Dataset Overview Title: Large-Scale Annotation Dataset for Fetal Head Biometry in Ultrasound Images License: Creative Commons Attribution 4.0 International (CC BY 4.0) Total Images: 3,832 Image Dimensions: 959 x 661 pixels Description: This dataset provides a comprehensive collection of ultrasound images focusing on fetal head biometry. It is designed to support the development and evaluation of image segmentation and biometric analysis algorithms in prenatal diagnostics. The images have been carefully annotated by experts in the field, ensuring high-quality data for researchers. For additional details, including data structure, annotation guidelines, and access instructions, please refer to the readme.txt file included in the dataset package. Citation Instructions: If you utilize this dataset in your research, please acknowledge the work of the contributors by citing the following papers: Dataset Paper:Mahmood Alzubaidi, Marco Agus, Michel Makhlouf, Fatima Anver, Khalid Alyafei, Mowafa Househ, "Large-Scale Annotation Dataset for Fetal Head Biometry in Ultrasound Images," Data in Brief, 2023, 109708, ISSN 2352-3409.DOI: https://doi.org/10.1016/j.dib.2023.109708 Baseline Paper:M. Alzubaidi, U. Shah, M. Agus, and M. Househ, "FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery," IEEE Open Journal of Engineering in Medicine and Biology.DOI: https://ieeexplore.ieee.org/document/10480532 Review Paper: Alzubaidi, M., Agus, M., Alyafei, K., Althelaya, K.A., Shah, U., Abd-Alrazaq, A., Anbar, M., Makhlouf, M. and Househ, M., 2022. Toward deep observation: A systematic survey on artificial intelligence techniques to monitor fetus via ultrasound images. Iscience. DOI: https://doi.org/10.48550/arXiv.2201.07935 How Pixel is Converted Into Millimeter: Alzubaidi, M., Shah, U., Shah, H. and Househ, M., 2023, August. Conversion of Pixel to Millimeter in Ultrasound Images: A Methodological Approach and Dataset. In 2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) (pp. 1-6). IEEE. DOI: https://ieeexplore.ieee.org/document/10264909 Keywords: Ultrasonic imaging, Image segmentation, Head, Brain modeling, Biological system modeling, Imaging, Ultrasonic variables measurement, Fetal Ultrasound Imaging, Image Segmentation, Prompt-based Learning, Prenatal Diagnostics, Ultrasound Biometrics.