Multi Features Based Approach for White Blood Cells Segmentation and Classification in Peripheral Blood and Bone Marrow Images

Mohammed Lamine Benomar 1 Amine Chikh 1 Xavier Descombes 2 Mourtada Benazzouz 1
2 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : This paper proposes a complete automated analysis system for white blood cells differential count in peripheral blood and bone marrow images in order to reduce the time and increase the accuracy of several blood disorders diagnosis. A new color transformation is proposed to highlight the white blood cells regions then a marker controlled watershed algorithm is used to segment the region we are interested in by introducing this transformation. The nucleus and cytoplasm are subsequently separated. In the identification step a set of color, texture and morphological features are extracted from both nucleus and cytoplasm regions. Next, the performances of the random forest classifier on a set of microscopic images are compared and evaluated. The provided results reveal high recognition accuracies for both segmentation and classification stage.
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Submitted on : Thursday, September 5, 2019 - 11:28:09 AM
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Mohammed Lamine Benomar, Amine Chikh, Xavier Descombes, Mourtada Benazzouz. Multi Features Based Approach for White Blood Cells Segmentation and Classification in Peripheral Blood and Bone Marrow Images. 2019. ⟨hal-02279352⟩

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