TY - GEN
T1 - Method for the automatic segmentation of the palpebral conjunctiva using image processing
AU - Delgado-Rivera, Gerson
AU - Roman-Gonzalez, Avid
AU - Alva-Mantari, Alicia
AU - Saldivar-Espinoza, Bryan
AU - Zimic, Mirko
AU - Barrientos-Porras, Franklin
AU - Salguedo-Bohorquez, Mario
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Conventional methods to diagnose anemia require a blood draw. This generates a great problem in patients due to the fear of contracting a disease through syringes, or sensitivity to this element. The palpebral conjunctiva is an indicator of diseases such as the hordeolum, chalazion, marginal blepharitis, bacterial conjunctivitis, trachoma, and anemia. The palpebral conjunctiva pallor is an indicator of anemia and if we wanted to develop an automatic system, for the non-invasive diagnosis of anemia based on the analysis of photographs of the palpebral conjunctiva, we would need algorithms for the segmentation and analysis of this membrane. In this sense, this research proposes and develops a method for the automatic segmentation of the palpebral conjunctiva using an Android application and image processing techniques. As a result, the success of this segmentation method is 92.2%.
AB - Conventional methods to diagnose anemia require a blood draw. This generates a great problem in patients due to the fear of contracting a disease through syringes, or sensitivity to this element. The palpebral conjunctiva is an indicator of diseases such as the hordeolum, chalazion, marginal blepharitis, bacterial conjunctivitis, trachoma, and anemia. The palpebral conjunctiva pallor is an indicator of anemia and if we wanted to develop an automatic system, for the non-invasive diagnosis of anemia based on the analysis of photographs of the palpebral conjunctiva, we would need algorithms for the segmentation and analysis of this membrane. In this sense, this research proposes and develops a method for the automatic segmentation of the palpebral conjunctiva using an Android application and image processing techniques. As a result, the success of this segmentation method is 92.2%.
KW - Android application
KW - Anemia
KW - Image processing
KW - Palpebral conjunctiva
KW - Segmentation method
UR - https://www.scopus.com/pages/publications/85062171155
U2 - 10.1109/ICA-ACCA.2018.8609744
DO - 10.1109/ICA-ACCA.2018.8609744
M3 - Contribución a la conferencia
AN - SCOPUS:85062171155
T3 - IEEE ICA-ACCA 2018 - IEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control: Towards an Industry 4.0 - Proceedings
BT - IEEE ICA-ACCA 2018 - IEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control
A2 - Duran-Faundez, Cristian
A2 - Lefranc, Gaston
A2 - Fernandez-Fernandez, Mario
A2 - Munoz, Carlos
A2 - Rubio, Ernesto
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control: Towards an Industry 4.0, ICA-ACCA 2018
Y2 - 17 October 2018 through 19 October 2018
ER -