Current position

Education

• Master in Electronic Engineering, Industrial University of Santander, Colombia (2009).
• Degree in Electronic Engineering, Industrial University of Santander, Colombia (2004).

Research interests

My research is focused on Machine learning, deep learning and its applications in classification of abnormal lymphoid cells from peripheral blood digital images as a support in hematological diagnosis. This research is being carried out due to the cooperation between the Hospital Clinic of Barcelona and codalab group. I am also interested in applying convolutional neural networks and algorithms for classification when there is little data.

Awards

Publications

Journal Articles

Acevedo, A., Alférez, S., Merino, A., Puigví, L., & Rodellar, J. (2019). Recognition of peripheral blood cell images using convolutional neural networks,Computer Methods and Programs in Biomedicine, Volume 180, 2019, 105020 ISSN 0169-2607, https://doi.org/10.1016/j.cmpb.2019.105020

Boldú, L., Merino, A., Alférez, S., Molina, Á., Acevedo, A., & Rodellar, J. (2019). Automatic recognition of different types of acute leukaemia in peripheral blood by image analysis. Journal of Clinical pathology. doi:10.1136/jclinpath-2019-205949.

Puigví, L., Merino, A., Alférez, S., Boldú, L., Acevedo, A., & Rodellar, J. (2019). Quantitative cytologic descriptors to differentiate cll, sézary, granular, and villous lymphocytes through image analysis. American Journal of Clinical pathology, 152, 74–85. doi:10.1093/ajcp/aqz025.

Alférez, S., Merino, A., Acevedo, A., Puigví, L., & Rodellar, J. (2018). Colour clustering segmentation framework for image analysis of malignant lymphoid cells in peripheral blood. Medical & Biological Engineering & Computing. doi:10.111/ijlh.12818.

Rodellar, J., Alférez, S., Acevedo, A., Molina, A., & Merino, A. (2018). Image processing and machine learning in the morphological analysis of blood cells. International journal of laboratory hematology, 40, 46–53. doi:10.111/ijlh.12818.

Puigví, L., Merino, A., Alférez, S., Acevedo, A., & Rodellar, J. (2017). New quantitative features for the morphological differentiation of abnormal lymphoid cell images from peripheral blood. Journal of clinical pathology, 70(12), 1038–1048. doi:10.1136/jclinpath-2017-204389.

Conference Proceedings

Acevedo, A., Merino, A., Alférez, S., Boldú, L., Molina, Á., & Rodellar, J. (2019). Automatic detection of dysplastic cells using deep learning. International journal of laboratory hematology (Vol. 41). Abstract Proceedings of the 2019 Annual Meeting of the International Society for Laboratory Hematology.

Acevedo, A., Merino, A., Alférez, S., Puigví, L., & Rodellar, J. (2018). Training a convolutional neural network for automatic classification of peripheral blood cells. International journal of laboratory hematology (Vol. 40). Abstract Proceedings of the 2018 Annual Meeting of the International Society for Laboratory Hematology.

Alférez, S., Merino, A., Puigví, L., Boldú, L., Acevedo, A., & Rodellar, J. (2018). Automatic recognition of acute leukemia from peripheral blood smears. International journal of laboratory hematology (Vol. 40). Abstract Proceedings of the 2018 Annual Meeting of the International Society for Laboratory Hematology.

Boldú, L., Alférez, S., Puigví, L., Acevedo, A., Rodellar, J., & Merino, A. (2018). Definition of new quantitative features for the automatic classification of blast cells in peripheral blood by image analysis. International journal of laboratory hematology (Vol. 40). Abstract Proceedings of the 2018 Annual Meeting of the International Society for Laboratory Hematology.

Puigví, L., Merino, A., Redin, M., Alférez, S., Boldú, L., Acevedo, A., & Rodellar, J. (2018). Quantitative features in peripheral blood cell images obtained by different hospitals and acquisition methods: utility for reactive and neoplastic lymphoid cell discrimination. International journal of laboratory hematology (Vol. 40). Abstract Proceedings of the 2018 Annual Meeting of the International Society for Laboratory Hematology.

Acevedo, A., Alférez, S., Merino, A., Puigví, L., & Rodellar, J. (2017). Automatic recognition system of peripheral blood cell images using deep features. Abstract presented at IEEE International Symposium on Biomedical Imaging – ISBI 2017.

Alférez, S., Merino, A., Puigví, L., Raris, S., Acevedo, A., & Rodellar, J. (2017). Automatic cell recognition of abnormal cells in peripheral blood using digital images obtained by a conventional microscope. International journal of laboratory hematology (Vol. 39). Abstract Proceedings of the 2017 Annual Meeting of the International Society for Laboratory Hematology.

Merino, A., Alférez, S., Puigví, L., Acevedo, A., & Rodellar, J. (2017). Detection of the presence of blasts, atypical promyelocytes, abnormal and reactive lymphoid cells in peripheral blood using image analysis. International journal of laboratory hematology(Vol. 39). Abstract Proceedings of the 2017 Annual Meeting of the International Society for Laboratory Hematology.

Acevedo, A., Alférez, S., Merino, A., Puigví, L., & Rodellar, J. (2016). Automatic recognition system of nucleated peripheral blood cell images.  International journal of laboratory hematology (Vol. 38). Abstract Proceedings of the 2016 Annual Meeting of the International Society for Laboratory Hematology.

Alférez, S., Merino, A., Acevedo, A., Puigví, L., & Rodellar, J. (2016). Automatic classification of normal, reactive lymphocytes, abnormal lymphoid cells and blast cells. International journal of laboratory hematology (Vol. 38). Abstract Proceedings of the 2016 Annual Meeting of the International Society for Laboratory Hematology.

Puigví, L., Merino, A., Alférez, S., Acevedo, A., & Rodellar, J. (2016). Analysis of the most relevant quantitative features for the automatic differentiation of normal, reactive, abnormal lymphoid cell images and blast cell images from peripheral blood. International journal of laboratory hematology (Vol. 38). Abstract Proceedings of the 2016 Annual Meeting of the International Society for Laboratory Hematology.

Research Projects