Abstract: Coverslip detection locating all four coverslip edges. A field of view processor receives image data from a charge coupled device camera. The charge coupled device camera images a slide and coverslip that is mounted on a movable frame. The slide and coverslip are illuminated from below with a uniform light source. The moveable frame is under computer control and moves in response to the field of view processor. The field of view processor locates the coverslip by first positioning the movable frame to view a portion of the slide on a predetermined potion of the slide within a predetermined area of the slide. The slide is then re-imaged after the movable frame moves the slide toward a chosen edge of direction. Edge type objects are located and followed over multiple fields of view. If the edge object satisfies a set of predetermined criteria the coverslip edge has been found. The edge is extended to find all four corners of the coverslip. The edge objects are processed using morphological operators.

Abstract: A computer aided biological specimen screener is responsive to a priori information about biological specimens. An automated slide classifier scans a slide specimen and generates a set of scores. The classification which results from this set of scores depends on a priori information concerning the patient, such as patient age and prior health history and diagnosis. Using the patient information and an appropriate score, the specimen is classified. A normal threshold used for classification is changed over a wide range depending on the specificity appropriate to a particular patient risk category. The sensitivity of the classification is automatically maximized for a predetermined normal specificity.

Abstract: An automatic screening apparatus that screens all pap smear slides called normal by cytotechnologist. These normal pap smears will contain the mistakes, false negatives, which must be recovered as a measure of the cytotechnologist's performance. Additionally, these mistakes must be discovered to improve the quality of the laboratory services. The automated screening machine after rescreening the normals, rank orders of the pap smears with those "normals" most likely to be missed ranked at the top. Another human screener re-examines those pap smears with high ranking to determine if the first human screener misclassified the pap smear. Mistakes are recovered and the performance of the first screener is assessed. Proficiency testing is accomplished with 100% quality control.

Abstract: A network system for review and analysis of computer encoded microscope slides and specimens which were originally computer encoded from a microscope (attached via an encoder device to a local computer site), during an initial examination. The encoding includes parameters of viewing locations and events of interest on the slide, with such information being stored on a networked file server. The encoding also includes information regarding the manner in which the initial examination was conducted, for quality control purposes. The computer encoded information is retrievable at all remote locations of the network (either local or connected via modem) for supervisor review or for pathologist analysis. The network is further constituted by microscope sites having similar computer encoding devices attached thereto, which function, in this aspect, as computer terminals of the network. For enhanced analysis, the computer terminals have direct access to patient background information, e.g.

Abstract: A computerized slide encoder for use with microscope analysis and pathological studies is provided. The slide encoder is attached to the movable microscope stage, whereby x-y direction plane movement and location, is correlated to examination of an identified slide, with information marking and location being directly correspondingly written, at pre-defined times, on computer storage media, during the examination. Subsequent use of the computer-stored information, coupled with the slide encoder, in a slide re-examination, permits independent retrieval of such information and location on the slide. The computer storage media includes digitized vocal transcription of history of the slide made during the original examination. An embodiment of the slide encoder includes a computer mouse pen affixed to the stage of the microscope and a rolling surface, for the mouse pen, being affixed to the movable slide holder.

Abstract: Reference information for a biological slide is obtained. The reference information normalizes the measured object features. Calibrated feature measurement, not based on absolute measurements, self adjusts to match the situation of each slide, where each slide is characterized by the reference information. The reference may be different from slide to slide because of the preparation variations. The calibrated features will not carry the inter-slide variations. In addition, the reference information provides a good indication of the slide condition such as dark stained, air dried, etc. which can be used as slide features for the specimen classification. No alteration of the current practice of specimen preparation is required. The many slide context dependent features improve the classification accuracy of the objects in a specimen.

Abstract: Image enhancement for a digital image, such as an image of a biological specimen mounted on a microscope slide or a cytological specimen is herein described. A digital representation of the image is dilated to produce a dilated image and eroded to provide an eroded image. The dilated image, eroded image and the digital representation of the image are then processed to produce an enhanced image.

Abstract: Method and apparatus for identifying normal biomedical specimens. Image data is gathered representing an image of the specimen. The image data is processed to measure features of the objects to determine whether the object is normal. The feature measurements for all objects in the specimen are then combined to determine whether the specimen as a whole is normal.

Abstract: A method for high speed morphological processing in a computerized image processing system starts by acquiring a binary image and selecting feature and height values corresponding to a desired morphological processing of an image. The image is scanned in a raster scanning sequence so as to produce a scanned image including a plurality of pixels. A sequential labeling transformation is performed on each of the plurality of pixels of the scanned image so as to produce a transformed image. A thresholding operation is performed on the transformed image. The resultant image is translated.

Abstract: An automated method for checking cytological system autofocus integrity. The automated method includes the steps of checking focus illumination integrity, checking focus camera Modulation Transfer Function, checking focus camera position integrity, and checking closed loop accuracy. Checking focus illumination integrity includes checking focus illumination system integrity, and checking a focus noise floor level. Checking focus camera position integrity includes checking focus camera longitudinal separation, and checking focus camera lateral separation. Checking focus camera position integrity includes checking focus filter frequency response.

Abstract: An automated method for checking cytological system autofocus integrity. The automated method includes the steps of checking focus illumination integrity, checking focus camera Modulation Transfer Function, checking focus camera position integrity, and checking closed loop accuracy. Checking focus illumination integrity includes checking focus illumination system integrity, and checking a focus noise floor level. Checking focus camera position integrity includes checking focus camera longitudinal separation, and checking focus camera lateral separation. Checking focus camera position integrity includes checking focus filter frequency response.

Abstract: Field of views of a slide are examined to assess the likelihood of existence of detectable single cells, groups, and thick groups of cells to locate objects of interest by an automated microscope. The FOV features consists of features selected from the distribution profiles of size, shape, layout arrangement, texture and density of all objects within a FOV which are compared against pre-determined criteria.Each field of view is assigned a likelihood value based on FOV features. Areas that are blank, or contain air bubbles, or are too dense for analysis are identified and excluded for further analysis. Each FOV is ranked according to its likelihood of containing SIL (Squamous Intraepithelial Lesion) cells or cell groups of interest. These results, such as SIL, single cell ranking, group ranking are used to arrange the further examination of FOVs in a priority order.

Abstract: A classifier measures robustness responsive to object presentation effects and decision boundary effects. A cytological image analysis computer obtains objects of interest and classifies them responsive to a decision tree classifier. The robustness of classification is calculated dynamically as objects are classified responsive to a segmentation robustness and a classification decisiveness measure. The results of the decisiveness measure and the segmentation robustness data are combined to provide enhanced overall classification reliability.

Abstract: A robust biological specimen classifier. An automated microscopy system obtains features from an image of a biological specimen slide. A computer system in the automated microscopy system computes feature variations. Clusters are created that comprise samples of similar characteristics. A cluster membership generator generates membership values for each cluster. Classifiers specialized to certain feature sets are used to provide independent outputs. These outputs are offset and biased by the output of the membership generator. The output of the adjusted classification values are summed to create a slide score output.

Abstract: A method for checking cytological system illumination including the steps of checking global illumination variation, static field uniformity, dynamic field uniformity, specimen thickness variation, strobe repeatability, calibration plate cleanliness, and strobe dropout. A calibration plate and test target is employed for various illumination checks.

Abstract: A method and apparatus for determining whether a slide is suitable for processing. A suite of suitability tests are performed by an automated microscope system. The tests include magnification error flags, staining flags, main optical density flags, including detected intermediate cell nuclei, rings around detected intermediate cell nuclei, average texture measure of detected intermediate cell nuclei, average contrast to detected intermediate cell nuclei to cytoplasm, standard deviation of detected intermediate cell nuclei optical densities, detected intermediate cell ratios, average stripe area, measure of a saturated magnification of the image, measure of a grossly saturated magnification, and the percentage of images focused properly on a first try, including images never focused properly. The automated microscope quantifies the measurements in a reliable and repeatable way.

Abstract: An automated apparatus for urine sediment sample handling includes settling cells for carrying patient samples transported on a sample and cell transport assembly. An illumination and camera assembly is positioned in an examination area to view one of the settling cells when it moves to the examination area. The illumination and camera assembly have a first data output. An image processing assembly is coupled to receive data from the first data output. The image processing assembly have a second data output for carrying processed digital data. A processor having control lines is coupled to the sample and cell transport assembly, illumination and camera assembly, and image processing assembly where the sample and cell transport assembly, illumination and camera assembly, and image processing assembly operate responsively to commands from the processor to handle the urine sediment samples.

Abstract: The detection of optical stripes on an image of a glass slide of material of interest. An automated microscope system with an illuminator having a spatial intensity homogenizer provides spatially uniform illumination of a microscope slide specimen. Periodic optical patterns formed from the illumination system are detected by a computer system. The computer forms a high transmission mask of an image of the biological specimen. Edges in the image are detected and a low transmission area process is performed. Horizontal stripes are enhanced. A final thresholding generates a binary image of the patterns. Stripes in the patterns are detected an a stripe flag and strip area are calculated.

Abstract: An illumination device provides temporally, spatially and angularly stable illumination for microscopic evaluations. An arc lamp serves as the light source. An input optical train gathers and focuses the light through an aperture stop to place an image of the arc incident on an input aperture of a light pipe. The magnification of the arc lamp is chosen to reduce the variation due to occlusion. The light pipe spatially homogenizes the light while preserving the angular integrity. An exit window may be placed over the exit aperture of the light pipe to keep dust and debris out of focus. Another optical train receives the spatially homogenized, angularly preserved light and may focus a many arclet images to fill the pupil of a condenser lens. The condenser lens also may focus the exit aperture of the light pipe onto or near the specimen on a microscope slide. A feedback system samples the light and corrects for residual temporal variations by electronically modifying the image as it leaves a CCD.

Abstract: An automated biological specimen screener reports an assessment of slide and specimen preparation and quality. The automated biological specimen screener measures, parameters which reflect slide physical characteristics, specimen collection quality, and specimen preparation quality. The automated system reports an objective measure and uses a consistent standard of evaluation. The automated system evaluates characteristics of a slide set from a clinic. The automated system makes a determination of whether these characteristics are within a training capability of a given automated biological screener. Additionally, rather than periodic reviews, slides successfully scanned by the automated system may be used as part of a specimen preparation assessment.