Artificial Intelligence in Obstetric and Gynecological MR Imaging

Area of Science:

• Radiology
• Artificial Intelligence
• Women's Health

Background:

• Artificial intelligence (AI) is increasingly utilized in medical imaging.
• Obstetrics and gynecology (OB/GYN) MRI presents unique diagnostic challenges.
• The integration of AI aims to enhance diagnostic accuracy and efficiency in OB/GYN imaging.

Purpose of the Study:

• To review the progress and applications of AI in obstetrics and gynecological MRI.
• To highlight AI's role in diagnosing specific conditions like uterine leiomyosarcoma, endometrial cancer, cervical cancer, ovarian tumors, and placenta accreta.
• To discuss AI applications in segmentation and quality improvement for OB/GYN MRI.

Main Methods:

• Review of recent research (last few years) on AI applications in OB/GYN MRI.
• Analysis of studies employing AI for condition identification, segmentation, and quality enhancement.
• Exploration of foundational algorithmic techniques, deep learning, and radiomics.

Main Results:

• AI demonstrates significant progress in identifying various gynecological and obstetrical conditions using MRI.
• AI applications for image segmentation and quality improvement in OB/GYN MRI are effective.
• Advancements are driven by accessible datasets and multiparametric MRI.

Conclusions:

• AI integration in OB/GYN MRI enhances diagnostic accuracy and efficiency.
• Future directions include further AI research for personalized medicine in women's health.
• Challenges remain, but AI holds substantial potential for improved patient outcomes.