Search PubMed⌕ Search

Biomedical subjects

H M Aus

Publications and source records attributed to H M Aus.

11 recordsLinked to original sources
PubMed1990

Automated recognition of cell images in high grade malignant lymphoma and reactive follicular hyperplasia.

In the past, the comparison of results of studies on malignant lymphomas has been biased by the use of different classifications of the diseases and to an even greater extent by subjective interpretation in the classification of the tumour cells. To overcome these short-comings, we have developed cytometric features specifically for automated recognition of cell images from high grade malignant non-Hodgkin's lymphomas (NHL) and reactive lymphoid lesions. This study used a colour TV-microscope system, high resolution scanning (13.3 pixel/microns), and image processing to study a total of 3600 lymphoid cells from 15 high grade malignant NHL and three tonsils. Sixteen out of 64 features, especially developed for image analysis in cytological preparations, have been evaluated. Because of a considerable overlap of all the single features, no feature on its own allows reliable discrimination. But, multivariant analysis of suitable feature combinations resulted in reliable identification and discrimination of the most frequently occurring cell types. We show that the lymphocytes, centrocytes, centroblasts, immunoblasts and lymphoblasts, as they are defined by subjective morphological criteria in the Kiel-classification of malignant NHL, also form distinctive subpopulations on the basis of their objective mathematical cell features. Furthermore, we have shown that there are distinctive differences between the lymphoma cells and their benign counterparts derived from reactive lymphoid lesions.

Diagnosis, Differential↗
PubMed1987

On-line transmission electron microscopic image analysis of chromatin texture for differentiation of thyroid gland tumors.

Nuclei of the cells from the thyroid gland were analyzed in a transmission electron microscope by direct TV scanning and on-line image processing. The method uses the advantages of a visual-perception model to detect structures in noisy and low-contrast images. The features analyzed include area, a form factor and texture parameters from the second derivative stage. Three tumor-free thyroid tissues, three follicular adenomas, three follicular carcinomas and three papillary carcinomas were studied. The computer-aided cytophotometric method showed that the most significant differences were the statistics of the chromatin texture features of homogeneity and regularity. These findings document the possibility of an automated differentiation of tumors at the ultrastructural level.

Adenocarcinoma↗
PubMed1986

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.

Cell Nucleus↗
PubMed1986

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.

Blood Cells↗
PubMed1985

Computer-based cytophotometric classification of thyroid tumors in imprints.

This study of 14 follicular adenomas, 10 papillary carcinomas and 11 follicular carcinomas of the human thyroid gland demonstrates the possibility of a cytological tumor classification using digital picture processing. Routinely prepared, HE-stained imprints of surgical specimens were scanned under a light microscope at high resolution with a colour TV camera. The cell nuclei were segmented and analysed with an image processing system. The computer-aided cytophotometric methods detected the most significant differences in the chromatin texture with a criteria variance of texture line distances and texture points per texture knots. Using these criteria benign and malignant tumor types could be successfully differentiated.

Adenocarcinoma↗
PubMed1979

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.

Blood Cells↗
PubMed1979

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.

Animals↗
PubMed1977

Bone marrow cell scene segmentation by computer-aided color cytophotometry.

Computer scene segmentation of touching cell images in bone marrow, on the basis of color information, is achieved using digitized scans at three different wavelengths of light. With trivariate histograms and Euler's coordinate transformation, it is possible cytophotometrically to isolate, on the basis of chromatic differences, individual heterogeneous cells located in cell groups. The ability of the described computer methods to isolate correctly the touching cell images is determined by visual comparison of the cells as seen in the microscope and the computer-generated displays of the scanned and segmented scenes.

Bone Marrow Cells↗