Standard/non-standard (S-NS) plane classification is a key step for Nuchal Translucency measurement and early Down Syndrome assessment in fetus during pregnancy weeks 11–14. To classify S-NS planes, fetal intracranial structures have to be identified with high precision and low latency. This paper presents a comparative study between YOLOv8 and YOLO-NAS for the identification of fetal intracranial structures during pregnancy weeks 11–14. Using a diverse dataset comprising 1528 2D sagittal-view ultrasound images from 1519 females, we evaluate the performance of these state-of-the-art object detection models. The dataset includes meticulously labelled instances of crucial fetal intracranial structures such as thalami, nasal bone, palate, 4th ventricle, cisterna magna, NT (nuchal translucency), nasal tip, nasal skin and midbrain. Through comprehensive experiments and analysis, this research sheds light on the suitability of these YOLO variants for accurate and efficient detection of these structures in early-stage pregnancies, providing valuable insights for improving prenatal healthcare and diagnosis.