Keywords: AI/ML Software, Data Processing, Fetal, Placenta
Motivation: The radiological assessment of fetal MRIs continues to face challenges related to access to care, timing of diagnosis, and associated costs.
Goal(s): To develop a web application that assists with the radiological processing of fetal MRIs.
Approach: We developed the Fetal Assessment Suite (FetAS), a web application that permits cloud-based use of our automatic fetal MRI processing algorithms, including artifact detection, motion correction, segmentations, biometric measurements, orientation and abnormality detection.
Results: Users can upload DICOM datasets which are automatically deidentified, detect artifact severity, reduce motion artifacts, and utilize cloud-based computing on our previously developed segmentation and classification algorithms.
Impact: FetAS provides clinicians with advanced fetal MRI diagnostic tools, enhancing efficiency and patient outcomes while supporting limited fetal radiological expertise. It also accelerates fetal MRI research by enabling systematic data extraction. FetAS is currently in a multisite clinical validation study.
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