10X Genomics, Inc.

Lam Research Corporation

Dongyao Li

Neil Ira Weisenfeld

Paul Ryvkin

Michal Danek

Anand Chandrashekar

Augusto Manuel Tentori

Denis Pristinski

Atashi Basu

David M Fried

Ashkan Beyranvand Nejad

Preyas Shah

Kapil Umesh Sawlani

Pratomo Alimsijah

Michael Bowes

Xiaoyan Qian

Reynaldo Farias Zorrilla

William Nitsch

Provided herein are methods for image segmentation. An image having a plurality of pixels arranged in a plurality of dimensions is obtained. The image is provided to a pretrained machine learning model and a plurality of amplitudes for each of the plurality of pixel is received from the model. Each of the plurality of amplitudes for each of the plurality of pixels corresponds to exactly one of the plurality of dimensions. At least one instance in the image is identified by: determining a first basin associated with the at least one instance, where the basin consists of a contiguous subset of the plurality of pixels having an amplitude with a magnitude not exceeding first threshold, determining a second subset of the plurality of pixels having an amplitude with a magnitude exceeding the first threshold, where the second subset of pixels bounds the first subset of pixels, and constructing the at least one instance by a flow of the second subset of pixels to the first subset of pixels according to the amplitudes thereof.

Systems and methods for image segmentation

In embodiments, a method includes reading a nuclear segmentation mask of an image including pixels arranged in two dimensions. The nuclear segmentation mask identifies cellular nuclei stained with a cellular nucleus stain. The method includes determining amplitudes for each pixel. Each amplitude corresponds to exactly one dimension of the two dimensions. The method includes constructing a graph having nodes and edges. Each node corresponds to a pixel. Nodes corresponding to neighboring pixels are connected by an edge. The method includes assigning a weight to each edge. Each edge's weight is based on amplitudes of pixels corresponding to nodes connected thereby. The method further includes, based on the graph, determining, for each cellular nuclei, a heat map corresponding to a predicted cell region associated with that cellular nucleus. The method further includes based on the heat maps of the cellular nuclei, determining a cellular segmentation mask comprising predicted cell regions.

Systems and methods for image segmentation using multiple stain indicators

Systems and methods for spatial analysis of analytes are provided. A data structure is obtained comprising an image, as an array of pixel values, of a sample on a substrate having intersecting border regions, fiducial markers encoding N-digit codes, and a set of capture spots, where at least two border regions includes a fiducial marker. The pixel values are analyzed to identify locations of fiducial markers. The locations are aligned with locations of reference fiducial markers in a template using an alignment algorithm to obtain a final transformation between the fiducial markers in the image and the reference fiducial markers in the template. The final transformation and a coordinate system of the template are used to register the image to the set of capture spots. The registered image is then analyzed in conjunction with spatial analyte data associated with each capture spot, thereby performing spatial analysis of analytes.

Systems and methods for spatial analysis of analytes using fiducial alignment

Specimen substrate

A method of self-testing an imaging system of a sample handling apparatus is provided. Systems and non-transitory computer readable mediums performing the method are also provided.

Self-test for imaging device

Provided herein are systems and methods for optimizing feature fill processes. The feature fill optimization systems and methods may be used to optimize feature fill from a small number of patterned wafer tests. The systems and methods may be used for optimizing enhanced feature fill processes including those that include inhibition and/or etch operations along with deposition operations. Results from experiments may be used to calibrate a feature scale behavioral model. Once calibrated, parameter space may be iteratively explored to optimize the process.

Fill process optimization using feature scale modeling

Growing community of inventors

San Jose, CA, United States of America

Dongyao Li