Biomedical subjects

J W Bacus

Publications and source records attributed to J W Bacus.

7 recordsLinked to original sources

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↗

PubMedDate not supplied

Error measures for objective assessment of scene segmentation algorithms.

Scene segmentation is an important element in pattern recognition problems. Previous efforts to evaluate and compare scene segmentation procedures have been largely subjective. Quantitative error measures would facilitate objective comparison of scene segmentation algorithms. A theoretical discussion leading to a new generalized quantitative error measure, G2, based on comparison of both pixel class proportions and spatial distributions of "true" and test segmentations, is presented. This error measure was tested on 14 manual segmentations and 40 gynecologic cytology specimens segmented with five different scene segmentation techniques. Results indicate that G2 seems to have the desirable properties of correlation with human observation, categorization of error allowing for weighting, invariance with picture size and ease of computation necessary for a useful scene segmentation error measure.

Autoanalysis↗

PubMedDate not supplied

Studies on Papanicolaou staining. I. Visible-light spectra of stained cervical cells.

This paper presents visible-light absorbance spectra of the nuclei and cytoplasms of ten types of cervical cells stained by the Papanicolaou technique, together with tables summarizing the data. It is concluded that for automated image processing of Papanicolaou smears the most suitable wavelengths are 531 nm to maximize the contrast of cell against background and a wavelength in the range 560 nm to 605 nm (with a mean at 575 nm) to maximize the contrast of the nucleus against the cytoplasm.

Carcinoma in Situ↗

PubMedDate not supplied

Studies on Papanicolaou staining. II. Quantitation of dye components bound to cervical cells.

Dye binding to Papanicolaou-stained cervical cells was quantitated with a spectral subtraction technique. It was shown that of the dye components of Papanicolaou stains only aluminum hematein, orange G, light green SF and eosin Y are bound to cervical cells and that their chromophores do not interact. Bismarck brown Y was not bound to cervical cells, which confirms the subjective findings of previous authors, and so it should be omitted. No evidence of substrate-related variations in dye polymerization was found. The proportions of the four dyes were found to vary considerably from substrate to substrate. Spectra are presented of (1) solutions of the component dyes of the Papanicolaou stain, and (2) cervical cells stained with these individual component dyes, for comparison with the full Papanicolaou technique.

Cell Nucleus↗