Ventana Medical Systems, Inc.

Bikash Sabata

Srinivas Chukka

Anindya Sarkar

Gregory Loney

Chris Todd

Glenn Stark

Suhas Hanmantrao Patil

Sujit Siddheshwar Chivate

Olcay Sertel

Ronald T Kurnik

Ronald L Allen

Quan Yuan

Lou Dietz

Pascal Bamford

Lokesh Tatke

Suraj Somwanshi

Gregory C Loney

A facility includes systems and methods for providing a learning-based image analysis approach for the automated detection, classification, and counting of objects (e.g., cell nuclei) within digitized pathology tissue slides. The facility trains an object classifier using a plurality of reference sample slides. Subsequently, and in response to receiving a scanned image of a slide containing tissue data, the facility separates the whole slide into a background region and a tissue region using image segmentation techniques. The facility identifies dominant color regions within the tissue data and identifies seed points within those regions using, for example, a radial symmetry based approach. Based at least in part on those seed points, the facility generates a tessellation, each distinct area in the tessellation corresponding to a distinct detected object. These objects are then classified using the previously-trained classifier. The facility uses the classified objects to score slides.

Tissue object-based machine learning system for automated scoring of digital whole slides

Systems and techniques for an optical scanning microscope and/or other appropriate imaging system includes components for scanning and collecting focused images of a tissue sample and/or other object disposed on a slide. The focusing system described herein provides for determining best focus for each snapshot as a snapshot is captured, which may be referred to as 'on-the-fly focusing.' The devices and techniques provided herein lead to significant reductions in the time required for forming a digital image of an area in a pathology slide and provide for the creation of high quality digital images of a specimen at high throughput.

Method and device for slide scanning

The disclosure relates to devices, systems and methods for image registration and annotation. The devices include computer software products for aligning whole slide digital images on a common grid and transferring annotations from one aligned image to another aligned image on the basis of matching tissue structure. The systems include computer-implemented systems such as work stations and networked computers for accomplishing the tissue-structure based image registration and cross-image annotation. The methods include processes for aligning digital images corresponding to adjacent tissue sections on a common grid based on tissue structure, and transferring annotations from one of the adjacent tissue images to another of the adjacent tissue images.

Whole slide image registration and cross-image annotation devices, systems and methods

Processing of images acquired via fluorescence microscopy by identifying broadband and other undesired signals from the component signals of a scanned image, and processing selected regions of the image that are known to contain signals of interest, thereby extracting or identifying desired signals while subtracting undesired signals. One or more broadband signals are recognized by their unique signature and ubiquitous dispersion through the image. Regions of the scanned image may be tagged as consisting of predominantly broadband signals and are ignored during a spectral unmixing process. The remaining regions of the image, or selected regions of the image known to contain desired signals, may be unmixed, and the plurality of reference spectra subtracted from the components to extract or identify the target signals. The set of target signals may be refined by eliminating known or obvious sources of noise by, for instance, being compared to known or ideal sets of signals from similar materials.

Spectral unmixing

Device for a microscope stage

Method and device for slide caching

Provided herein are systems methods including a design of a microscope slide scanner for digital pathology applications which provides high quality images and automated batch-mode operation at low cost. The instrument architecture is advantageously based on a convergence of high performance, yet low cost, computing technologies, interfaces and software standards to enable high quality digital microscopy at very low cost. Also provided is a method based in part on a stitching method that allows for dividing an image into a number of overlapping tiles and reconstituting the image with a magnification without substantial loss of accuracy. A scanner is employed in capturing snapshot images. The method allows for overlapping images captured in consecutive snapshots.

Digital microscope slide scanning system and methods

Growing community of inventors

Cupertino, CA, United States of America

Bikash Sabata