0000000000884566
AUTHOR
Tegolo D
Megakaryocytic features useful for the diagnosis of myeloproliferative disorders can be obtained by a novel unsupervised software analysis
An unsupervised method for megakaryocyte detection and analysis is proposed, in order to validate supplementary tools which can be of help in supporting the pathologist in the classification of Philadelphia negative chronic myeloproliferative disorders with thrombocytosis. The experiment was conducted on high power magnification photomicrographs taken from hematoxylin-and-eosin 3 µm thick sections of formalin fixed, paraffin embedded bone marrow biopsies from patients with reactive thrombocytosis or chronic myeloproliferative disorders. Each megakaryocyte has been isolated in the photos through an image segmentation process, mainly based on mathematical morphology and wavelet analysis. A se…
Complex objects classified by morphological shape analysis and elliptical Fourier descriptors
This chapter deals with the classification of complex objects by morphological shape analysis and elliptical Fourier descriptors. An unsupervised method has been proposed to identify components with specific shapes by a simple edge detector and to classify them via the description of their contours. A particular application has been arranged in order to evaluate the goodness of this approach when discriminating between normal and pathological human megakaryocytes. Alterations in these cells can occur in many pathological processes and in such cases the pattern, size and shape of the cytoplasm and/or of the nucleus are extremely varied.