Difficulty in detecting tumours in early stages is the major cause of mortalities in patients,
despite the advancements in treatment and research regarding ovarian cancer. Deep …

Ovarian cancer is one of the leading causes of death worldwide among the female
population. Early diagnosis is crucial for patient treatment. In this work, our main objective is …

Deep Learning models have shown tremendously impressive performance on image
classification tasks. In the medical imaging domain, progress has been made in obtaining …

In recent days, artificial intelligence (AI) is gaining worldwide popularity in several industries
among which healthcare is an important sector. AI is being used in healthcare to reduce …

The classification of tumours into benign and malignant continues to date to be a very
relevant and significant research topic in the cancer research domain. With the advent of …

Ovarian cancer is one of the most common gynecologic malignancies. Accurate
classification of ovarian cancer types (serous carcinoma, mucous carcinoma, endometrioid …

Ovaries are important part of female reproductive system. The importance of these tiny
glands is derived from the production of female sex hormones and female gametes. The …

Background Upon the discovery of ovarian cysts, obstetricians, gynecologists, and
ultrasound examiners must address the common clinical challenge of distinguishing …

Discrimination of ovarian tumors is necessary for proper treatment. In this study, we
developed a convolutional neural network model with a convolutional autoencoder (CNN …

Ovarian cancer ranks as the fifth leading cause of cancer-related mortality in women. Late-
stage diagnosis (stages III and IV) is a major challenge due to the often vague and …