This research presents a solution for classifying ultrasound diagnostic images describing five types of ovarian cyst as Hemorrhagic cyst, PCOS, Dermoid cyst, Endometriotic cyst, Malignant cyst. This work proposed a hybrid algorithmic technique for ovarian cyst image classification. Automatic feature extraction is implemented using recent deep learning neural network (DLNN) that extracts images. The DLNN consists of three dense layers. A proposed DLNNSVM approach outperforms existing learning approaches for ovarian cyst classification. Compared with DLNN and DLNNSVM, the performance of proposed method is better in precision, recall, accuracy and f1-measure.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.