de aprendizagem de máquina para detecção de ceratocone. In: WORKSHOP DE TESES E DISSERTAÇÕES EM SISTEMAS DE INFORMAÇÃO - SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 16. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 25-29.
DOI: https://doi.org/10.5753/sbsi.2020.13120.
