FPDANet combines a ResNet backbone with dual attention and bilateral feature fusion to reach 91.05% top-1 accuracy on 21 fetal ultrasound view classes, but the architecture reuses known modules without citation and the evaluation lacks code, data, and error bars.
Practice guidelines for performance of the routine mid-trimester fetal ultrasound scan
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FPDANet: A Multi-Section Classification Model for Intelligent Screening of Fetal Ultrasound
FPDANet combines a ResNet backbone with dual attention and bilateral feature fusion to reach 91.05% top-1 accuracy on 21 fetal ultrasound view classes, but the architecture reuses known modules without citation and the evaluation lacks code, data, and error bars.