Dr. Luisa Sánchez Brea

Luisa Sánchez Brea

Office: Na 25-12
Phone: +31-10-7044886
Email: m.sanchezbrea@erasmusmc.nl

Curriculum Vitae

Luisa Sánchez Brea received her PhD in Computer Science at University of A Coruña in 2018. She worked with the Artificial Vision and Pattern Recognition Group (VARPA) since 2013 on different image processing tasks involving ophthalmic imaging. Her main research interests are machine learning and image processing.

She is now working as a posdoc researcher in the Biomedical Imaging Group Rotterdam (since June 2018), as a part of the Merlin project.

Research lines

Image Registration Image guidance in interventions and therapy

Projects

MERLIN

Publications

Journal Articles

  1. Brea, L. S., Rodríguez, N. B., González, A. M., Pena-Verdeal, H., & Vilar, E. Y.-P. (2018). Precise segmentation of the bulbar conjunctiva for hyperaemia images. Pattern Analysis and Applications, 21(2), 563–577.
  2. Brea, M. L. S., Rodríguez, N. B., Maroño, N. S., González, A. M., García-Resúa, C., & Fernández, M. J. G. (2016). On the development of conjunctival hyperemia computer-assisted diagnosis tools: Influence of feature selection and class imbalance in automatic gradings. Artificial Intelligence in Medicine, 71, 30–42.
  3. Sánchez Brea, M. L., Barreira Rodríguez, N., Mosquera González, A., Evans, K., & Pena-Verdeal, H. (2016). Defining the optimal region of interest for hyperemia grading in the bulbar conjunctiva. Computational and Mathematical Methods in Medicine, 2016.

Conference Articles

  1. Brea, L. S., Rodríguez, N. B., González, A. M., & Evans, K. (2017). Assessment of the repeatability in an automatic methodology for hyperemia grading in the bulbar conjunctiva. In Neural Networks (IJCNN), 2017 International Joint Conference on (pp. 1673–1680). IEEE.
  2. Brea, L. S., Barreira, N., Sánchez, N., Mosquera, A., García-Resúa, C., & Yebra-Pimentel, E. (2016). On the analysis of feature selection techniques in a conjunctival hyperemia grading framework. In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
  3. Sánchez Brea, L., Barreira, N., Pena-Verdeal, H., & Yebra-Pimentel, E. (2015). A novel framework for hyperemia grading based on artificial neural networks. In International Work-Conference on Artificial Neural Networks (pp. 263–275). Springer.

Book Chapters

  1. Remeseiro, B., Barreira, N., Sánchez-Brea, L., Ramos, L., & Mosquera, A. (2018). Machine Learning Applied to Optometry Data. In Advances in Biomedical Informatics (pp. 123–160). Springer.