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 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: 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: 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.