Ventana Medical Systems, Inc.

Koninklijke Philips Corporation N.v.

Hoffmann-la Roche Inc.

Grail, Inc.

Koninklike Philips N.v.

University of California

F. Hoffmann-la Roche Ag

Joerg Bredno

Srinivas Chukka

Jim F Martin

Juergen Weese

Anindya Sarkar

Michael S Barnes

Alexandra Groth

Eberhard Sebastian Hansis

Sven Prevrhal

Christophe Chefd'hotel

Ting Chen

Sabine Mollus

Lingxiong Shao

Christoph Herrmann

Gereon Vogtmeier

Jinghan Ye

William Kenneth Day

Xiyun Song

Onur Sakarya

Drazenko Babic

Peter Maria Johannes Rongen

Arash Jamshidi

David Sowards-Emmerd

Kien Nguyen

Kandavel Shanmugam

Max Wintermark

Kirsten Regina Meetz

Chi-Hua Tung

Jens Wiegert

Kai Eck

Yao Nie

Heidrun Steinhauser

Klaus Juergen Engel

Rainer Kiewitt

Norbert Conrads

Christian Baeumer

Helko Lehmann

Christoph Neukirchen

Martin Weibrecht

Matthias Bertram

Samuel S Gross

Ingwer Curt Carlsen

Oliver Claude Venn

Noemi Sebastiao

M Cyrus Maher

Seyedmehdi Shojaee

Auranuch Lorsakul

Mark Olszewski

Astrid Heller

Gabriele Hoelzlwimmer

Rebecca C Bowermaster

Wen-Wei Liu

Junming Zhu

Konstanty Korski

Jason Stephen Wiener

Oliver Grimm

Patrick Olivier

Georg Rose

Lou Dietz

Olivier Ecabert

Alisa Tubbs

Christoph Guetter

Amy Perkins

Ronaldus Petrus Johannes Hermans

Alexander P Fields

Mehrnoush Khojasteh

Ellen Suzue

Antonius Johannes Cornelius Bruijns

Qinwen Liu

Eberhard Sevastian Hansis

Harit Nandani

Jafi Lipson

Max Weiland Rosen

Kathan Roberts

Robert Ochs

Ilya Ravkin

Smadar Shiffman

Xingwei Wang

Steffen Gunther Hohmann

Jan Schellenberger

Christophe Chefd´hotel

William Day

Jim Martin

John F Beausang

Christophe CHEFD`HOTEL

Michael Barnes

Techniques for acquiring focused images of a microscope slide are disclosed. During a calibration phase, a 'base' focal plane is determined using non-synthetic and/or synthetic auto-focus techniques. Furthermore, offset planes are determined for color channels (or filter bands) and used to generate an auto-focus model. During subsequent scans, the auto-focus model can be used to quickly estimate the focal plane of interest for each color channel (or filter band) rather than re-employing the non-synthetic and/or synthetic auto-focus techniques.

Auto-focus methods and systems for multi-spectral imaging

Techniques described herein pertain to automated systems and methods for analyzing, storing, and/or retrieving information associated with biological objects including lymphocytes. In some embodiments, a shape metric is derived for each detected and segmented lymphocyte and the shape metric is stored along with other relevant data.

Systems for cell shape estimation

Immune context scores are calculated for tumor tissue samples using continuous scoring functions. Feature metrics for at least one immune cell marker are calculated for a region or regions of interest, the feature metrics including at least a quantitative measure of human CD3 or total lymphocyte counts. A continuous scoring function is then applied to a feature vector including the feature metric and at least one additional metric related to an immunological biomarker, the output of which is an immune context score. The immune context score may then be plotted as a function of a diagnostic or treatment metric, such as a prognostic metric (e.g. overall survival, disease-specific survival, progression-free survival) or a predictive metric (e.g. likelihood of response to a particular treatment course). The immune context score may then be incorporated into diagnostic and/or treatment decisions.

Methods and systems for evaluation of immune cell infiltrate in tumor samples

The subject disclosure presents systems and methods for automatically selecting meaningful regions on a whole-slide image and performing quality control on the resulting collection of FOVs. Density maps may be generated quantifying the local density of detection results. The heat maps as well as combinations of maps (such as a local sum, ratio, etc.) may be provided as input into an automated FOV selection operation. The selection operation may select regions of each heat map that represent extreme and average representative regions, based on one or more rules. One or more rules may be defined in order to generate the list of candidate FOVs. The rules may generally be formulated such that FOVs chosen for quality control are the ones that require the most scrutiny and will benefit the most from an assessment by an expert observer.

Quality control of automated whole-slide analyses

The present disclosure is directed, among other things, to automated systems and methods for analyzing, storing, and/or retrieving information associated with biological objects having irregular shapes. In some embodiments, the systems and methods partition an input image into a plurality of sub-regions based on localized colors, textures, and/or intensities in the input image, wherein each sub-region represents biologically meaningful data.

Method of storing and retrieving digital pathology analysis results

Disclosed herein are systems and methods of estimating the autofluorescence (AF) signal and other non-target signals in each channel of a multi-channel image of a biological sample that is stained with one or more fluorescent labels. In some embodiments, the estimated autofluorescence signal can then be subtracted or masked from the multi-channel image. In some embodiments, the autofluorescence-removed multichannel image can then be use for further processing (e.g. image analysis, etc.).

Systems and methods for computing the contributions of autofluorescence in multichannel image

According to various embodiments, a system and method for processing an image of a biological specimen stained for a presence of at least one lymphocyte biomarker is disclosed. The system and method are configured to detect lymphocytes in the image and compute a foreground segmentation mask based on the lymphocytes detected within the image. Outlines of the detected lymphocytes are identified in the image by filtering the image with the computed foreground segmentation mask. A shape metric may be derived for each of the detected lymphocytes based on the identified lymphocytes outlines. The derived shape metric may be associated with location information for each of the detected lymphocytes and a value of each of the derived shape metric may be compared to a predetermined threshold value. A predictive cell motility label may be assigned to each of the detected lymphocytes based on the comparison.

A method for extracting information from a dataset, e.g., a document, includes: receiving the dataset at an information handling device, optionally, extracting, via optical character recognition implemented by a processor of the information handling device, textual information associated with the dataset, and classifying the dataset into one of a plurality of classes. Classifying the dataset may include computing a similarity score for each of the plurality of classes for each of a plurality of window regions of the dataset, calculating a subset of highest similarity scores for each of the plurality of classes for each of the plurality of window regions, determining overall similarity scores for each of the plurality of classes, and classifying the dataset as corresponding to a class with a highest overall similarity score.

Systems and methods for automated classification of a document

The present application provides for systems and methods for detecting and estimating signals corresponding to one or more biomarkers in biological samples stained for the presence of protein and/or nucleic acid biomarkers. On particular aspect is directed to a method of estimating an amount of signal corresponding to at least one biomarker in an image of a biological sample. The method includes detecting isolated spots in a first image, deriving an optical density value of a representative isolated spot based on signal features from the detected isolated spots, estimating a number of predictive spots in signal aggregates in each of a plurality of sub-regions based on the derived optical density value of the representative isolated spot, and storing the estimated number of predictive spots and detected isolated spots in each of the plurality of generated sub-regions in a database.

Quantitation of signal in stain aggregates

Growing community of inventors

San Francisco, CA, United States of America

Joerg Bredno