Patents by Inventor Gabriele CAMPANELLA

Gabriele CAMPANELLA has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20220292681
    Abstract: The present application relates generally to image tiling, including but not limited to systems and methods of fast whole slide tissue tiling. A computing system may identify a first image of a first dimension from which to select one or more tiles. The computing system may perform a reduction operation on the first image to generate a second image of a second dimension. The computing system may apply a thresholding operation on the second image to identify a first set of pixels corresponding to the presence of the feature and a second set of pixels corresponding to the absence of the feature based on an intensity of each pixel in the second image. The computing system may select, from a plurality of tiles corresponding to the first image, a subset of tiles corresponding to the first set of pixels identified from the second image.
    Type: Application
    Filed: August 24, 2020
    Publication date: September 15, 2022
    Inventors: Gabriele CAMPANELLA, Thomas FUCHS
  • Publication number: 20210295111
    Abstract: The present disclosure discusses systems and methods to detect blur in digital images. The solution can be incorporated into the quality control systems of pathology and other slide scanners or can be a stand-alone solution. The solution can identify scanned images that include blur and cause the scanner to automatically rescan the blurry image. The solution can also identify regions of the scanned image that include blur. The solution can generate blur maps for each of the scanned images that identify regions of the scanned image that include blur.
    Type: Application
    Filed: December 28, 2020
    Publication date: September 23, 2021
    Applicant: MEMORIAL SLOAN KETTERING CANCER CENTER
    Inventors: Gabriele CAMPANELLA, Peter J. SCHÜFFLER, Thomas FUCHS
  • Publication number: 20210049763
    Abstract: The present disclosure is directed to systems and methods for classifying biomedical images. A feature classifier may generate a plurality of tiles from a biomedical image. Each tile may correspond to a portion of the biomedical image. The feature classifier may select a subset of tiles from the plurality of tiles by applying an inference model. The subset of tiles may have highest scores. Each score may indicate a likelihood that the corresponding tile includes a feature indicative of the presence of the condition. The feature classifier may determine a classification result for the biomedical image by applying an aggregation model. The classification result may indicate whether the biomedical includes the presence or lack of the condition.
    Type: Application
    Filed: October 19, 2020
    Publication date: February 18, 2021
    Applicant: MEMORIAL SLOAN KETTERING CANCER CENTER
    Inventors: Thomas Fuchs, Gabriele Campanella
  • Patent number: 10878293
    Abstract: The present disclosure discusses systems and methods to detect blur in digital images. The solution can be incorporated into the quality control systems of pathology and other slide scanners or can be a stand-alone solution. The solution can identify scanned images that include blur and cause the scanner to automatically rescan the blurry image. The solution can also identify regions of the scanned image that include blur. The solution can generate blur maps for each of the scanned images that identify regions of the scanned image that include blur.
    Type: Grant
    Filed: August 30, 2017
    Date of Patent: December 29, 2020
    Assignee: MEMORIAL SLOAN KETTERING CANCER CENTER
    Inventors: Gabriele Campanella, Peter J. Schüffler, Thomas Fuchs
  • Patent number: 10810736
    Abstract: The present disclosure is directed to systems and methods for classifying biomedical images. A feature classifier may generate a plurality of tiles from a biomedical image. Each tile may correspond to a portion of the biomedical image. The feature classifier may select a subset of tiles from the plurality of tiles by applying an inference model. The subset of tiles may have highest scores. Each score may indicate a likelihood that the corresponding tile includes a feature indicative of the presence of the condition. The feature classifier may determine a classification result for the biomedical image by applying an aggregation model. The classification result may indicate whether the biomedical includes the presence or lack of the condition.
    Type: Grant
    Filed: October 11, 2019
    Date of Patent: October 20, 2020
    Assignee: Memorial Sloan Kettering Cancer Center
    Inventors: Thomas Fuchs, Gabriele Campanella
  • Patent number: 10685255
    Abstract: Systems and methods for training and using an image classifier are provided. A plurality of points can be generated from respective patches of images annotated as either a first type or a second type. The points corresponding to the images of the second type can be clustered into two clusters. A first cluster of the two clusters can be identified as closer to the points corresponding to the images annotated as the first type. The points in the first cluster can be assigned to a class positive, the points in the second cluster can be assigned to a class negative, and the points corresponding to the images annotated as the first type can be assigned to an anchor class. A plurality of triplets can be generated based on the points in the various classes. Parameters of an image classifier can be adjusted based on a loss function of the triplets.
    Type: Grant
    Filed: June 5, 2019
    Date of Patent: June 16, 2020
    Assignee: Memorial Sloan Kettering Cancer Center
    Inventors: Thomas Fuchs, Gabriele Campanella
  • Publication number: 20200043164
    Abstract: The present disclosure is directed to systems and methods for classifying biomedical images. A feature classifier may generate a plurality of tiles from a biomedical image. Each tile may correspond to a portion of the biomedical image. The feature classifier may select a subset of tiles from the plurality of tiles by applying an inference model. The subset of tiles may have highest scores. Each score may indicate a likelihood that the corresponding tile includes a feature indicative of the presence of the condition. The feature classifier may determine a classification result for the biomedical image by applying an aggregation model. The classification result may indicate whether the biomedical includes the presence or lack of the condition.
    Type: Application
    Filed: October 11, 2019
    Publication date: February 6, 2020
    Applicant: MEMORIAL SLOAN KETTERING CANCER CENTER
    Inventors: Thomas Fuchs, Gabriele Campanella
  • Patent number: 10445879
    Abstract: The present disclosure is directed to systems and methods for classifying biomedical images. A feature classifier may generate a plurality of tiles from a biomedical image. Each tile may correspond to a portion of the biomedical image. The feature classifier may select a subset of tiles from the plurality of tiles by applying an inference model. The subset of tiles may have highest scores. Each score may indicate a likelihood that the corresponding tile includes a feature indicative of the presence of the condition. The feature classifier may determine a classification result for the biomedical image by applying an aggregation model. The classification result may indicate whether the biomedical includes the presence or lack of the condition.
    Type: Grant
    Filed: March 22, 2019
    Date of Patent: October 15, 2019
    Assignee: Memorial Sloan Kettering Cancer Center
    Inventors: Thomas Fuchs, Gabriele Campanella
  • Publication number: 20190295252
    Abstract: The present disclosure is directed to systems and methods for classifying biomedical images. A feature classifier may generate a plurality of tiles from a biomedical image. Each tile may correspond to a portion of the biomedical image. The feature classifier may select a subset of tiles from the plurality of tiles by applying an inference model. The subset of tiles may have highest scores. Each score may indicate a likelihood that the corresponding tile includes a feature indicative of the presence of the condition. The feature classifier may determine a classification result for the biomedical image by applying an aggregation model. The classification result may indicate whether the biomedical includes the presence or lack of the condition.
    Type: Application
    Filed: March 22, 2019
    Publication date: September 26, 2019
    Inventors: Thomas Fuchs, Gabriele Campanella
  • Publication number: 20190197362
    Abstract: The present disclosure discusses systems and methods to detect blur in digital images. The solution can be incorporated into the quality control systems of pathology and other slide scanners or can be a stand-alone solution. The solution can identify scanned images that include blur and cause the scanner to automatically rescan the blurry image. The solution can also identify regions of the scanned image that include blur. The solution can generate blur maps for each of the scanned images that identify regions of the scanned image that include blur.
    Type: Application
    Filed: August 30, 2017
    Publication date: June 27, 2019
    Applicant: MEMORIAL SLOAN KETTERING CANCER CENTER
    Inventors: Gabriele CAMPANELLA, Peter J. SCHÜFFLER, Thomas FUCHS