Diseño de un sistema de reconocimiento de patrones en imágenes termográficas y de huella plantar para la identificación de pie plano en niños con edades entre cinco y seis años

Design of a pattern recognition system in thermographic and footprint images for flatfoot identification in children between five and six years old

  • Milton Javier Muñoz-Neira Fundación Universitaria de San Gil, San Gil, Santander, Colombia
  • Anyed Stephany Martínez-Parra Fundación Universitaria de San Gil, San Gil, Santander, Colombia
  • Cristian Gerardo Ruiz-Adarme Fundación Universitaria de San Gil, San Gil, Santander, Colombia
  • Carlos Humberto Triana-Castro Fundación Universitaria de San Gil, San Gil, Santander, Colombia
  • Jorge Luis Cornejo-Plata UNISANGIL
Palabras clave: flatfoot, texture patterns, footprint patterns, artificial neuronal networks (en_US)
Palabras clave: pie plano, patrones de textura, patrones de huella, redes neuronales artificiales (es_ES)

Resumen (es_ES)

The following paper presents the main results of exploratory research-oriented to the design and implementation of a pattern recognition system for flatfoot identification in children between 5 and 6 years. Patterns were determined from texture analysis of foot thermographic images, and from contour analysis of footprint images. For each case, an artificial neuronal network was trained, with base in a back-propagation algorithm. In each trial, 70 % of data were used for training, and 30 % for validation. For experiments done, success rates greater than 80 % were achieved. The best results were reached with contour patterns reduced by principal components analysis, PCA, in a binary system, with a success rate of 90.84 % in cross-validation. Results are a contribution to the study of diagnostic techniques for flatfoot treatment through the use of technologic tools.

Resumen (en_US)

The following paper presents the main results of an exploratory research oriented to design and implementation of a pattern recognition system for flatfoot identification in children between 5 and 6 years. Patterns were determined from texture analysis of foot thermographic images, and from contour analysis of footprint images. For each case, an artificial neuronal network was trained, with base in a back propagation algorithm. In each trial, 70% of data were used for training, and 30% for validation.  For experiments done, success rates greater than 80% were achieved. The best results was reached with contour patterns reduced by PCA, in a binary system, with a success rate of 90.84% in cross validation. Results are a contribution to study of diagnostic techniques for flatfoot treatment through use of technologic tools.

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Referencias

Aretusi, G.; Fontanella, L.; Ippoliti, L. (2009). Texture Analysis in Thermal Infrared Imaging for Classification of Raynaud’s Phenomenon. En S. Co. 2009. Sixth Conference. Complex Data Modeling and Computationally Intensive Statistical Methods for Estimation and Prediction, p. 13. Maggioli Editore. https://doi.org/10.1007/978-88-470-1386-5_1

Ballestero, R. (2015). Análisis Clínico y Baropodométrico de los niños con pie plano valgo flexible infantil en edad preescolar. Tesis para optar el grado de doctor. Madrid: Universidad Complutense de Madrid. https://eprints.ucm.es/30672/1/T36148.pdf

Bhattacharjee, N.; Goswami, M. (2017). Footprint analysis and prevalence of flatfoot: a study among the children of South 24 Parganas, West Bengal, India. Anthropological Review, 80(4), 369-380. https://doi.org/10.1515/anre-2017-0026

Bishop, C. (2016). Pattern recognition and machine learning. Springer-Verlag, Nueva York.

Cebulski, A.; Boutry, N.; Szymanski, C.; Maynou, C.; Lefebvre, G.; Amzallag, E.; Cotten, A. (2016) Correlation between primary flat foot and lower extremity rotational misalignment in adults. Diagnostic and Interventional Imaging, 97(11), 1151-1157. https://doi.org/10.1016/j.diii.2016.01.011

Colque, M. M. (2017). Incidencia de pie plano y cavo en niños de la Institución Educativa Inicial N.º 349 Tawantinsuyo de la ciudad de Juliaca. Tesis de Licenciatura. Puno: Universidad Nacional del Altiplano. http://repositorio.unap.edu.pe/handle/UNAP/6046

de Cesar Netto, C.; Schon, L. C.; Thawait, G. K.; da Fonseca, L. F.; Chinanuvathana, A.; Zbijewski, W. B.; Demehri, S. (2017). Flexible adult acquired flatfoot deformity: comparison between weight-bearing and non-weight-bearing measurements using cone-beam computed tomography. JBJS, 99(18), e98. https://doi.org/10.2106/JBJS.16.01366

Duda, R. O.; Hart, P. E.;Stork, D. G. (2012). Pattern classification. John Wiley & Sons.

Gonzalez, R. C.; Woods, R. E. (2012). Digital image processing. 4 edition. Pearson.

Hamza, A. O.; Ahmed, H. K.; Khider, M. O. (2015). A new noninvasive flatfoot detector. Journal of Clinical Engineering, 40(1), 57-63. https://doi.org/10.1097/JCE.0000000000000081

Harris, G.; Young, L.; Handel, I.; Farish, M.; Mason, C.; Mitchell, M. A.; Haskell, M. J. (2018). The use of infrared thermography for detecting digital dermatitis in dairy cattle: What is the best measure of temperature and foot location to use? The Veterinary Journal, 237, 26-33. https://doi.org/10.1016/j.tvjl.2018.05.008

Kao, E. F.; Lu, C. Y.; Wang, C. Y.; Yeh, W. C.; Hsia, P. K. (2018). Fully automated determination of arch angle on weight-bearing foot radiograph. Computer Methods and Programs in Biomedicine, 154, 79-88. https://doi.org/10.1016/j.cmpb.2017.11.009

Kittler, J. (2002). Reconocimiento de Patrones. Notas de seminario, Universidad de Surrey, Rev. 0.9.

Laowattanatham, N.; Chitsakul, K.; Tretriluxana, S.; Hansasuta, C. (2014). Smart digital podoscope for foot deformity assessment. En Biomedical Engineering International Conference (BMEiCON) (pp. 1-5). IEEE. https://doi.org/10.1109/BMEiCON.2014.7017410

Lever, C. J.; Hennessy, M. S. (2016). Adult flat foot deformity. Orthopaedics and Trauma, 30(1), 41-50. https://doi.org/10.1016/j.mporth.2016.02.005

Martínez, A. G. (2009). Pie plano en la infancia y adolescencia. Conceptos actuales. Revista Mexicana de Ortopedia Pediátrica, 11(1), 5-13. http://www.medigraphic.com/pdfs/opediatria/op-2009/op091b.pdf

Milosevic, M.; Jankovic, D.; Peulic, A. (2014). Thermography based breast cancer detection using texture features and minimum variance quantization. Excli Journal, 13, 1204. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4464488/

Navarro, L. A.; García, D. O.; Villavicencio, E. A.; Torres, M. A.; Nakamura, O. K.; Huamaní, R.; Yabar, L. F. (2010). Opto-electronic system for detection of flat foot by using estimation techniques: Study and approach of design. In Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE (pp. 5768-5771) https://doi.org/10.1109/IEMBS.2010.5627842

Pauk, J.; Ezerskiy, V.; Raso, J. V.; Rogalski, M. (2012). Epidemiologic factors affecting plantar arch development in children with flat feet. Journal of the American Podiatric Medical Association, 102(2), 114-121. https://doi.org/10.7547/1020114

Pfeiffer, M.; Kotz, R.; Ledl, T.; Hauser, G.; Sluga, M. (2006). Prevalence of flat foot in preschool-aged children. Pediatrics, 118(2), 634-639. https://doi.org/10.1542/peds.2005-2126

Pita, S.; Gonzalez, C.; Alonso, F.; Seoane, T.; Pertega, S.; Perez, S.; Balboa, V. (2017). Flat Foot in a Random Population and its Impact on Quality of Life and Functionality. Journal of Clinical and Diagnostic Research: JCDR, 11(4), LC22. https://doi.org/10.7860/JCDR/2017/24362.9697

Pramanik, S.; Bhattacharjee, D.; Nasipuri, M. (2016). Texture analysis of breast thermogram for differentiation of malignant and benign breast. En Advances in Computing, Communications and Informatics (ICACCI), (pp. 8-14), IEEE. https://doi.org/10.1109/ICACCI.2016.7732018

Revenga, C.; Bulo, M. P. (2005). El pie plano valgo: evolución de la huella plantar y factores relacionados. Revista de Ortopedia y Traumatología, 49(4), 271-280. https://doi.org/10.1016/S1888-4415(05)76315-3

Ring, F. (2010). Thermal imaging today and its relevance to diabetes. Journal of Diabetes Science and Technology, 4(4.) https://doi.org/10.1177/193229681000400414

Saldívar, H. I.; Ramírez, A. G.; Acevedo, M. A. R.; Pérez-Rodríguez, P. (2015). Obesidad infantil: factor de riesgo para desarrollar pie plano. Boletín médico del Hospital Infantil de México, 72(1), 55-60. https://doi.org/10.1016/j.bmhimx.2015.02.003

Su, K. H.; Kaewwichit, T.; Tseng, C. H.; Chang, C. C. (2016). Automatic footprint detection approach for the calculation of arch index and plantar pressure in a flat rubber pad. Multimedia Tools and Applications, 75(16), 9757-9774. https://doi.org/10.1007/s11042-015-2796-x

van Netten, J. J.; van Baal, J. G.; Liu, C.; van Der Heijden, F.; Bus, S. A. (2013). Infrared thermal imaging for automated detection of diabetic foot complications. Journal of Diabetes Science and Technology, 7(5). https://doi.org/10.1177/193229681300700504

Vergara, E.; Serrano Sánchez, R. F.; Correa Posada, J. R.; Molano, A. C.; Guevara, O. A. (2012). Prevalence of flatfoot in school between 3 and 10 years. Study of two different populations geographically and socially. Colombia Médica, 43(2), 141-146. https://doi.org/10.1007/s00590-010-0717-2

Cómo citar
Muñoz-Neira , M. J., Martínez-Parra, A. S., Ruiz-Adarme, C. G., Triana-Castro, C. H., & Cornejo-Plata, J. L. (2019). Diseño de un sistema de reconocimiento de patrones en imágenes termográficas y de huella plantar para la identificación de pie plano en niños con edades entre cinco y seis años . Revista científica, 3(36). Recuperado a partir de https://revistas.udistrital.edu.co/index.php/revcie/article/view/14345
Publicado: 2019-08-13
Sección
Ciencia e ingeniería