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| Current research status of artificial intelligence for endometrial cancer recognition in nuclear magnetic images |
| CHU Zebin1 AN Yuepan2 LI Xiaohe1 LIU Wei2 |
1.Graduate School, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot 010000, China;
2.Department of Gynaecology, Inner Mongolia Maternal and Child Health Care Hospital, Inner Mongolia Autonomous Region, Hohhot 010000, China |
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Abstract With the increasing incidence rate of endometrial cancer, accurate and rapid early diagnosis is crucial for the treatment and prognosis of patients. Magnetic resonance imaging plays an important role in the diagnosis of endometrial cancer, however, relying on traditional visual interpretation still has some limitations. In recent years, the rapid development of artificial intelligence technology has brought new possibilities for medical imaging diagnosis. Through deep learning and machine learning algorithms, features can be effectively extracted from a large amount of magnetic resonance imaging data, and endometrial cancer lesions can be automatically identified, further assisting doctors in disease staging and treatment decision-making. At present, the application of artificial intelligence in endometrial cancer is still in the exploratory stage, and it still faces some challenges. The scale and diversity of datasets are key issues in current research. In addition, applying these technologies to clinical practice requires more clinical validation and strict regulation. Overall, the use of artificial intelligence for identifying magnetic resonance images further demonstrates potential application value. With the further development of technology and the continuous accumulation of more data, it is believed that artificial intelligence will play an increasingly important role in the early diagnosis and treatment of endometrial cancer.
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