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Biomedical subjects

C MacAulay

Publications and source records attributed to C MacAulay.

7 recordsLinked to original sources
PubMed1992

Comparison of three different methods for automated classification of cervical cells.

Over 4600 exfoliated squamous cervical cells taken from appropriate Papanicolaou samples were classified as normal, mildly dysplastic, moderately dysplastic and severely dysplastic by an experienced cytopathologist. The slides were de-stained and subsequently re-stained with Feulgen Thionin-SO2 stain. Images of the nuclei were then captured, recorded and processed employing an image cytometry device. Automated classification of the cells was carried out using three different methods--discriminant function analysis, a decision tree classifier and a neutral network classifier. The discriminant function analysis method, which combined all dysplastic cells into an abnormal group, achieved a combined error rate of less than 0.4% for moderate and severe dysplastic cells, and less than 40% for mildly dysplastic cells. All three methods yielded comparable results, which approached those of human performance.

Cell Nucleus↗
PubMed1990

Fractal texture features based on optical density surface area. Use in image analysis of cervical cells.

The spatial distribution of the optical density of an image of a cell nucleus can be imagined to resemble a rugged surface in a three-dimensional space. The area of this surface can be measured using different unit-sized squares, yielding different values for the total area depending on the unit size. A fractal dimension can be calculated from the relationship between the unit size and the overall area measured; this fractal dimension is characteristic of the surface measured. This technique was applied to extract three new nuclear features from stained cervical cells. These new features were useful for the computer discrimination of normal and premalignant cervical cells. The features are defined, and their discriminating power is compared to that of some other nuclear features.

Cell Membrane↗
PubMed1990

An edge relocation segmentation algorithm.

An automated procedure that refines the nuclear contour of a previously segmented nucleus is described. The algorithm makes use of intensity information, edge magnitude information and both object and edge connectivity information. This automated procedure generates a closed contour precisely along the edge of the nucleus. The procedure was tested on a database of 3,680 red-green-blue images of thionin-SO2 and orange II-stained cervical cells obtained from normal and dysplastic samples. When used in conjunction with a simple threshold selection algorithm and an artifact removal routine, this edge relocation algorithm resulted in the correct segmentation of over 98% of the nuclei. Only 63 (1.7%) of all nuclei were incorrectly segmented.

Algorithms↗
PubMed1989

Adaptive color basis transformation. An aid in image segmentation.

Multispectral images of stained cells enable the use of color differences to segment and/or to discriminate between image components, such as cell types and cellular subcomponents. When the spectral characteristics of the image components do not change over the area of a slide or from slide to slide, one can create a constant weighted linear combination of spectral images to generate one-dimensional or two-dimensional images that have the desired contrast between the image components that must be discriminated. However, when the spectral characteristics are not constant, i.e., when they vary from image to image, a constant weighted linear combination cannot be employed; instead, an appropriate solution must be found for each selected image. This is usually a time-consuming, manual procedure that cannot be employed in a fully automated process of discriminating and segmenting stained cells. This paper describes an algorithm that uses principal components decomposition basis vectors to generate a nonstatic weighted linear combination of color images that can be used by an automated system. This algorithm relies on a semiconstant relationship between the areas (sizes) of the image components that are to be discriminated and/or segmented. The technique has been successfully applied as an aid in the segmentation of images of stained cervical smears; the images were acquired with a three-chip CCD camera that generates three broad-band color images.

Algorithms↗
PubMed1988

Imaging system for morphometric assessment of absorption or fluorescence in stained cells.

An image acquisition and processing system has been developed for quantitative microscopy of absorption or fluorescence in stained cells. Three different light transducers are used in the system to exploit the best characteristics of these sensors for different biological measurements. A digital scanner, in the form of a linear array charge-coupled device (CCD), acquires data with high spatial and photometric resolution. A color (RGB) camera is employed when spectral information is required for the segmentation of cellular subcomponents. An image-intensified charged-injection device (CID) camera provides for very low light intensity measurements, primarily for fluorescence-labeled cells. Properties of these transducers, such as contrast transfer function, linearity, and photo-response nonuniformity, have been measured. Two dedicated image processing units were incorporated into the system. The front-end processor, based on a digital signal processor, provides functions such as object detection, raw image calibration, compression, artifact removal, and filtering. The second image processor is associated with the frame memory and includes a histogram processor, a dedicated arithmetic logic unit for image processing functions, and a graphics module for one-bit overlay functions. An interactive program was developed to acquire cell images and to experiment with a range of segmentation algorithms, feature extractions, and other image processing functions. The results of any image operation are displayed on the video monitor. Once a desired processing sequence is determined, the sequence may be stored to become part of a command library and can be executed thereafter as a single instruction.

Algorithms↗
PubMed1988

A comparison of some quick and simple threshold selection methods for stained cells.

The segmentation accuracy of four fast and simple gray-scale threshold selection methods were compared using a data base of stained cervical cell images. Some postprocessing was applied to the segmented images to increase the accuracy of the nuclear segmentation. The most accurate method correctly segmented the cytoplasm of 81% of the cell images and the nuclei of 78% of the cell images in the data base.

Algorithms↗