Computer aided analysis of chromatin network and basophil color for differentiation of mononuclear peripheral blood cells.

Computer aided differentiation of plasmoblasts, Pfeiffer cells, immunoblasts, lymphocytes and centrocytes is achieved with the parameters of chromatin network arrangement and structure, and multispectral cytoplasm color. The digital methods involve: (a) segmenting the nuclear image into topographic sections and analyzing the optical density distribution from the chromatin in these sections; (b) determining the nuclear structure with a 7 x 7 median filter, gradient filter and contour following algorithms; and (c) clustering two-dimensional chromatic data from panoptically stained cellular components. The parameters reported here are a subset of those needed for the automated diagnosis of many hematologic diseases especially the leukemias.

Automated quantitative analysis of single and double label autoradiographs.

A method for the analysis of silver grain content in both single and double label autoradiographs is presented. The total grain area is calculated by counting the number of pixels at which the recorded light intensity in transmission dark field illumination exceeds a selected threshold. The calibration tests included autoradiographs with low (3H-thymidin) and high (3H-desoxyuridin) silver grain density. The results are proportional to the customary visual grain count. For the range of visibly countable grain densities in single labeled specimens, the correlation coefficient between the computed values and the visual grain counts is better than 0.96. In the first emulsion of the two emulsion layer autoradiographs of double labeled specimens (3H-14C-thymidin) the correlation coefficient is 0.919 and 0.906. The method provides a statistical correction for the background grains not due to the isotope. The possibility to record 14C tracks by shifting the focus through the second emulsion of the double labeled specimens is also demonstrated. The reported technique is essentially independent of size, shape and density of the grains.

Segmentation of stained blood cell images measured at high scanning density with high magnification and high numerical aperture optics.

In hematological morphology, it is necessary to resolve and analyze the smallest possible cellular details appearing in the light microscope. A prerequisite for computer-aided analysis of subtle morphological features is measuring the cells at a high scanning density with high magnification and high numerical aperture optics. Contrary to visual observations, the information content in a measured picture can be increased by setting the condensor's numerical aperture (NA) greater than the objective's NA. The complexity and heterogeneity of such cell images necessitate a new segmentation method that conserves the morphological information required in the subsequent image analysis, feature extraction, and cell classification. In our segmentation strategy, characteristic color difference thresholds for each nucleus and cytoplasm are combined with geometric operations, probability functions, and a cell model. All thresholds are repeatedly recalculated during the successive improvements of the image masks. None of the thresholds are fixed. This strategy segments blood cell images containing touching cells and large variations in staining, texture, size, and shape. Biological inconsistencies in the calculated cell masks are eliminated by comparing each mask with the cell model criteria integrated into the entire segmentation process. All 20,000 leukocyte images from 120 smears in our leukemia project were segmented with this method.

Computer-aided image analysis for the differentiation of mononuclear cells in peripheral blood smears from leukemic patients.

Different leukemias originating from the lymphatic system and from the myeloid tissue of the bone marrow were selected to develop and test algorithms to cytophotometrically define leukemic cells. Two of these cases were of low-grade, one of intermediate-grade and one of high-grade malignancy. The malignant cell types of each leukemic form could be identified and characterized by assessing the chromatin texture of the nucleus in the leukemic cells. With this method, normal peripheral white blood cells could be differentiated from leukemic ones. The results correlate directly with established hematologic parameters as they are described in the literature. The investigation demonstrated the usefulness of computer methods in the differentiation of closely related cell structures.

Evidence for non-random sequence of centromere separation in muntjak chromosomes by high resolution TV-microscopy.

The sequence of separation of sister centromeres in the chromosomes of the muntjak was analysed using a high resolution TV-microscope-system. Computer programs which permit the identification of the individual chromosome pairs and the measurement of the distances between the sister centromeres are described. The study demonstrates that the centromeres do not separate in a random sequence. It could be shown that the amount of pericentromeric heterochromatin participates in the control of centromere separation; however, other factors must also be involved. The significance of the asynchronous division of centromeres in the origin of aneusomic cells in mammals is discussed.

Application of a high-resolution TV-microscope system to estimate the sequence of centromere separation in muntjak chromosomes.

The sequence of centromere separation in muntjak fibroblasts was studied using a high-resolution TV-microscope system. Computer programs that identify the chromosomes as well as measure the centromere separation are described. Important prerequisites for this study are the high sampling rate and the digital processing of the two images from the red and green channel of a color TV-camera. The study demonstrates that the centromeres do not separate in a random sequence and that the separation sequence is not solely controlled by the amount of constitutive heterochromatin in the chromosomes.

Leukemia-related morphological features in blast cells.

This paper investigates the use of image-processing methods to detect leukemia-related morphological differences in mononuclear blast cells. Routinely prepared Pappenheim-stained blood smears were scanned in a high-resolution color TV-microscope system. Eleven blast-cell classes (OMSBC, T-ALL, OMS, ALL, LBL, IBL, AUL, AML, AMOL, AMMOL, and CML) were analyzed with the nonparametric statistical software program "Classification and Regression Trees" (CART). This paper documents the initial statistical evaluation of 62 leukemia-related morphological features that directly measure and analyze the cell-related quantifiable differences occurring in the various blast cells. The 62 cell image features include both common cytophotometric features, and new texture and color features developed for this project. This study found that each leukemia specimen contains a dominant class of blasts that correlates with the specific leukemia, plus a distribution of blasts from related diseases. The present data suggest the existence of a distribution fingerprint pattern for each leukemia.

Computer analysis of chromatin arrangement and nuclear texture in follicular thyroid tumours.

The differentiation of the thyroid glands follicular neoplasias into adenomas and carcinomas is currently done using the histological criteria recommended by WHO. This pilot study of 10 human follicular carcinomas and 10 folliculars adenomas demonstrates the possibility of a cytological classification using digital picture processing of high resolution cell images. Giemsa stained paraplast sections were scanned with a Colour-TV-camera, different channels were used with respect to staining and analyzing methods and computed with an image processing system. The computer aided cytophotometric methods detected significant differences in the chromatin arrangement and structure.