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Abstract #4030

Deep Learning Model for Automatic Fetal Brain Landmark Localization in MRI

Jie Deng1,2, Xuchu Liu2, Jubril O Adepoju2, and Sharon E Byrd2
1Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, United States, 2Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago, IL, United States


Fetal MRI provides great anatomic details for diagnosis of perinatal disorders when ultrasound is inconclusive in assessing fetal anatomy during all phases of gestation. Immediate interventions can be attempted when abnormal anatomic changes of fetal brain structures are identified early during gestation. Size measurements of a fetal brain structure can be realized by identifying several landmarks of the structure accurately and calculating the distance between the landmarks. We developed a deep learning model that exploits U-net as a ‘transforming’ function to learn imaging features adjacent to a landmark point and predict the landmark location automatically.

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