This paper presents a comparison between two different Computer Aided Diagnosis systems for classification of five types of leucocytes located in the tail of a Peripheral Blood Smears: Lymphocytes, Monocytes, Neutrophils, Basophils and Eosinophils. In particular, we have evaluated and compared the performance of a previous feature-based Back Propagation Neural Network classifier with the performance of two novel classifiers both based on Deep Learning using Convolutional Neural Networks introduced in this study. All the classifiers are built considering the same dataset of images acquired in a previous study. The experimental results, reported in terms of accuracy, sensitivity, specificity and precision, show that the different strategies could be compared and discussed from both clinical and technical point of view.

A novel deep learning approach in haematology for classification of leucocytes / Bevilacqua, Vitoantonio; Brunetti, Antonio; Trotta, Gianpaolo Francesco; De Marco, Domenico; Quercia, Marco Giuseppe; Buongiorno, Domenico; D’Introno, Alessia; Girardi, Francesco; Guarini, Attilio. - STAMPA. - 103:(2019), pp. 265-274. [10.1007/978-3-319-95095-2_25]

A novel deep learning approach in haematology for classification of leucocytes

Bevilacqua, Vitoantonio;Brunetti, Antonio;Trotta, Gianpaolo Francesco;Quercia, Marco Giuseppe;Buongiorno, Domenico;
2019-01-01

Abstract

This paper presents a comparison between two different Computer Aided Diagnosis systems for classification of five types of leucocytes located in the tail of a Peripheral Blood Smears: Lymphocytes, Monocytes, Neutrophils, Basophils and Eosinophils. In particular, we have evaluated and compared the performance of a previous feature-based Back Propagation Neural Network classifier with the performance of two novel classifiers both based on Deep Learning using Convolutional Neural Networks introduced in this study. All the classifiers are built considering the same dataset of images acquired in a previous study. The experimental results, reported in terms of accuracy, sensitivity, specificity and precision, show that the different strategies could be compared and discussed from both clinical and technical point of view.
2019
Quantifying and Processing Biomedical and Behavioral Signals
978-3-319-95094-5
Springer
A novel deep learning approach in haematology for classification of leucocytes / Bevilacqua, Vitoantonio; Brunetti, Antonio; Trotta, Gianpaolo Francesco; De Marco, Domenico; Quercia, Marco Giuseppe; Buongiorno, Domenico; D’Introno, Alessia; Girardi, Francesco; Guarini, Attilio. - STAMPA. - 103:(2019), pp. 265-274. [10.1007/978-3-319-95095-2_25]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/138424
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