Automatic endometrial cancer segmentation based on deep learning
L. Feng, Changpu Chen, Ye Li, Siwei Zhang · IET conference proceedings. · 2024
The incidence of endometrial cancer, a malignant neoplasm originating from endometrial glands, has been on the rise in recent years, and is close to or even exceeding that of cervical cancer.Magnetic resonance imaging (MRI) can clearly show the size and extent of the endometrial cancer, so as to accurately estimate the stage of the tumor, therefore, the application of magnetic resonance imaging in the hospital more preoperative evaluation.Deep learning (DL) as a new computer-aided diagnosis method has been widely used in medical image processing which can reduce the misdiagnosis by radiologists.In this study, an image segmentation technique based on deep learning was used to locate endometrial cancer lesions quickly and accurately, artificial intelligence can also be used to help medical laboratory students to use computers to learn.