Fully supervised medical image segmentation methods use pixel-level labels to achieve
good results, but obtaining such large-scale, high-quality labels is cumbersome and time …

Endometrial cancer, one of the three major malignant tumors of the female genitalia, has
seen an increase in incidence in recent years. The 5-year survival rate for early endometrial …

Medical image segmentation can effectively identify lesions in medicine, but some small and
rare lesions cannot be well identified. Existing studies do not take into account the …

Uterine segmentation of endometrial cancer MR images can be a valuable diagnostic tool
for gynecologists. However, uterine segmentation based on deep learning relies on artificial …

Preoperative MR imaging in endometrial cancer patients provides valuable information on
local tumor extent, which routinely guides choice of surgical procedure and adjuvant …

Endometrial cancer is the most common gynecological malignant tumor in developed
countries, and accurate preoperative risk stratification is essential for personalized medicine …

Background Epithelial ovarian cancer (EOC) segmentation is an indispensable step in
assessing the extent of disease and guiding the treatment plan that follows. Currently …

Early treatment increases the 5-year survival rate of patients with endometrial cancer (EC).
Deep learning (DL) as a new computer-aided diagnosis method has been widely used in …

Endometrial cancer (EC) is the most common gynecological tumor in developed countries,
and preoperative risk stratification is essential for personalized medicine. There have been …

The segmentation of cardiac MR images requires extensive attention as it needs a high level
of care and analysis for the diagnosis of affected part. The advent of deep learning …