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A computer visual-input system for the automatic recognition of blood cells

University of British Columbia

A computer visual-input system was built for the purpose of studying the classification of leukocytes. It consisted of an image dissector camera interfaced directly to a D.E.C. PDP-9 computer; a display of the image field was also provided, using a monitoring scope. The design and hardware arrangement of the system is briefly described, while detailed diagrams of the logic networks are shown in Appendix II. Photomicrographs of neutrophils were used as a pattern set, in a study of the computer classification of cell age and lobularity. Clustering of feature vectors was noted in a two-dimensional measurement space showing that metamyelocyte, banded and segmented cells can be distinguished. A square contour-trace of the neutrophil nuclei was performed and an area operator pre-processed the shape of a nucleus into a curvature function. Peaks in this curvature function, a measure of lobularity, as well as the ratio of the perimeter to square root of nuclear area, a measure of the irregularity in the nuclear boundary, were used as orientation and size-independent features. The area operator was found to be unsuitable for extracting curvature from leukocyte images. In cases of extreme nuclear curvature and nuclear filamentation, the basic formulations of the operator were violated giving an erroneous measure of curvature. The general form of the frequency spectrum of the video signal from the image dissector camera was derived. The signal bandwidth requirements and the camera resolution were found experimentally.

Text

2011-05-25

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http://hdl.handle.net/2429/34860

Electrical and Computer Engineering

University of British Columbia

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