TY - JOUR
T1 - Classification of lymphoproliferative disorders by spectral imaging of the nucleus
AU - Greenspan, Hayit
AU - Rothmann, C.
AU - Cycowitz, T.
AU - Nissan, Y.
AU - Cohen, A. M.
AU - Malik, Z.
PY - 2002
Y1 - 2002
N2 - Spectral nuclear morphometry was used for the classification of lymphocytes in lymphoproliferative disorders. May-Grunwald-Giemsa-stained blood specimens were taken from thirty patients with infectious mononucleosis, non-Hodgkin lymphoma or chronic lymphocytic leukemia, and from ten healthy individuals. Blood specimens were analyzed by spectral imaging. Seventeen distinct spectra were collected into a spectral library and a distinct pseudo color was assigned to each one of them. The library was used to scan all the cells in the database and to create a spectrally classified image of each cell. The spectral map, per cell, reveals distinct spectral-response regions in each cellular compartment, via the distinct region colors. Computational analysis of the spectral maps allows for the objective quantification of a set of parameters, or features, representing the cell. The features used in this work include the area and perimeter of the nucleus, circularity, edginess and the spectral pattern. The analysis pursued showed that each class of cells is associated with a set of unique parameters. We conclude that spectral analysis combined with feature analysis provides significant information in the analysis of lymphoproliferative disorders and may serve as an additional tool for the histopathological evaluation of disease.
AB - Spectral nuclear morphometry was used for the classification of lymphocytes in lymphoproliferative disorders. May-Grunwald-Giemsa-stained blood specimens were taken from thirty patients with infectious mononucleosis, non-Hodgkin lymphoma or chronic lymphocytic leukemia, and from ten healthy individuals. Blood specimens were analyzed by spectral imaging. Seventeen distinct spectra were collected into a spectral library and a distinct pseudo color was assigned to each one of them. The library was used to scan all the cells in the database and to create a spectrally classified image of each cell. The spectral map, per cell, reveals distinct spectral-response regions in each cellular compartment, via the distinct region colors. Computational analysis of the spectral maps allows for the objective quantification of a set of parameters, or features, representing the cell. The features used in this work include the area and perimeter of the nucleus, circularity, edginess and the spectral pattern. The analysis pursued showed that each class of cells is associated with a set of unique parameters. We conclude that spectral analysis combined with feature analysis provides significant information in the analysis of lymphoproliferative disorders and may serve as an additional tool for the histopathological evaluation of disease.
KW - Chronic lymphocytic leukemia
KW - Infectious mononucleosis
KW - Lymphocytes
KW - Non-Hodgkin's lymphoma
KW - Spectral imaging
UR - http://www.scopus.com/inward/record.url?scp=0036067799&partnerID=8YFLogxK
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AN - SCOPUS:0036067799
SN - 0213-3911
VL - 17
SP - 767
EP - 773
JO - Histology and Histopathology
JF - Histology and Histopathology
IS - 3
ER -