Abstract: An improved diagnostic resolution of digital slide images is obtained by scanning a first digital slide image at diagnostic resolution that is then deconvolved into separate images with one stain per image. The single stain images are then enhanced with image adjustments and/or processed with image analysis algorithms. The resulting single image data sets from the image analysis algorithms can then be stored. Additionally, the resulting enhanced single images can be recombined into a second digital slide image at diagnostic resolution that is also enhanced.

Abstract: Systems and methods for image pattern recognition comprise digital image capture and encoding using vector quantization (“VQ”) of the image. A vocabulary of vectors is built by segmenting images into kernels and creating vectors corresponding to each kernel. Images are encoded by creating a vector index file having indices that point to the vectors stored in the vocabulary. The vector index file can be used to reconstruct an image by looking up vectors stored in the vocabulary. Pattern recognition of candidate regions of images can be accomplished by correlating image vectors to a pre-trained vocabulary of vector sets comprising vectors that correlate with particular image characteristics.

Abstract: Systems and methods for processing, storing, and viewing extremely large imagery data rapidly produced by a linear-array-based microscope slide scanner are provided. The system receives, processes, and stores imagery data produced by the linear scanner as a series of overlapping image stripes and combines the data into a seamless and contiguous baseline image. The baseline image is logically mapped into a plurality of regions that are individually addressed to facilitate viewing and manipulation of the baseline image. The system enables dynamic imagery data compression while scanning and capturing new image stripes that eliminates the overhead associated with storing uncompressed image stripes. The system also creates intermediate level images, thereby organizing the baseline image into a variable level pyramid structure referred to as a virtual slide.

Abstract: A portion of imagery data is obtained from a digital slide and a protocol of image analysis/diagnostic tasks is performed on the portion of imagery data by a pathologist or an image analysis module. The result of each task (e.g., success or no success) is recorded and a score is determined for the portion of the imagery data. Multiple portions of imagery data from the digital slide are analyzed and scored and the various scores from the multiple portions of imagery data are calculated to determine an overall score for the digital slide. Regions of the digital slide can be scored separately. Multiple rounds of scoring (by different pathologists and/or different image analysis algorithms) may be employed to increase the accuracy of the score for a digital slide or region thereof.

Abstract: Systems and methods for creating and viewing three dimensional virtual slides are provided. One or more microscope slides are positioned in an image acquisition device that scans the specimens on the slides and makes two dimensional images at a medium or high resolution. This two dimensional images are provided to an image viewing workstation where they are viewed by an operator who pans and zooms the two dimensional image and selects an area of interest for scanning at multiple depth levels (Z-planes). The image acquisition device receives a set of parameters for the multiple depth level scan, including a location and a depth. The image acquisition device then scans the specimen at the location in a series of Z-plane images, where each Z-plane image corresponds to a depth level portion of the specimen within the depth parameter.

Abstract: Systems and methods are provided to facilitate consultations between a referral source (e.g., labs, pathologists and patients) and a consultant (e.g., pathologist, radiologist, or other digital image analyst). Links between the various referral sources and consultants are established through a scanning center via a data communication network such as the Internet. The referral source sends a slide to the scanning center where the corresponding digital slide is posted for review and analysis by the consultant. Upon completion of the analysis and report, a digital slide conference is conducted through the scanning center that provides a venue for direct communication regarding the consultation. The scanning center may also facilitate payment from the referral source to the consultant.

Abstract: Apparatus for and method of fully automatic rapid scanning and digitizing of an entire microscope sample, or a substantially large portion of a microscope sample, using a linear array detector synchronized with a positioning stage that is part of a computer controlled microscope slide scanner. The invention provides a method for composing the image strips obtained from successive scans of the sample into a single contiguous digital image. The invention also provides a method for statically displaying sub-regions of this large digital image at different magnifications, together with a reduced magnification macro-image of the entire sample. The invention further provides a method for dynamically displaying, with or without operator interaction, portions of the contiguous digital image. In one preferred embodiment of the invention, all elements of the scanner are part of a single-enclosure that has a primary connection to the Internet or to a local intranet.

Abstract: Systems and methods for improving quality assurance in pathology using automated quality assessment and digital image enhancements on digital slides prior to analysis by the pathologist are provided. A digital pathology system (slide scanning instrument and software) creates, assesses and improves the quality of a digital slide. The improved digital slide image has a higher image quality that results in increased efficiency and accuracy in the analysis and diagnosis of such digital slides when they are reviewed on a monitor by a pathologist. These improved digital slides yield a more objective diagnosis than reading the corresponding glass slide under a microscope.

Abstract: A data management system and method for processing, storing, and viewing the extremely large imagery data that is rapidly produced by a linear-array-based microscope slide scanner is provided. The system receives, processes, and stores imagery data produced by the linear-array-based microscope slide scanner at approximately 3 GB per minute. The data are received as a series of overlapping image stripes and combined into a seamless and contiguous baseline image. The baseline image is logically mapped into a plurality of regions that are individually addressed to facilitate viewing and manipulation of the baseline image. The data management system enables imagery data compression while scanning and capturing new image stripes. This advantageously eliminates the overhead associated with storing uncompressed image stripes. The image compression also creates intermediate level images, thereby organizing the baseline image into a variable level pyramid structure referred to as a virtual slide.

Abstract: Systems and methods that acquire digital slides and other large images and store these images into commercially available PACS systems using DICOM-standard messaging are provided. A digital slide or other large two-dimensional image is acquired and each separate resolution level of the digital slide or large image is divided into a series of regions that are each identified as a DICOM image. All of the regions at the same resolution in the digital slide or other large image are collectively identified as a DICOM series. A plurality of DICOM series, representing multiple resolution levels in a digital slide are collectively identified and stored as a DICOM study.

Abstract: Images created by one or more image acquisition devices are initially stored in remote data bases at one or more remote or satellite locations and copies of the images are subsequently transferred to a central server at a central storage location over a network and stored in a central data base. A common catalog listing local image files stored at the central data base and remote image files stored at one or more remote data bases is stored at the central location and is accessed by users to search for images. User requests for images associated with local image files result in transfer of the requested images by the central server to the user. User requests for images associated with remote image files are relayed by the central server to the associated remote location, and the requested images are then relayed to the user from the remote location via the central server.

Abstract: Systems and methods for image pattern recognition comprise digital image capture and encoding using vector quantization (“VQ”) of the image. A vocabulary of vectors is built by segmenting images into kernels and creating vectors corresponding to each kernel. Images are encoded by creating a vector index file having indices that point to the vectors stored in the vocabulary. The vector index file can be used to reconstruct an image by looking up vectors stored in the vocabulary. Pattern recognition of candidate regions of images can be accomplished by correlating image vectors to a pre-trained vocabulary of vector sets comprising vectors that correlate with particular image characteristics.

Abstract: Systems and methods for image pattern recognition comprise digital image capture and encoding using vector quantization (“VQ”) of the image. A vocabulary of vectors is built by segmenting images into kernels and creating vectors corresponding to each kernel. Images are encoded by creating a vector index file having indices that point to the vectors stored in the vocabulary. The vector index file can be used to reconstruct an image by looking up vectors stored in the vocabulary. Pattern recognition of candidate regions of images can be accomplished by correlating image vectors to a pre-trained vocabulary of vector sets comprising vectors that correlate with particular image characteristics.

Abstract: A system and method for processing and analyzing virtual microscopy digital images (“virtual slides”) is provided. The system comprises an algorithm server that maintains or has access to a plurality of image processing and analysis routines. The algorithm server additionally has access to a plurality of virtual slides. The algorithm server executes a selected routine on an identified virtual slide and provides the resulting data. The virtual slide can be accessed locally or remotely across a network. Similarly, the image processing routines can be obtained from local storage or across a network, or both. Advantageously, certain common sub-routines may be stored locally for inclusion in other local or remotely obtained routines. Access to image processing and analysis may be restricted through a monitor process that authenticates requests to process or view virtual slides.

Abstract: A system and method for processing and analyzing virtual microscopy digital images (“virtual slides”) is provided. The system comprises an algorithm server that maintains or has access to a plurality of image processing and analysis routines. The algorithm server additionally has access to a plurality of virtual slides. The algorithm server executes a selected routine on an identified virtual slide and provides the resulting data. The virtual slide can be accessed locally or remotely across a network. Similarly, the image processing routines can be obtained from local storage or across a network, or both. Advantageously, certain common sub-routines may be stored locally for inclusion in other local or remotely obtained routines. Access to image processing and analysis may be restricted through a monitor process that authenticates requests to process or view virtual slides.

Abstract: A data management system and method for processing, storing, and viewing the extremely large imagery data that is rapidly produced by a linear-array-based microscope slide scanner is provided. The system receives, processes, and stores imagery data produced by the linear-array-based microscope slide scanner at approximately 3 GB per minute. The data are received as a series of overlapping image stripes and combined into a seamless and contiguous baseline image. The baseline image is logically mapped into a plurality of regions that are individually addressed to facilitate viewing and manipulation of the baseline image. The data management system enables imagery data compression while scanning and capturing new image stripes. This advantageously eliminates the overhead associated with storing uncompressed image stripes. The image compression also creates intermediate level images, thereby organizing the baseline image into a variable level pyramid structure referred to as a virtual slide.

Abstract: Apparatus for and method of fully automatic rapid scanning and digitizing of an entire microscope sample, or a substantially large portion of a microscope sample, using a linear array detector synchronized with a positioning stage that is part of a computer controlled microscope slide scanner. The invention provides a method for composing the image strips obtained from successive scans of the sample into a single contiguous digital image. The invention also provides a method for statically displaying sub-regions of this large digital image at different magnifications, together with a reduced magnification macro-image of the entire sample. The invention further provides a method for dynamically displaying, with or without operator interaction, portions of the contiguous digital image. In one preferred embodiment of the invention, all elements of the scanner are part of a single-enclosure that has a primary connection to the Internet or to a local intranet.

Abstract: A data management system and method for processing, storing, and viewing the extremely large imagery data that is rapidly produced by a linear-array-based microscope slide scanner is provided. The system receives, processes, and stores imagery data produced by the linear-array-based microscope slide scanner at approximately 3 GB per minute. The data are received as a series of overlapping image stripes and combined into a seamless and contiguous baseline image. The baseline image is logically mapped into a plurality of regions that are individually addressed to facilitate viewing and manipulation of the baseline image. The data management system enables imagery data compression while scanning and capturing new image stripes. This advantageously eliminates the overhead associated with storing uncompressed image stripes. The image compression also creates intermediate level images, thereby organizing the baseline image into a variable level pyramid structure referred to as a virtual slide.

Abstract: A system and method for processing and analyzing virtual microscopy digital images (“virtual slides”) is provided. The system comprises an algorithm server that maintains or has access to a plurality of image processing and analysis routines. The algorithm server additionally has access to a plurality of virtual slides. The algorithm server executes a selected routine on an identified virtual slide and provides the resulting data. The virtual slide can be accessed locally or remotely across a network. Similarly, the image processing routines can be obtained from local storage or across a network, or both. Advantageously, certain common sub-routines may be stored locally for inclusion in other local or remotely obtained routines. Access to image processing and analysis may be restricted through a monitor process that authenticates requests to process or view virtual slides.

Abstract: Systems and methods for image pattern recognition comprise digital image capture and encoding using vector quantization (“VQ”) of the image. A vocabulary of vectors is built by segmenting images into kernels and creating vectors corresponding to each kernel. Images are encoded by creating a vector index file having indices that point to the vectors stored in the vocabulary. The vector index file can be used to reconstruct an image by looking up vectors stored in the vocabulary. Pattern recognition of candidate regions of images can be accomplished by correlating image vectors to a pre-trained vocabulary of vector sets comprising vectors that correlate with particular image characteristics.