A physics based model of the absorption of light by histological stains used to measure the amount of one or more stains at locations within tissue is disclosed. The subsequent analysis results in several improvements in the detection of tissue on a slide, improvements to autofocus algorithms so focusing during image acquisition is confined to tissue, improvements to image segmentation and identification of tissued and its features, improvements to the identification of stain where multiple stains are used, and improvements to the quantification of the extent of staining. The invention relates to the application of these improvements to stain detection and quantification to provide for objective comparison between tissues and closer correlation between the presentations of such features and concurrent patterns of gene or protein expression.
Robust Stain Detection And Quantification For Histological Specimens Based On A Physical Model For Stain Absorption
Ronald Stone - Pittsburgh PA Othman Abdulkarim - Pittsburgh PA Michael Fuhrman - Pittsburgh PA
Assignee:
Icoria, Inc. - Research Triangle Park NC
International Classification:
G06K 900
US Classification:
382133
Abstract:
A physics based model of the absorption of light by histological stains used to measure the amount of one or more stains at locations within tissue is disclosed. The subsequent analysis results in several improvements in the detection of tissue on a slide, improvements to autofocus algorithms so focusing during image acquisition is confined to tissue, improvements to image segmentation and identification of tissued and its features, improvements to the identification of stain where multiple stains are used, and improvements to the quantification of the extent of staining. The invention relates to the application of these improvements to stain detection and quantification to provide for objective comparison between tissues and closer correlation between the presentations of such features and concurrent patterns of gene or protein expression.
Quantification And Differentiation Of Tissue Based Upon Quantitative Image Analysis
Peter Johnson - Wexford PA, US Othman Abdulkarim - Pittsburgh PA, US Michael Fuhrman - Pittsburgh PA, US Mark Disilvestro - Fort Wayne IN, US Ronald Stone - Pittsburgh PA, US Mark Braughler - Upper St. Clair PA, US
International Classification:
G06K009/00 G06K009/46 G06K009/66
US Classification:
382/128000, 382/190000
Abstract:
We disclose quantitative geometrical analysis enabling the measurement of several features of images of tissues including number, size, density of extracted hepatocyte nuclei, and other metrics. Automation of feature extraction creates a high throughput capability that enables analysis of histologically prepared tissue sections for accurate quantification of extracted features from tissues. Measurement results are input into a relational database where they can be statistically analyzed and compared across studies. As part of the integrated process, results are also imprinted on the images themselves to facilitate auditing of the results. The analysis is objective, fast, repeatable and accurate and provides an alternative or supplement to the subjective analysis of tissue slides by a pathologist.
System And Method Of Generating And Storing Correlated Hyperquantified Tissue Structure And Biomolecular Expression Datasets
Peter Johnson - Wexford PA, US Andres Kriete - Pittsburgh PA, US Keith Boyce - Wexford PA, US Ronald Stone - Pittsburgh PA, US Andrew Lesniak - Pittsburgh PA, US
International Classification:
C12Q001/68 G06F019/00 G01N033/48 G01N033/50
US Classification:
435/006000, 702/020000
Abstract:
We disclose a method for the correlation of structural feature information derived from digital images of a diagnostic set of histopathological tissue specimens from a group of subjects with shared characteristics and molecular activity (which may be either gene or protein expression) information derived from related specimens of the same set to provide for the objective characterization and analysis of the variability of tissue structural features in relation to such molecular activity (the product of such correlation referred to herein as the “correlated tissue information”). Such correlated tissue information allows for comparison and combination with correlated tissue information obtained through studies taking place at different times, with different protocols for the collection, preservation, histological staining and molecular activity assays of the tissue. The present invention specifically relates to a system and method to obtain and store correlated tissue information by combining hyperquantified feature expression data with gene and/or protein expression data. Such a system also allows for the relation of such correlated tissue information to certain clinical diagnoses or conditions through the inclusion or exclusion parameters describing the shared characteristics of the set of subjects providing the tissue specimens for analysis.
Michael Meissner - Pittsburgh PA, US Ronald Stone - Pittsburgh PA, US Raghavan Venugopal - Pittsburgh PA, US
Assignee:
OMNYX, LLC - Pittsburgh PA
International Classification:
G06F 19/00 G06Q 50/24
US Classification:
705 3
Abstract:
A system and method of increasing digital pathology productivity is provided. The system accepts case information from a plurality of sources and pre-processes that information in order to present the slides in an order and orientation dictated by preference and/or reviewing standard. Upon application of the system and method, the appearance and behavior of the user interface is optimized for the user.