Abstract: MRAM noise stabilizing and reducing apparatus and methods for MRAM sensing operations injects noise generated by activation of a word line (80, 82, 84, 86) into a sense line (128) and a reference line (130). Sense strings (20, 22, 24, 26) addressed by the word line (80, 82, 84, 86) are alternately coupled to the sense line (128) and the reference line (130). Cross coupling reduces the noise injected on the sense lines (128, 130). Cross coupling also balances the noise created by activation of the word line (80, 82, 84, 86) between the sense line (128) and reference line (130). A sense string (20, 22, 24, 26) not addressed by the word line (80, 82, 84, 86) provides a reference signal. A differential amplifier (132) includes circuitry to compare and store a difference between the sense line (128) and the reference line (130). The stored value can be further compared to a second value obtained by reversing the current on the word line (80, 82, 84, 86).

Abstract: An interactive process for sorting biological specimens includes the steps of processing a biological specimen to provide an analysis score, sorting the biological specimens according to the analysis score into categories including: clearly normal, interactive review, and microscopy review, and selecting a field-of-view (FOV) for the biological specimens sorted into the interactive review category.

Abstract: Dynamic control of the processing flow of an image analyzer such as a biological specimen analyzer as processing proceeds. Data collected and processed from a specimen under analysis, such as a biological specimen on a microscope slide, determines the fate of further processing. If there is enough evidence, based on the data collected from a slide, to make a decision with sufficient confidence, the processing of the slide can be stopped and a decision may be rendered. By avoiding unnecessary additional computation system throughput may be enhanced. Otherwise, data collection and computation continues until either certain termination criteria are met or no more data is left to acquire. This slide-dependent control and decision making method flexibly limits the amount of computation required to reach a system decision about a specimen.

Abstract: A method and apparatus for optimizing biological and cytological specimen screening and diagnosis. A slide review process is recommended for cytological specimen screening to identify abnormal sub-populations for further review and also diagnosis by a human expert. An automated screener processes a cytological specimen. Using a slide score generated by the automated screener, a slide review process using a slide score classification is determined. The recommendation of slide review processes improves overall performance of the screening process as measured by sensitivity to abnormal specimens, and at the same time reduces the work load of a human reviewer. The system also effectively and smoothly integrates the process of initial screening of the specimen with the process of further review of the specimen and final diagnosis of the specimen.

Abstract: An incremental concurrent learning method starts with providing potential defects and fabrication information and a primary classification rule and secondary classification rule selection from a knowledge defect database from multiple products with different process cycles. The method then performs a truth inquiry to update a classification rule database for use by the primary classification rule and secondary classification rule selection. The method performs a primary defect classification and checks the confidence of the classification, and performs a secondary defect classification if the confidence is not high. If the confidence of the secondary defect classification is not high, a new defect may have been discovered and a novelty defect detection step is performed to define artifacts or potential new defect types to provide information for the truth inquiry.

Abstract: A free-lying cell classifier. An automated microscope system comprising a computer and high speed processing field of view processors identifies free-lying cells. An image of a biological specimen is obtained and the image is segmented to create a set of binary masks. The binary masks are used by a feature calculator to compute the features that characterize objects of interest including free-lying cells, artifacts and other biological objects. The objects are classified to identify their type, their normality or abnormality or their identification as an artifact. The results are summarized and reported. A stain evaluation of the slide is performed as well as a typicality evaluation. The robustness of the measurement is also quantified as a classification confidence value. The free-lying cell evaluation is used by an automated cytology system to classify a biological specimen slide.

Abstract: A free-lying cell classifier. An automated microscope system comprising a computer and high speed processing field of view processors identifies free-lying cells. An image of a biological specimen is obtained and the image is segmented to create a set of binary masks. The binary masks are used by a feature calculator to compute the features that characterize objects of interest including free-lying cells, artifacts and other biological objects. The objects are classified to identify their type, their normality or abnormality or their identification as an artifact. The results are summarized and reported. A stain evaluation of the slide is performed as well as a typicality evaluation. The robustness of the measurement is also quantified as a classification confidence value. The free-lying cell evaluation is used by an automated cytology system to classify a biological specimen slide.

Abstract: A reduced instruction set architecture implements complicated image processing algorithms that are decomposed into combinations of simple operations. The simple operations are further decomposed into multiple operations of one dimensional data with an address controller to scan data in a highly flexible fashion for multi-dimensional applications.

Abstract: Image primitive based maskless semiconductor wafer and liquid crystal display panel inspection by the characterization of wafer patterns. Potential defects are detected as exceptions to the rules of general semiconductor surface pattern structure. The wafer or liquid crystal display, lcd, structure is encoded into multiple profiles of a set of primitive characterization modules. Primitive profiles are correlated with potential defects along with aligned pattern images for surface component to surface component, lcd active matrix element to lcd active matrix element, comparison and further refines the results using data from multiple surface components or lcd active matrix elements. Multiple stage defect classification is applied to the potential defects to reject false defects. Multiple layer correlation and automatic learning enhance and tailor detection rules during a ramp-up stage. There is a dramatic reduction of false and nuisance defects and a high sensitivity to critical defects.

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 thick group of cells classifier. Image data acquired from an automated microscope from a cytological specimen is processed by a computer system. The computer applies filters at different stages. Obvious artifacts are eliminated from analysis early in the processing. The first stage of processing is image segmentation where objects of interest are identified. The next stage of processing is feature calculation where properties of each segmented thick group object are calculated. The final step is object classification where every segmented thick group object is classified as being abnormal or as belonging to a cellular or non-cellular artifact.

Abstract: A free-lying cell classifier. An automated microscope system comprising a computer and high speed processing field of view processors identifies free-lying cells. An image of a biological specimen is obtained and the image is segmented to create a set of binary masks. The binary masks are used by a feature calculator to compute the features that characterize objects of interest including free-lying cells, artifacts and other biological objects. The objects are classified to identify their type, their normality or abnormality or their identification as an artifact. The results are summarized and reported. A stain evaluation of the slide is performed as well as a typicality evaluation. The robustness of the measurement is also quantified as a classification confidence value. The free-lying cell evaluation is used by an automated cytology system to classify a biological specimen slide.

Abstract: The detection of cellular aggregates within cytologic samples. An image analysis system with an image gathering system includes a camera, a motion controller, an illumination system and an interface obtains images of cell groupings. The image gathering system is constructed for gathering image data of a specimen mounted on a slide and is coupled to a data processing system. Image data is transferred from the image gathering system to the data processing system. The data processing system obtains objects of interest. A four step process finds cellular aggregates. The first step is acquisition of an image for analysis. The second step is extraction of image features. The third step is classification of the image to determine if any potential cellular aggregates may exist in the image. The fourth step is segmentation of objects which includes the substeps of detecting and locating potential cellular aggregates.

Abstract: Improving accuracy of frequency response measurements of linear systems using modulation transfer function test compensation. An optical imaging system illuminates and images an input test pattern. A processor measures a modulation transfer function. The processor determines a compensating factor for error in the input test pattern duty cycle. The driving function for the measurement is a test pattern having a periodic waveform approximating a square wave with an error in duty cycle. A windowed fast fourier transform on a greyscale image of the test pattern generates odd harmonics. Adjusting amplitude values of the odd harmonics corrects for the error in resolution target duty cycle.

Abstract: Measurement of the optical transfer function of an optical system imaging a bar pattern. A one dimensional fast Fourier transform processes sampled image data from the bar pattern. A model of the system utilizes robust measurements of the period, duty cycle and center of each stripe in the pattern. A signal alias free optical transfer function is estimated from the plurality of one dimensional frequency representation of the signal. An idealized bar pattern synthesized from the measured parameters of period, duty cycle and the center of each stripe in the pattern generates an ideal optical transfer function. The noise reduced optical transfer function, OTF, is estimated from OTF of the signal and OTF of the synthesized bar pattern.

Abstract: The invention detects areas of interest at low magnification, locating possible abnormal cells or other cells of interest using image processing and statistical pattern recognition techniques. Next, at high magnification, the areas identified at low magnification are re-examined. The information from the low magnification and high magnification scans is collated and a determination is made about the slide--whether it is normal, abnormal, contains endocervical component, and so forth. The invention also provides a method and apparatus to train object feature and slide feature classifiers. The invention provides an automated cytology system that can process training slides for use in a feed back classifier development environment. The invention also can classify endocervical groups of cells.

Abstract: A part inspection and calibration method for the inspection of integrated circuits includes a camera to image a precision pattern mask deposited on a transparent reticle. Small parts are placed on or above the transparent reticle to be inspected. A light source and overhead light reflective diffuser provide illumination. An overhead mirror or prism reflects a side view of the part under inspection to the camera. The scene of the part is triangulated and the dimensions of the system can thus be calibrated. A reference line is located on the transparent reticle to allow an image through the prism to the camera of the reference line between the side view and the bottom view. A precise reticle mask with dot patterns gives an additional set of information needed for calibration. By imaging more than one dot pattern the missing state values can be resolved using an iterative trigonometric solution.

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: A computer receives image data from a star-shaped optical target in the object plane and calculates angle-dependent boundary sharpness. The horizontal, x-direction, amplitude derivative and the vertical, y-direction, amplitude derivative are computed over a portion of each star pattern image from a Z panning sequence. A microscope slide stage, carrying the target, is moved vertically from a level just below where the target is in focus to a level just above where the target is in focus. For each small increment of vertical motion, Z panning, an image of the star pattern is captured for analysis. Computations are performed on the differentiated images to search for evidence of elongation of the point spread function and variation with stage Z position of the angle of long axis of such an out-of-round point spread function. The presence of a distorted point spread function that varies along the optical axis indicates astigmatism.

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.