System and Method Associated with Predicting Segmentation Quality of Objects in Analysis of Copious Image Data

A system to predict segmentation quality of segmented objects in image data, the system comprising:

• a computing device;
• and
• a non-transitory memory storing instructions that, when executed by the computing device, cause the computing device to perform operation comprising:
• accessing a trained classifier comprising at least one classification model trained during a training phase, the at least one classification model trained based on a training set of images with segmented objects, the images being partitioned into regions of interest (ROIs), each region of the ROIs being further partitioned into patches, and intensity and texture features being computed at a patch-level for each of the patches;
• receiving a test image with segmented objects during a classification phase in order to assess quality of segmentation of the segmented objects in the test image;
• partitioning the test image into a plurality of patches of a size equivalent to patches of the training set of images;
• computing intensity and texture features of the plurality of patches;
• and
• applying the trained classifier using the at least one classification model to iteratively classify segmentation quality of each patch of the plurality of patches based on the intensity and texture features of the plurality of patches as computed during classification and the patch-level intensity and texture features as computed during the training phase, the segmentation quality of each patch as classified predicting a segmentation quality of the segmented objects in each patch of the plurality of patches in the test image.