FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery

FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)

Abstract:

Goal: FetSAM represents a cutting-edge deep learning model aimed at revolutionizing fetal head ultrasound segmentation, thereby elevating prenatal diagnostic precision. Methods: Utilizing a comprehensive dataset-the largest to date for fetal head metrics-FetSAM incorporates prompt-based learning. It distinguishes itself with a dual loss mechanism, combining Weighted DiceLoss and Weighted Lovasz Loss, …

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