General Electric Company

Ge Healthcare Bio-sciences Corp.

Digital Pathco, LLC

Ge Healthcare Limited

Dirk Ryan Padfield

Jens Rittscher

Ali Can

Yousef Ahmed Al-Kofahi

Musodiq O Bello

Harvey E Cline

Robert John Filkins

Dashan Gao

James Vradenburg Miller

Thomas Baby Sebastian

Nicholas Thomas

Alberto Santamaria-Pang

Rahul Bhotika

Kevin Bernard Kenny

Brion Daryl Sarachan

Jilin Tu

Sheshadri Thiruvenkadam

Matthew William Turek

Paulo Ricardo Dos Santos Mendonca

Chandan Kumar Mallappa Aladahalli

Paulo Ricardo Mendonca

Michael Christopher Montalto

Fiona Ginty

Qing Li

Zhengyu Pang

Christopher James Sevinsky

Xiaofeng Liu

Shubao Liu

Megan Pearl Rothney

David LaVan Henderson

Ahmad Yekta

Navneeth Subramanian

Pavan Kumar Veerabhadra Annangi

Richard R McKay

Raghu Machiraju

Jyotirmoy Banerjee

Antti Seppo

Vipul A Baxi

Theresa Rose Broniak

Manasi Datar

Elizabeth P Roquemore

Umesha Adiga

Kishore Mosaliganti

Anand Magadi Narasimhamurthy

Anitti Eljas Seppo

Yousef Ahmed Al-kofahi

Antti Eljas Seppo

Fiona Mary Ginty

Systems and methods for determining parameters for image analysis are provided. One method includes obtaining ultrasound data of an object, generating an image of the object, and identifying a region of interest in the image. The method also includes determining a plurality of spatially varying parameters for image analysis of the region of interest using prior information for one or more objects of interest, including prior location information for the one or more objects of interest, and wherein the plurality of spatially varying parameters are determined for a plurality of sections of the region of interest and different for at least some of the plurality of sections. The method further includes using the plurality of spatially varying parameters for performing image analysis of the region of interest in the image to determine the location of the one or more objects of interest.

Systems and methods for determining parameters for image analysis

A computer-implemented method of processing image data representing biological units in a tissue sample includes receiving a first image of the tissue sample containing signals from an immunofluorescent (IF) morphological marker, wherein the tissue sample is stained with the IF morphological marker, and receiving a second image of the same tissue sample containing signals from a fluorescent probe, wherein the tissue sample is hybridized in situ with the fluorescent probe. The method further includes classifying each biological unit in the tissue sample into one of at least two classes based on a mean intensity of the signals from the IF morphological marker in the first image, performing a fluorescence in situ hybridization (FISH) analysis of the tissue sample in the second image to obtain results therefrom, and filtering the results of the FISH analysis to produce a subset of the results pertaining to biological units classified in one class.

Systems and methods for using an immunostaining mask to selectively refine ISH analysis results

The present techniques provide for the evaluation of cellular motion and/or cellular properties based on an analysis of motion for cluster of cells. In an exemplary technique, images of cells are acquired and the image is segmented into clusters. Motion data for each respective cluster is derived from the segmented data. The properties of each cluster can be used to evaluate cellular properties and/or cellular motion properties.

Automatic segmentation and characterization of cellular motion

The invention relates to a computer implemented method and systems for cell level fish dot counting. FISH (fluorescence in situ hybridization) dot counting is the process of enumerating chromosomal abnormalities in the cells which can be used in areas of diagnosis and cancer research. The method comprises in part overlaying images of a biological sample comprising a nuclear counterstain mask and a FISH binary mask. The FISH binary mask is extracted using a multi-level extended h-maxima or h-minima.

Method and systems for cell-level fish dot counting

Improved systems and methods for the analysis of digital images are provided. More particularly, the present disclosure provides for improved systems and methods for the analysis of digital images of biological tissue samples. Exemplary embodiments provide for: i) segmenting, ii) grouping, and iii) quantifying molecular protein profiles of individual cells in terms of sub cellular compartments (nuclei, membrane, and cytoplasm). The systems and methods of the present disclosure advantageously perform tissue segmentation at the sub-cellular level to facilitate analyzing, grouping and quantifying protein expression profiles of tissue in tissue sections globally and/or locally. Performing local-global tissue analysis and protein quantification advantageously enables correlation of spatial and molecular configuration of cells with molecular information of different types of cancer.

System and method for multiplexed biomarker quantitation using single cell segmentation on sequentially stained tissue

Methods, systems and computer program products for estimating the gestational age of a fetus are provided. According to one embodiment, the method generates a component image from a segmented ultrasound image of a fetal head. The component image includes one or more edges. The method then identifies a third ventricle within the component image. The method estimates a length of a bi-parietal diameter, based at least in part on the orientation of the third ventricle. Thereafter, the method estimates the gestational age of the fetus.

Methods and systems for estimating gestation age of a fetus

A method for automatically measuring interventricular septum thickness is provided. The method in one embodiment comprises acquiring a series of ultrasound images of a heart, acquiring a septum mask by applying a septum segmentation algorithm on the series of ultrasound images, localizing a mitral valve tip using a valve tip localization algorithm and calculating the thickness of the interventricular septum using an interventricular septum thickness algorithm. The interventricular septum thickness algorithm uses the septum mask and the localized mitral valve tip as inputs.

Methods and apparatus for automated measuring of the interventricular septum thickness

Systems and methods for segmenting images comprising cells, wherein the images comprise a plurality of pixels; one or more three dimensional (3D) clusters of cells are identified in the images; and the 3D clusters of cells are automatically segmented into individual cells using one or more models.

Methods and systems for automated segmentation of dense cell populations

Systems and methods for extracting information about an organism of interest, such as an atlas of the organism of interest; a storage device for at least temporarily storing an image of the organism of interest; and an operating device that automatically creates a map of the image of the organism of interest and automatically compares the map of the image to the atlas of the organism.

Systems and methods for automated extraction of high-content information from whole organisms

This invention, which provides a method for detecting a corruption in an image acquired from a biological sample, includes: providing at least one image of at least one cell; generating the image of the at least one cell over a period of time; determining if the at least one image of the at least one cell is corrupted; applying a wavelet transform, Fourier transform, or other frequency decomposing transform to the at least one image to decompose the at least one image into a plurality of sub-images, wherein the plurality of sub-images have a plurality of low frequency channels, a plurality of middle frequency channels and a plurality of high frequency channels; calculating a ratio based on an energy level of the plurality of low frequency channels and the plurality of middle frequency channels; and removing the at least one image of at least one cell if the at least one image is corrupted.

System and method for detecting and eliminating one or more defocused or low contrast-to-noise ratio images

Image quality is assessed for a digital image that is a composite of tiles or other image segments, especially focus accuracy for a microscopic pathology sample. An algorithm or combination of algorithms correlated to image quality is applied to pixel data at margins where adjacent image segments overlap and thus contain the same content in separately acquired images. The margins may be edges merged to join the image segments smoothly into a composite image, and typically occur on four sides of the image segments. The two versions of the same image content at each margin are processed by the quality algorithm, producing two assessment values. A sign and difference value are compared with other image segments, including by subsets selected for the orientation of the margins on sides on the image segments. The differences are mapped to displays. Selection criteria determine segments to be re-acquired.

Image quality assessment including comparison of overlapped margins

The present techniques provide for the processing of color tissue images based on image segmentation. In an exemplary embodiment, the color and texture features of pixels in a tissue image are used to generate a matrix of feature vectors. A subset of feature vectors is selected from the matrix of feature vectors and a set of colors and textures are derived using the tissue image and the subset of feature vectors. An initial segmented tissue image is then generated from this set of colors and textures.

Segmentation of tissue images using color and texture

The present invention provides a cell imaging technique for automatically tracking the progression of a cell through the cell cycle over time through segmentation of a volume of two-dimensional time-lapse images. The technique allows long-term tracking of the cell cycle progression of an individual cell or multiple cells. Further, the invention provides a unique display of cell cycle progression, allowing an end user to easily determine changes to cell cycle progression for a cell of interest.

Time-lapse cell cycle analysis of unstained nuclei

An imaging system for correcting a bias in the location edges in an image is provided. The imaging system comprises an image processor configured to detect edges in an image of a given substructure, characterize a blurring factor in the image and correct a bias in the detected edges in the of a given substructure using the blurring factor.

Edge detection and correcting system and method

Growing community of inventors

Albany, NY, United States of America

Dirk Ryan Padfield