Abstract: Multiple different samples are obtained from a bulk material and are separately stained. The differently stained materials look different with the different stains but also have similar characteristics. A computer is used to reorient the images so that the samples are oriented with one another. The thus oriented samples can have their like parts either reoriented. Once the stained areas are analyzed, the identified area in the unstained sample can be removed by laser capture microdissection.

Abstract: A block of tissue is imaged and used as a reference. Later slides formed from that tissue receive numbers, and are also imaged. The imaged slides are compared to the reference image to determine identification errors.

Abstract: A tissue sample to be analyzed is tested. Multiple different samples of multiple areas of said tissue sample, each of said multiple areas is a smaller area than an entire tissue sample to be analyzed. After analysis, the tissue sample is processed in a way that facilitates viewing tumor information on the sample, for example, by fixing or staining. An area is identified on the stained sample, and at least one of the samples that corresponds to an identified area is tested. This small area is tested using a technique that homogenizes the sample before testing.

Abstract: Multiple different samples are obtained from a bulk material and are separately stained. The differently stained materials look different with the different stains but also have similar characteristics. A computer is used to reorient the images so that the samples are oriented with one another. The thus oriented samples can have their like parts either reoriented. Once the stained areas are analyzed, the identified area in the unstained sample can be removed by laser capture microdissection.

Abstract: A tissue sample to be analyzed is tested. Multiple different samples of multiple areas of said tissue sample, each of said multiple areas is a smaller area than an entire tissue sample to be analyzed. After analysis, the tissue sample is processed in a way that facilitates viewing tumor information on the sample, for example, by fixing or staining. An area is identified on the stained sample, and at least one of the samples that corresponds to an identified area is tested. This small area is tested using a technique that homogenizes the sample before testing.

Abstract: A priori knowledge is obtained from known tumor samples, indicative of cellular pathways associated with those known tumor samples. Multiple pathways are found for each tumor. This becomes a priori knowledge. Later unknown tumor samples are then analyzed against the a priori knowledge to find the pathways etc within the unknown tumor samples. Multiple pathways are collected to form an oncogenic signature. The oncogenic signature is used to find a cocktail of multiple treatments that treats each of the multiple pathways.

Abstract: A block of tissue is imaged and used as a reference. Later slides formed from that tissue receive numbers, and are also imaged. The imaged slides are compared to the reference image to determine identification errors.

Abstract: A method and apparatus for automated analysis of transmitted and fluorescently labeled biological samples, wherein the apparatus automatically scans at a low magnification to acquire images which are analyzed to determine candidate cell objects of interest. Once candidate objects of interest are identified, further analysis is conducted automatically to process and collect data from samples having different staining agents.

Abstract: A system and method for visual image compression and transmission offers significant bandwidth conservation while retaining high resolution imaging capability. Videograpic images are decomposed into detail levels, and images are delivered to a remote site display at a level of detail proportional to the perception level of a viewer. Images are transformed, quantized, coded and queued for transmission in accordance with their level of image detail. Image detail layers are transmitted as an inverse function of image displacement speed and as a direct function of image magnification. Images are constructed vertically with each additional queueing layer providing additional image detail. Higher priority layers are lossy encoded, while the lowest priority layers (highest detail levels) are losslessly encoded.

Abstract: Imaging apparatuses and methods that capture a low-resolution image of a slide, identify a region of interest, and capture a high-resolution image of the region of interest.

Abstract: A method and apparatus for automated cell analysis of biological specimens automatically scans at a low magnification to acquire images (288) which are analyzed to determine candidate cell objects of interest. The low magnification images are converted from a first color space to a second color space (290). The color space converted image is then low pass filtered (292) and compared to a threshold (294) to remove artifacts and background objects from the candidate object of interest pixels of the color converted image. The candidate object of interest pixels are morphologically processed (296) to group candidate object of interest pixels together into groups which are compared to blob parameters (298) to identify candidate objects of interest which correspond to cells or other structures relevant to medical diagnosis of the biological specimen. The location coordinates of the objects of interest are stored and additional images of the candidate cell objects are acquired at high magnification.

Abstract: A method, system, and apparatus are provided for automated light microscopic for detection of proteins associated with cell proliferative disorders.

Abstract: The apparatus and method of the invention provide for assigning coordinates to samples in an array. The method is based on a hierarchical pattern matching to a local lattice structure that is used as a template. Starting from the best local match, the pattern is expanded hierarchically to encompass the entire array.

Abstract: A method and apparatus for automated cell analysis of biological specimens automatically scans at a low magnification to acquire images which are analyzed to determine candidate cell objects of interest. The low magnification images are converted from a first color space to a second color space. The color space converted image is then low pass filtered and compared to a threshold to remove artifacts and background objects from the candidate object of interest pixels of the color converted image. The candidate object of interest pixels are morphologically processed to group candidate object of interest pixels together into groups which are compared to blob parameters to identify candidate objects of interest which correspond to cells or other structures relevant to medical diagnosis of the biological specimen. The location coordinates of the objects of interest are stored and additional images of the candidate cell objects are acquired at high magnification.

Abstract: A method for automated image analysis of a biological specimen by histological reconstruction. Also provided is an automated cell image method for analyzing a biological specimen that has consecutively been stained by either an in situ hybridization (ISH) method, or an immunohistochemistry (IHC) method or a nucleic acid stain, and counterstained. The method couples composite images in an automated manner for processing and analysis. To identify structure in tissue that cannot be captured in a single field of view image or a single staining technique, the disclosure provides a method for histological reconstruction to analyze many fields of view on potentially many slides simultaneously.