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US 10,872,410 B2Granted
Methods and apparatus for assessing immune system activity and therapeutic efficacy
AssigneeAnimantis, LLC
InventorsMartin Russell Blanchard, Ryan Stanley Kerwin, Bryan James Walker
Life of this patent
Estimating the term…
Abstract
Methods, compositions, and apparatuses are disclosed and described for assessing systemic immune response by monitoring changes of biophysical properties of mammalian immune cells or immune relevant bacterial cells in response to a gradient of chemoattractant in vitro.
Claims24
A system for classifying a cell, the system comprising:
- a sample vessel including:
- a sample reservoir configured to receive a sample and said sample reservoir comprising one or more cell adhesion molecules and a chemoattractant for an assay;
- an elongate channel;
- and
- a processing chamber in fluid communication with the sample reservoir through the elongate channel;
- an imaging device configured to capture images of the processing chamber;
- a control server configured to adjust the imaging device based at last in part on the assay;
- and
- an image processing system configured to:
- receive the images, wherein each image shows the cell, wherein a plurality of images generates a video;
- generate a binary image for each image included in the images, individual binary image indicating a set of locations within the respective image where the cell may be located;
- and
- for each binary image:
- generate a probability that each location in the set of locations is the location of the cell;
- assign one location from the set of locations for each binary image, the assignment maximizing the probability for all of the binary images;
- generate a set of metrics for the cell, the set of metrics generated using changes in a characteristic for the cell between binary images for sequentially captured images included in the video;
- and
- classify the cell using the set of metrics and a classification model, the classification model receiving at least a portion of the set of metrics as an input and generating a classification as an output.
15 more elements
A method of classifying a cell, the method comprising:
- combining the cell with a chemoattractant in a vessel having a first transparent portion;
- receiving a video including a plurality of images showing the cell through the first transparent portion;
- and
- for each image included in the plurality of images:
- identifying a set of locations within an image where the cell may be located using at least one of temporal variance in pixel values between images and pixel variance from a mean for the image, and
- generating a binary image for the image, the binary image indicating the set of locations;
- for each binary image:
- generating a probability that each location in the set of locations is the location of the cell;
- assigning one location from the set of locations for each binary image, the assignment maximizing the probability for all of the binary images;
- generating a set of metrics for the cell, the set of metrics generated using changes in location for the cell between binary images for sequentially captured images included in the video;
- obtaining a classification model, the classification model receiving at least a portion of the set of metrics as an input and generating a classification as an output;
- and
- classifying the cell using the set of metrics and the classification model.
10 more elements
A non-transitory computer-readable medium comprising instructions that, when executed by at least one processor of a computing device, cause the computing device to:
- receive a video including a plurality of images showing the cell through the first transparent portion;
- and
- for each image included in the plurality of images:
- identify a set of locations within an image where the cell may be located using at least one of temporal variance in pixel values between images and pixel variance from a mean for the image, and
- generate a binary image for the image, the binary image indicating the set of locations;
- and
- for each binary image:
- generate a probability that each location in the set of locations is the location of the cell;
- assign one location from the set of locations for each binary image, wherein the assignment maximizes the probability for all of the binary images;
- generate a set of metrics for the cell, the set of metrics generated using changes in location for the cell between binary images for sequentially captured images included in the video;
- obtain a classification model, the classification model receiving at least a portion of the set of metrics as an input and generating a classification as an output;
- and
- classify the cell using the set of metrics and the classification model.
10 more elements
A method of classifying a cell, the method comprising:
- receiving a video including a plurality of images showing the cell;
- generating a binary image for each image included in the plurality of images, individual binary image indicating a set of locations within the respective image where the cell may be located;
- and
- for each binary image:
- generating a probability that each location in the set of locations is the location of the cell;
- assigning one location from the set of locations for each binary image, the assignment maximizing the probability for all of the binary images;
- generating a set of metrics for the cell, the set of metrics generated using changes in a characteristic for the cell between binary images for sequentially captured images included in the video;
- and
- classifying the cell using the set of metrics and a classification model, the classification model receiving at least a portion of the set of metrics as an input and generating a classification as an output.
6 more elements
Dependencies are inferred from the claim text.