Publication: Megakaryocytic features useful for the
diagnosis of myeloproliferative disorders can
be obtained by a novel unsupervised software analysis
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Date
2006
Authors
Tripodo, C. ; Valenti, C. ; Ballarò, B. ; Rudzki, Z. ; Tegolo, D. ; Di Gesù, V. ; Florena, A.M. ; Franco, V.
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Publisher
Murcia : F. Hernández
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DOI
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info:eu-repo/semantics/article
Description
Abstract
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 set of
features (e.g. area, perimeter and fractal dimension of
the cell and its nucleus, shape complexity via elliptic
Fourier transform, and so on) is used to characterize the
disorders and discriminate between essential
thrombocythemia and idiopathic myelofibrosis. Features
related to the general contour of the cell like cytoplasmic
area and perimeter are good markers in distinguishing
between normal or reactive and pathologic
megakaryocytes while nuclear features and global
circularity are helpful in the differential diagnosis
between ET and prefibrotic IMF. The method proposed
should be considered as a fast preprocessing tool for the
diagnostic phase and its use can be extended to solve
different object recognition problems.
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