Systems and methods for segmentation and processing of tissue images and feature extraction from same for treating, diagnosing, or predicting medical conditions

A system comprising:

• one or more processors configured to interact with a computer-readable medium in order to perform operations comprising:
• receiving within a memory of the processor, an image of at least one tissue;
• segmenting nuclei of a cellular region within the image into individually contiguous regions;
• extracting one or more epithelial nuclei centers;
• partitioning the image into polygonal regions with the one or more epithelial nuclei centers at the vertices, thereby identifying one or more triangles;
• merging one or more regions of the one or more triangles, thereby identifying one or more polygonal areas within the tissue;
• classifying at least one of the one or more polygonal areas as at least one of:
• (a) gland rings,
• (b) glandular non-rings,
• (c) stroma regions
• (d) under-segmented regions, and
• (e) incomplete regions;
• evaluating a dataset with a predictive model stored within a memory of the processor, the model being based on one or more ring features selected from the group of ring features consisting of:
• one or more ring metrics, feature(s) derived from one or more ring metrics, and feature(s) representing an adjacency relationship between rings;
• and
• generating an evaluation of a medical condition by outputting a value indicative of the medical condition in the patient.

A computer implemented method comprising:

• receiving an image of at least one tissue within the memory of a computer;
• performing, using code executing in at least one or more processors of the computer, triangulation on the tissue image with epithelial nuclei centers as vertices, thereby identifying one or more triangles having one or more regions;
• identifying one or more polygonal areas within the tissue by merging one or more regions of the one or more triangles;
• classifying, with the at least one or more processors, at least one of the one or more polygonal areas as at least one of:
• (a) gland rings,
• (b) glandular non-rings,
• (c) stroma regions,
• (d) under-segmented regions, and
• (e) incomplete regions;
• storing the classified image to at least one data storage device as a patient dataset;
• evaluating the patient dataset with a predictive model using code executing in at least one or more processors of the computer, the model being based on one or more ring features selected from the group of ring features consisting of:
• one or more ring metrics,
• feature(s) derived from one or more ring metrics, and
• feature(s) representing an adjacency relationship between rings;
• and
• providing, based on the evaluating, output data indicative of the medical condition of the patient.