Identifying abnormal images in set of medical images based on combined feature set with global features extracted using first cnn and local features extracted using second cnn analyzing high resolution image patches

Abstract

Disclosed herein is a method and system for identifying abnormal images in a set of medical images for optimal assessment of the medical images. A plurality of global features from each medical image is extracted based on pretrained weights associated with each global feature. Similarly, plurality of local features from each medical image is extracted analyzing a predefined number of image patches generated from a higher resolution image corresponding to each medical image. Further, an abnormality score for each medical image is determined based on weights associated with a combined feature set obtained by concatenating the plurality of global features and the plurality of local features. Thereafter, the medical image is identified as an abnormal image when the abnormality score of the medical image is higher than a predefined first threshold score.