Progress of machine learning based on magnetic resonance imaging for orbital tumor research
Orbital tumors vary in location and histopathological differences,presenting diagnostic challenges. Although advances in imaging technology have improved this problem,its classification and identification remains a challenge. As a key branch of artificial intelligence,machine learning has achieved certain results in the medical field,especially its combination with imaging and ophthalmology has greatly promoted the precision treatment of orbital tumors,and it has shown great potential and broad application prospects in tumor identification,lesion segmentation and image reconstruction,which is expected to improve the diagnosis level of orbital tumors and reduce the cost of clinical practice. This article reviews the application of MRI-based machine learning technology in orbital tumors,aiming to provide clinicians and radiologists with ideas for the diagnosis,treatment and prognosis of orbital tumors,and to further promote the application and popularization of machine learning in this field.
orbital tumorsmagnetic resonance imagingmachine learningdifferential diagnosisefficacy predictionprognosis
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