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Systems and methods for encoding image features of high-resolution digital images of biological specimens

專利號
US11176412B2
公開日期
2021-11-16
申請人
Ventana Medical Systems, Inc.(US AZ Tucson)
發(fā)明人
Yao Nie
IPC分類
G06K9/00; G06K9/62; G06T7/11; G06K9/46
技術領域
superpixel,image,clustering,centroid,clusters,in,cluster,vectors,vector,biological
地域: AZ AZ Tucson

摘要

An image analysis system for analyzing biological specimen images is disclosed. The system may include: a superpixel generator configured to obtain a biological specimen image and group pixels of the biological specimen image into a plurality of superpixels; a feature extractor configured to extract, from each superpixel in the plurality of superpixels, a feature vector comprising a plurality of image features; a clustering engine configured to assign the plurality of superpixels to a predefined number of clusters, each cluster being characterized by a centroid vector of feature vectors of superpixels assigned to the cluster; and a storage interface configured to store, for each superpixel in the plurality of superpixels, clustering information identifying the one cluster to which the superpixel is assigned. The system may also include a graph engine configured construct a graph based on the stored information, and use the graph to perform a graph-based image processing task.

說明書

In situ hybridization (ISH) staining is a technique that uses a labeled complementary DNA, RNA or modified nucleic acids strand (i.e., probe) to localize a specific DNA or RNA sequence in a portion or section of tissue. In situ hybridization can be a powerful technique for identifying specific mRNA species within individual cells in tissue sections, providing insights into physiological processes and disease pathogenesis.

Researchers and clinicians have traditionally examined tissue slides stained with H&E, IHC, ISH, fluorescent ISH (FISH), or other methods under a bright-field or a fluorescence microscope. However, as the assays are becoming more complicated and often require locating and counting of hundreds or thousands of cells of specific types in specific types of regions, performing these tasks manually (and accurately) becomes an increasingly difficult task. Accordingly, more and more researchers and clinicians are beginning to employ “digital pathology” solutions that can help them get faster, more accurate, and more reproducible results. Digital pathology systems include slide scanners that can scan tissue slides to produce very high resolution (e.g., 0.5 or 0.275 microns per pixel) digital images of the tissue. Digital pathology systems also include hardware and/or software solutions for automatically processing, viewing, segmenting, analyzing (e.g., scoring) and otherwise managing tissue images or other types of biological specimen images.

權利要求

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