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Ovarian Cyst Detection Using Neural Networks

The ovarian cyst is an abnormal health condition most common for women in reproductive age. Hormonal shifts and imbalances in the body arise which affects the normal well-being. Early diagnosis is essential to eradicate further complications. Ultrasound imaging helps in detecting the amount and size of the cysts in the ovary. Manual tracking and detection of the type of cyst prolong the diagnosing period. In this paper, an innovative method for automated classification of the type of cysts in the digital ultrasound images is proposed. This method employs preprocessing, segmentation to get the required ROI and Feature Extraction to extract the necessary feature vectors. The classification method, Convolutional Neural Networks (CNN) estimates the abnormalities and also detects the type of Ovarian cysts which include Dermoid cyst, Hemorrhagic cyst, and Endometrioma cyst. Our automated diagnostic tool aims at reducing the cost and diagnosing period to provide accurate treatment as soon as possible