Blood morphology and image-based artificial intelligence 

Research projects



  • Development of an image-based blood cell recognition system for infectious diseases detection by means of machine learning techniques. Healthcare SLU. Project 2019-2021.


  • Characterization and automatic classification of leukemic cells by means of digital image processing and pattern recognition to support the diagnosis. Ministerio de Economía y Competitividad. Project 2014-2019.
PhD research project



  • Automatic classification of myeloid, monocytic, promyelocytic, and lymphoid blast cells. PhD research project by Laura Boldú, 2017-2020.


  • A deep learning system for the automatic classification of normal and dysplastic blood cells as a support tool for the diagnosis. PhD research project by Andrea Acevedo, 2016-2020.


  • New quantitative features for the morphologic characterization of normal, reactive and abnormal lymphoid cells and blast cells in peripheral blood through digital image analysis. PhD research project by Laura Puigví, 2016-2019.


  • A new segmentation framework for image analysis of malignant lymphoid cells in peripheral blood. Postdoctoral project by Santiago Alférez, 2016-2018.


  • A methodology for automatic classification of atypical lymphoid cells from peripheral blood by means of digital image processing and machine learning. PhD research project by Santiago Alférez, 2012-2015.