Abstract: An exemplary method for determining a sampling protocol for sampling tissue cores for a tissue microarray includes obtaining an initial plurality of tissue cores from an image of a tissue slide; selecting a first subset of the initial plurality of tissue cores based on a first candidate sampling protocol; inputting the first subset of the plurality of tissue cores into a machine learning model; evaluating the first candidate sampling protocol by evaluating a first output of the machine learning model; selecting a second subset of the initial plurality of tissue cores based on a second candidate sampling protocol; inputting the second subset of the plurality of tissue cores into the machine learning model; evaluating the second candidate sampling protocol by evaluating a second output of the machine learning model; and determining the sampling protocol based on the evaluation of the first candidate sampling protocol and the second candidate sampling protocol.

Abstract: A method for filtering out artifacts from a microscopic image of a tissue includes determining a plurality of frequency values corresponding to a plurality of pixels in the microscopic image of the tissue; grouping the plurality of pixels into a plurality of pixel clusters based on the plurality of frequency values corresponding to the plurality of pixels; identifying, from the plurality of pixel clusters, one or more pixel clusters corresponding to one or more artifacts in the microscopic image; and filtering the microscopic image by removing one or more regions in the microscopic image corresponding to the one or more pixel clusters corresponding to the one or more artifacts.

Abstract: An exemplary method for determining a sampling protocol for sampling tissue cores for a tissue microarray includes obtaining an initial plurality of tissue cores from an image of a tissue slide; selecting a first subset of the initial plurality of tissue cores based on a first candidate sampling protocol; inputting the first subset of the plurality of tissue cores into a machine learning model; evaluating the first candidate sampling protocol by evaluating a first output of the machine learning model; selecting a second subset of the initial plurality of tissue cores based on a second candidate sampling protocol; inputting the second subset of the plurality of tissue cores into the machine learning model; evaluating the second candidate sampling protocol by evaluating a second output of the machine learning model; and determining the sampling protocol based on the evaluation of the first candidate sampling protocol and the second candidate sampling protocol.

Abstract: A method for filtering out artifacts from a microscopic image of a tissue includes determining a plurality of frequency values corresponding to a plurality of pixels in the microscopic image of the tissue; grouping the plurality of pixels into a plurality of pixel clusters based on the plurality of frequency values corresponding to the plurality of pixels; identifying, from the plurality of pixel clusters, one or more pixel clusters corresponding to one or more artifacts in the microscopic image; and filtering the microscopic image by removing one or more regions in the microscopic image corresponding to the one or more pixel clusters corresponding to the one or more artifacts.