Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance

Joel Oswaldo Gallegos Guillen; Laura Jovani Estacio Cerquin; Javier Delgado Obando; Eveling Gloria Castro Gutierrez

doi:10.1007/978-3-319-91262-2_3

Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance

Joel Oswaldo Gallegos Guillen, Laura Jovani Estacio Cerquin, Javier Delgado Obando, Eveling Gloria Castro Gutierrez

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

1 Cita (Scopus)

Resumen

Using image processing to assist in the diagnostic of diseases is a growing challenge. Segmentation is one of the relevant stages in image processing. We present a strategy of complete segmentation of the proximal femur (right and left) in anterior-posterior pelvic radiographs using statistical models of shape and appearance for assistance in the diagnostics of diseases associated with femurs. Quantitative results are provided using the DICE coefficient and the processing time, on a set of clinical data that indicate the validity of our proposal.

Idioma original	Inglés
Título de la publicación alojada	Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings
Editores	Ryszard Tadeusiewicz, Leszek Rutkowski, Witold Pedrycz, Rafal Scherer, Marcin Korytkowski, Jacek M. Zurada
Editorial	Springer Verlag
Páginas	25-35
Número de páginas	11
ISBN (versión impresa)	9783319912615
DOI	https://doi.org/10.1007/978-3-319-91262-2_3
Estado	Publicada - 2018
Evento	17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018 - Zakopane, Polonia Duración: 3 jun. 2018 → 7 jun. 2018

Serie de la publicación

Nombre	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen	10842 LNAI
ISSN (versión impresa)	0302-9743
ISSN (versión digital)	1611-3349

Conferencia

Conferencia	17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018
País/Territorio	Polonia
Ciudad	Zakopane
Período	3/06/18 → 7/06/18

Nota bibliográfica

Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.

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10.1007/978-3-319-91262-2_3

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Gallegos Guillen, J. O., Estacio Cerquin, L. J., Obando, J. D., & Castro Gutierrez, E. G. (2018). Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance. En R. Tadeusiewicz, L. Rutkowski, W. Pedrycz, R. Scherer, M. Korytkowski, & J. M. Zurada (Eds.), Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings (pp. 25-35). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10842 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-91262-2_3

Gallegos Guillen, Joel Oswaldo ; Estacio Cerquin, Laura Jovani ; Obando, Javier Delgado et al. / Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance. Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. editor / Ryszard Tadeusiewicz ; Leszek Rutkowski ; Witold Pedrycz ; Rafal Scherer ; Marcin Korytkowski ; Jacek M. Zurada. Springer Verlag, 2018. pp. 25-35 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance",

abstract = "Using image processing to assist in the diagnostic of diseases is a growing challenge. Segmentation is one of the relevant stages in image processing. We present a strategy of complete segmentation of the proximal femur (right and left) in anterior-posterior pelvic radiographs using statistical models of shape and appearance for assistance in the diagnostics of diseases associated with femurs. Quantitative results are provided using the DICE coefficient and the processing time, on a set of clinical data that indicate the validity of our proposal.",

keywords = "AP X-ray, DICE coefficient, Gold standard, Segmentation, Statistical appearance models (SAM), Statistical shape models (SSM)",

author = "{Gallegos Guillen}, {Joel Oswaldo} and {Estacio Cerquin}, {Laura Jovani} and Obando, {Javier Delgado} and {Castro Gutierrez}, {Eveling Gloria}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018 ; Conference date: 03-06-2018 Through 07-06-2018",

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doi = "10.1007/978-3-319-91262-2_3",

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Gallegos Guillen, JO, Estacio Cerquin, LJ, Obando, JD & Castro Gutierrez, EG 2018, Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance. En R Tadeusiewicz, L Rutkowski, W Pedrycz, R Scherer, M Korytkowski & JM Zurada (eds.), Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10842 LNAI, Springer Verlag, pp. 25-35, 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018, Zakopane, Polonia, 3/06/18. https://doi.org/10.1007/978-3-319-91262-2_3

Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance. / Gallegos Guillen, Joel Oswaldo; Estacio Cerquin, Laura Jovani; Obando, Javier Delgado et al.
Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. ed. / Ryszard Tadeusiewicz; Leszek Rutkowski; Witold Pedrycz; Rafal Scherer; Marcin Korytkowski; Jacek M. Zurada. Springer Verlag, 2018. p. 25-35 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10842 LNAI).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance

AU - Gallegos Guillen, Joel Oswaldo

AU - Estacio Cerquin, Laura Jovani

AU - Obando, Javier Delgado

AU - Castro Gutierrez, Eveling Gloria

N1 - Publisher Copyright: © Springer International Publishing AG, part of Springer Nature 2018.

PY - 2018

Y1 - 2018

N2 - Using image processing to assist in the diagnostic of diseases is a growing challenge. Segmentation is one of the relevant stages in image processing. We present a strategy of complete segmentation of the proximal femur (right and left) in anterior-posterior pelvic radiographs using statistical models of shape and appearance for assistance in the diagnostics of diseases associated with femurs. Quantitative results are provided using the DICE coefficient and the processing time, on a set of clinical data that indicate the validity of our proposal.

AB - Using image processing to assist in the diagnostic of diseases is a growing challenge. Segmentation is one of the relevant stages in image processing. We present a strategy of complete segmentation of the proximal femur (right and left) in anterior-posterior pelvic radiographs using statistical models of shape and appearance for assistance in the diagnostics of diseases associated with femurs. Quantitative results are provided using the DICE coefficient and the processing time, on a set of clinical data that indicate the validity of our proposal.

KW - AP X-ray

KW - DICE coefficient

KW - Gold standard

KW - Segmentation

KW - Statistical appearance models (SAM)

KW - Statistical shape models (SSM)

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U2 - 10.1007/978-3-319-91262-2_3

DO - 10.1007/978-3-319-91262-2_3

M3 - Contribución a la conferencia

AN - SCOPUS:85048060813

SN - 9783319912615

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 25

EP - 35

BT - Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings

A2 - Tadeusiewicz, Ryszard

A2 - Rutkowski, Leszek

A2 - Pedrycz, Witold

A2 - Scherer, Rafal

A2 - Korytkowski, Marcin

A2 - Zurada, Jacek M.

PB - Springer Verlag

T2 - 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018

Y2 - 3 June 2018 through 7 June 2018

ER -

Gallegos Guillen JO, Estacio Cerquin LJ, Obando JD, Castro Gutierrez EG. Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance. En Tadeusiewicz R, Rutkowski L, Pedrycz W, Scherer R, Korytkowski M, Zurada JM, editores, Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. Springer Verlag. 2018. p. 25-35. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-91262-2_3

Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance

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