Method for training machine learning model to analyze immunohistochemically stained images and computing system performing same

A machine learning model training system comprising:

• a processor;
• and
• a memory storing a computer program,
• wherein:
• the computer program, when executed by the processor, causes the machine learning model training system to perform a machine learning model training method;
• the machine learning model training method comprises:
• generating, by the machine learning model training system, a training data set including M pieces of individual training data (where M is a natural number of 2 or more);
• and
• training, by the machine learning model training system, the machine learning model based on the training data set;
• the generating of the training data set including the M pieces of individual training data comprises, for all integers m where 1<=m<=M, generating mth training data to be included in the training data set;
• the generating of the mth training data comprises:
• acquiring an mth immunohistochemically stained image, wherein the mth immunohistochemically stained image includes an area corresponding to an immunohistochemically stained tissue stained by an immunohistochemistry (IHC) staining method for staining a predetermined target biomarker;
• calculating a staining intensity by immunohistochemical staining for each pixel of the mth immunohistochemically stained image;
• for all integers n where 1<=n<=N (where N is an integer of 2 or more), generating an nth feature vector of the mth immunohistochemically stained image based on the staining intensity for each pixel of the mth immunohistochemically stained image and a predetermined nth staining intensity reference value;
• and
• generating the mth training data based on the first staining intensity reference value to the Nth staining intensity reference value and the first feature vector to the Nth feature vector of the mth immunohistochemically stained image;
• and
• the generating of the nth feature vector of the mth immunohistochemically stained image based on the staining intensity for each pixel of the mth immunohistochemically stained image and the predetermined nth staining intensity reference value comprises:
• generating an nth binarized image corresponding to the mth immunohistochemically stained image by comparing the staining intensity for each pixel of the mth immunohistochemically stained image with the nth staining intensity reference value, wherein the nth binarized image is an image divided into an area having a staining intensity greater than the nth staining intensity reference value and an area not having the same;
• and
• generating the nth feature vector of the mth immunohistochemically stained image based on the nth binarized image corresponding to the mth immunohistochemically stained image.