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Biomedical subjects

J W Bacus

Publications and source records attributed to J W Bacus.

At least 37 records · Page 2Linked to original sources
PubMed1984

Scene-segmentation algorithm development using error measures.

Development of scene-segmentation algorithms has generally been an ad hoc process. This paper presents a systematic technique for developing these algorithms using error-measure minimization. If scene segmentation is regarded as a problem of pixel classification whereby each pixel of a scene is assigned to a particular object class, development of a scene-segmentation algorithm becomes primarily a process of feature selection. In this study, four methods of feature selection were used to develop segmentation techniques for cervical cytology images: (1) random selection, (2) manual selection (best features in the subjective judgment of the investigator), (3) eigenvector selection (ranking features according to the largest contribution to each eigenvector of the feature covariance matrix) and (4) selection using the scene-segmentation error measure A2. Four features were selected by each method from a universe of 35 features consisting of gray level, color, texture and special pixel neighborhood features in 40 cervical cytology images . Evaluation of the results was done with a composite of the scene-segmentation error measure A2, which depends on the percentage of scenes with measurable error, the agreement of pixel class proportions, the agreement of number of objects for each pixel class and the distance of each misclassified pixel to the nearest pixel of the misclassified class. Results indicate that random and eigenvector feature selection were the poorest methods, manual feature selection somewhat better and error-measure feature selection best. The error-measure feature selection method provides a useful, systematic method of developing and evaluating scene-segmentation algorithms.

Computers↗
PubMed1984

Malignant cell detection and cervical cancer screening.

A study was conducted to determine the isolated, single-cell detection characteristics of human observers as this information relates to cervical cancer screening. Two interrelated experiments were performed. First, the receiver operating characteristic (ROC) was obtained for slide screening. In this experiment, approximately 1,200 slides were examined. Second, ROCs were obtained for human observer cell discrimination, using a rating method. An individual's curves were computed, assuming a multiple decision criterion. In this experiment, 6,375 cells from the same specimens used in the slide screening experiment were studied. In both experiments, results were analyzed using a Gaussian signal-detection model. This approach provided analytical detection criteria and rigorous definition of ROCs. These experiments addressed the problem of where the screening information lies: (1) in individual cells alone or (2) with additional components in global or other a priori information. We quantified the detection requirements of (1) the Papanicolaou smear screening process, Az = 0.99, and (2) the capabilities of trained cytotechnologists on isolated single cells, Az = 0.87. System modeling using intermediate cell detection instead of "rare event" detection resulted in a reduction of the predicted number of cells required for analysis from approximately 60,000 to 750.

Female↗
PubMed1983

Red blood cell morphology in sickle cell anemia as determined by image processing analysis: the relationship to painful crises.

Red blood cell morphology was studied in the peripheral blood of adults with sickle cell anemia to determine if changes occur during painful crises. Image processing of the cells with an automated system of red blood cell analysis was used. Four groups of cells were observed: normocytes, macrocytes, target cells, and cells with the shape of irreversibly sickled cells. During asymptomatic periods, the percentages of these cells differed in each individual but were typical for that individual and generally were stable. During crises, macrocytosis occurred and the concentration of irreversibly sickled cells showed greater fluctuation. The macrocytosis most likely reflected a marrow response to increased hemolysis and demonstrated that the increased red blood cell destruction observed during pain crises may be more extensive than previously considered. Changes in the concentration of irreversibly sickled cells during crises were not consistent and could not be used as an indicator of a crisis. Image processing with automated red blood cell analysis allows for accurate assessment of all the morphologic groups of red blood cells in patients with sickle cell anemia and compares well with standard methods for measuring the concentration of irreversibly sickled cells.

Adult↗
PubMed1981

Microspectrophotometric studies of Romanowsky stained blood cells. II. Comparison of the performance of two standardized stains.

This paper describes a comparison of the performance of two standardized Romanowsky blood stains, namely those of Marshall et al. and Wittekind et al., both containing azure B and eosin alone. Stain performance is assessed objectively by the use of three complementary techniques, all based on the visible absorbance spectra of stained cellular substrates. The first of these techniques is a simple comparison of the shapes and heights of the absorbance spectra. The second technique uses the CIE Colorimetric System, and thus permits the quantitation of colour in a manner that agrees with human observation. CIE co-ordinates (chromaticity points, luminance) are calculated directly from absorbance spectra. The third technique is that of spectral subtraction, which yields a set of factors which describe the quantities of component dyes which are bound by the object. This technique, unlike the other two, requires a priori knowledge of the dyes used in the stains, and their spectra when bound to cellular substrates. Although the differences between the two methods are subtle, and hard for the subjective observer to define, the objective methods described here do show statistically significant differences. Wittekind's stain produces less intense staining, except for lymphocyte and monocyte cytoplasms. To the human eye, the differential coloration of these two substrates is more pronounced, but the difference between all nuclei and cytoplasm is less marked. The major difference in the uptake of dye components is in the small quantities of eosin dimer that are bound in this technique.

Blood Cells↗
PubMed1980

Assessment of the anemia of chronic disease by digital image processing of erythrocytes.

Eighteen patients with the anemia of chronic disease were studied to determine the usefulness and accuracy of image processing analysis of erythrocytes for diagnosis. Diagnostic tests used for comparison included estimates of serum ferritin, serum iron and iron-binding capacity, stainable marrow iron, and erythrocyte morphology as determined by standard methods. The findings show that the analyses obtained by image processing were diagnostic for 83% of the patients with chronic disease. Serum ferritin levels were supportive of diagnosis for 33% of the patients, and serum iron levels were useful for approximately 25% of the patients. Cell indices and marrow iron were of limited value. The study demonstrates that quantitative information obtained by digital image processing of erythrocytes can be very useful for the diagnosis of the anemia of chronic disease.

Anemia↗
PubMed1980

Microspectrophotometric studies of Romanowsky stained blood cells. I. Subtraction analysis of a standardized procedure.

This paper describes a microspectrophotometric study of blood smears stained by a simple, standardized Romanowsky technique, using only the dyes azure B and cosin. Absorbance spectra are presented for twenty-two classes of cellular object, and for the two dyes in solution, together with tabulations of spectral maxima, and suitable wavelengths for use in automated image processing. The colours of objects stained with azure B/eosin are discussed in terms of absorbance spectra. By a spectral subtraction technique, it is shown that the differential colouration of various cell structures may be explained satisfactorily in terms of the varying proportions of only four dye components. These are the monomers and dimers of azure B and eosin. Polymerization was found to occur both in solution and on binding to biopolymers. A similar analysis of a conventional Romanowsky stain would present much greater difficulties, due to the greater number of dye components, which, however, contribute little to the colours observed.

Azure Stains↗
PubMed1980

Quantitative measurement of red blood cell central pallor and hypochromasia.

A quantitataive definition and techniques of measurement for central pallor of red blood cells are proposed. These are based on high-resolution measurements of absorbance across the center of the cell. Thus, the measurements reflect both variations in cell thickness and hemoglobin concentration. Although contributions of thickness and concentration may differ in individual cells, to a first approximation, a specific cell may be considered as having a similar concentration of hemoglobin throughout, and thus the major contribution to the central pallor is that due to the difference in thickness between the edges of the cell and the center. The definition proposed expresses central pallor as the percentage volume of indentation, comparing the red cell to a disc of uniform absorbance equal to the maximum found at the cell edges. Population distributions of central pallor then provide a basis for quantitation of hypochromasia. The mean and standard deviation of such distributions are proposed as quantitative descriptors. Sample distributions from 27 normal persons, 8 patients with spherocytic anemia and 26 patients with iron deficiency anemia were studied.

Anemia, Hypochromic↗
PubMed1980

Quantitative morphological analysis of red blood cells.

Recently developed methods for making quantitative measurements of red cell morphology are described. High-speed image processing is used to make six simultaneous red cell measurements relating to size, hemoglobin content, central pallor, and shape. These measurements are combined objectively to subdivide red cells into five subpopulations and to characterize each subpopulation by its principal distributional parameters. Also, an objective assessment of the blood sample is made relative to the diagnosis of anemia. Results from five typically encountered blood conditions are presented and analyzed in detail to illustrate the various distributional parameters involved and to illustrate the potential of these new measurements to extract relevant diagnostic information.

Anemia↗
PubMed1979

Automated scene analysis of CT scans.

Since the advent of computed tomography, there has been an increasing realization that CT scans contain quantitative as well as qualitative information useful in the diagnostic process. Often however, the use of this information is impeded by the tedious manual outlining of the areas of interest in the scan. To alleviate this problem, we have developed a scene segmentation algorithm which will automatically delineate areas of interest in a CT scan. This procedure uses known information about the expected objects in the scan in conjuction with an algorithm to label those objects. The resultant scene segmentation divides the scan into four anatomical areas: skull, normal brain, high density lesions and CSF. After an area of interest is interactively selected by the clinician, volume, density or other quantitative measures may be computed. Limitations of the algorithm and its clinical applications are discussed.

Absorptiometry, Photon↗
PubMed1977

An automated method of differential red blood cell classification with application to the diagnosis of anemia.

A method of automated red cell analysis suitable for the rapid classification of large numbers of red cells from individual blood specimens has been developed, and preliminarily tested on normal bloods and clinically proven cases of anemias and red cell disorders. According to this method digital image processing techniques provide several features relating to shape and internal central pallor configurations of red cells. These features are used with a fully automated decision logic to rapidly provide a quantitative "red cell differential" analysis, a report of the percentage subpopulations of recognized categories of red cells. For each subpopulation, measurements of mean cell area, mean cell hemoglobin content and mean cell hemoglobin density are provided. The nine types of red cell disorders studied with this method were: (a) iron deficiency anemia, (b) the anemia of chronic disease, (c) beta-thalassemia trait, (d) sickle cell anemia, (e) hemoglobin C disease, (f) intravascular hemolysis, (g) hereditary elliptocytosis, (h) hereditary spherocytosis, and (i) megaloblastic anemia due to folic acid deficiency. Preliminary indications are that the red cell differential is useful in distinguishing between these conditions.

Anemia↗
PubMed1977

A multi-spectral approach for scene analysis of cervical cytology smears.

A multi-spectral approach for the scene analysis of cervical cytology smears, using multiple images of a scene digitized through suitably chosen color filters matched to the Papanicolaou stain, has been proposed here. This technique involves clustering of two-dimensional data for extracting cytoplasm of the epithelial cells. Its performance on an experimental data set of 233 scenes involving more than 10 types of normal and malignant epithelial cells has been compared with density and gradient thresholding techniques. This resulted in an approximate 83% rate of success compared to approximately 40% for the rest of the other techniques.

Cell Nucleus↗
PubMed1977

Automated classification of blood cell neutrophils.

The classification of white blood cell neutrophils into band neutrophils (bands) and segmented neutrophils (segs) is a subproblem of the white blood cell differential count. This classification problem is not well defined for at least two reasons: (a) there are no unique quantitative definitions for bands and segs and (b) existing definitions use the shape of the nucleus as the only discriminating criterion. When cells are classified on a slide, decisions are made from the two-dimensional views of these three-dimensional cells. A problem arises because the exact shape of the nucleus becomes indeterminate when the nucleus overlaps so that the filament is hidden. To assess the importance of this problem, this paper quantitates the classification errors due to overlapped nuclei (ON). The results indicate that, using only neutrophils without ON, the classification accuracy is 89%. For neutrophils with ON, the classification accuracy is 65%. This suggests a classification strategy of first classifying neutrophils into three categories: (a) bands without ON, (b) segs without ON and (c) neutrophils with ON. Category III can then be further classified into segs and bands by other stretegies.

Autoanalysis↗
PubMed1976

Image processing for automated erythrocyte classification.

Digital image processing and pattern recognition techniques were applied to determine the feasibility of a natural n-space subgrouping of normal and abnormal peripheral blood erythrocytes into well separated categories. The data consisted of 325 digitized red cells from 11 different cell classes. The analysis resulted in five features: (a) size, (b) roundness, (c) spicularity, (d) eccentricity and (e) central gray level distribution. These features separated the data into six distinct condensed subgroups of red cells. Each subgroup consisted of morphologically similar cells: (a) macrocytes, (b) normocytes, (c) schistocytes, acanthocytes and burr cells, (d) microcytes and spherocytes, (e) elliptocytes, sickle cells and pencil forms and (f) target cells. The concept of a quantitative "red cell differential" was introduced, utilizing these subgroup definitions to establish subpopulations of red cells, with quantifiable indices for the diagnosis of anemia, at the specimen level.

Autoanalysis↗