Detection of Acetabulum Fractures Using X-Ray Imaging and Processing Methods Focused on Noisy Images

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

doi:10.1109/AICAI.2019.8701297

Detection of Acetabulum Fractures Using X-Ray Imaging and Processing Methods Focused on Noisy Images

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

Departamento Académico de Ingeniería de Sistemas e Informática

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Acetabulum fractures are a clinical problem that primarily affects people between the ages of 21 and 30. The incidence of this type of injury has increased due to accidents involving both immediate and late implications. The analysis of an x-ray image is the first step in evaluating this type of injury and determining the type of treatment the patient should undergo. Identifying if the traumatic injury is located in the pelvis, is an acetabular fracture or not, serves as a support for all those orthopedic surgeons who have to deal with this type of injury. A method of X-ray image processing was proposed using the Local Binary Pattern (LBP) feature extractor and the Support Vector Machine (SVM) classification method. Also, the use of pre-processing methods to improve image quality is a key contribution. The results show 80% accuracy in classification using the CLAHE preprocessing method.

Original language	English
Title of host publication	Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	296-302
Number of pages	7
ISBN (Electronic)	9781538693469
DOIs	https://doi.org/10.1109/AICAI.2019.8701297
State	Published - 26 Apr 2019
Event	2019 Amity International Conference on Artificial Intelligence, AICAI 2019 - Dubai, United Arab Emirates Duration: 4 Feb 2019 → 6 Feb 2019

Publication series

Name	Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019

Conference

Conference	2019 Amity International Conference on Artificial Intelligence, AICAI 2019
Country/Territory	United Arab Emirates
City	Dubai
Period	4/02/19 → 6/02/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Acetabulum fractures
CLAHE
LBP
SVM
X-ray

Access to Document

10.1109/AICAI.2019.8701297

Cite this

Castro Gutierrez, E. G., Estacio-Cerquin, L., Gallegos-Guillen, J., & Obando, J. D. (2019). Detection of Acetabulum Fractures Using X-Ray Imaging and Processing Methods Focused on Noisy Images. In Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019 (pp. 296-302). [8701297] (Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AICAI.2019.8701297

Castro Gutierrez, Eveling Gloria ; Estacio-Cerquin, Laura ; Gallegos-Guillen, Joel et al. / Detection of Acetabulum Fractures Using X-Ray Imaging and Processing Methods Focused on Noisy Images. Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 296-302 (Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019).

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abstract = "Acetabulum fractures are a clinical problem that primarily affects people between the ages of 21 and 30. The incidence of this type of injury has increased due to accidents involving both immediate and late implications. The analysis of an x-ray image is the first step in evaluating this type of injury and determining the type of treatment the patient should undergo. Identifying if the traumatic injury is located in the pelvis, is an acetabular fracture or not, serves as a support for all those orthopedic surgeons who have to deal with this type of injury. A method of X-ray image processing was proposed using the Local Binary Pattern (LBP) feature extractor and the Support Vector Machine (SVM) classification method. Also, the use of pre-processing methods to improve image quality is a key contribution. The results show 80% accuracy in classification using the CLAHE preprocessing method.",

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Castro Gutierrez, EG, Estacio-Cerquin, L, Gallegos-Guillen, J & Obando, JD 2019, Detection of Acetabulum Fractures Using X-Ray Imaging and Processing Methods Focused on Noisy Images. in Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019., 8701297, Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019, Institute of Electrical and Electronics Engineers Inc., pp. 296-302, 2019 Amity International Conference on Artificial Intelligence, AICAI 2019, Dubai, United Arab Emirates, 4/02/19. https://doi.org/10.1109/AICAI.2019.8701297

Detection of Acetabulum Fractures Using X-Ray Imaging and Processing Methods Focused on Noisy Images. / Castro Gutierrez, Eveling Gloria; Estacio-Cerquin, Laura; Gallegos-Guillen, Joel et al.

Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 296-302 8701297 (Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Obando, Javier Delgado

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Castro Gutierrez EG, Estacio-Cerquin L, Gallegos-Guillen J, Obando JD. Detection of Acetabulum Fractures Using X-Ray Imaging and Processing Methods Focused on Noisy Images. In Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 296-302. 8701297. (Proceedings - 2019 Amity International Conference on Artificial Intelligence, AICAI 2019). doi: 10.1109/AICAI.2019.8701297

Detection of Acetabulum Fractures Using X-Ray Imaging and Processing Methods Focused on Noisy Images

Abstract

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Keywords

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