A Manual of Morphometry in Diagnostic Pathology by Jan P. A. Baak M.D., Ph.D., Jan Oort M.D., Ph.D. (auth.)

By Jan P. A. Baak M.D., Ph.D., Jan Oort M.D., Ph.D. (auth.)

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8: 209-215. , Kaam H. , Leach, A. P A. (1982a). Morphometry and cytodiagnosis of breast lesions. Virchows Arch. (PathoI. ) 369, 9-18. J. A. {1982b}. Computation of pre-operative diagnosis probability for follicular adenoma and carcinoma of the thyroid on aspiration smears. Quant. Anal. Cytol. 4,1-5. G. L. (1974). The identification and follow-up of high. risk infants. R. Robinson, editor, London and Toronto, Foundation for the study of infant death, pp. 91-96. W. R. (1971). Multivariate data analysis.

Acta Cytol. 12, 180-204. G. H. (1969a). Computer-assisted identification of cells from uterine adenocarcinoma. A clinical feasibility study with TICAS 1. Measurements at wavelength 530 nm. Acta Cytol. 12,357-370. G. H. (1969b). Computer-assisted identification of cells from uterine adenocarcinoma. II. Measurements at 590 nm. Acta Cytol:B, 21-26. F. H. (1970). Automatic analyses of cellular images by TICAS. L. F. Bahr, editors, Academic Press, New York, pp. 195-368. T. (1970). Automated leukocyte recognition.

The decisions are taken se- quentially. 31 Mucinous ovarian tumour no Take other samples yes Select area with highest tumour grade yes Malignant tumour yes Borderline tumour Fig. 4. A more complex decision tree (after Hart and Norris, 1973).. 6 Multivariate Analysis The second type of discrimination considers the discriminating power of several features simultaneously. Such a simultaneous combined consideration of two or more features, which as single features may show a considerable overlap, may result in improved discrimination and thus in a higher percentage of correctly classified cases.

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