@inproceedings{Dubost2019,
  year = {2019},
  pages = {438--446},
  author = {Florian Dubost and Gerda Bortsova and Hieab Adams and M. Arfan Ikram and Wiro Niessen and Meike Vernooij and Marleen de Bruijne},
  title = {Hydranet: Data Augmentation for Regression Neural Networks},
  booktitle = {MICCAI}
}

@article{JARDIM2005243,
title = "Segmentation of fetal ultrasound images",
journal = "Ultrasound in Medicine and Biology",
volume = "31",
number = "2",
pages = "243 - 250",
year = "2005",
author = "Sandra M.G.V.B. Jardim and Mário A.T. Figueiredo",
keywords = "Ultrasound images, Fetal anatomic structures, Contour estimation, Statistical framework, Maximum likelihood criterion, Region-based model",
abstract = "This paper describes a new method for segmentation of fetal anatomic structures from echographic images. More specifically, we estimate and measure the contours of the femur and of cranial cross-sections of fetal bodies, which can thus be automatically measured. Contour estimation is formulated as a statistical estimation problem, where both the contour and the observation model parameters are unknown. The observation model (or likelihood function) relates, in probabilistic terms, the observed image with the underlying contour. This likelihood function is derived from a region-based statistical image model. The contour and the observation model parameters are estimated according to the maximum likelihood (ML) criterion, via deterministic iterative algorithms. Experiments reported in the paper, using synthetic and real images, testify for the adequacy and good performance of the proposed approach. (E-mail: sandraj@est.ipcb.pt)"
}

@article{LU2005929,
title = "Automated fetal head detection and measurement in ultrasound images by iterative randomized hough transform",
journal = "Ultrasound in Medicine & Biology",
volume = "31",
number = "7",
pages = "929 - 936",
year = "2005",
author = "Wei Lu and Jinglu Tan and Randall Floyd",
keywords = "Object detection, Randomized Hough transform, Fetal ultrasound, Fetal growth, Image processing, Pattern recognition",
abstract = "An image-processing and object-detection method was developed to automate the measurements of biparietal diameter (BPD) and head circumference (HC) in ultrasound fetal images. The heads in 214 of 217 images were detected by an iterative randomized Hough transform. A head was assumed to have an elliptical shape with parameters progressively estimated by the iterative randomized Hough transform. No user input or size range of the head was required. The detection and measurement took 1.6 s on a personal computer. The interrun variations of the algorithm were small at 0.84% for BPD and 2.08% for HC. The differences between the automatic measurements and sonographers’ manual measurements were 0.12% for BPD and −0.52% for HC. The 95% limits of agreement were −3.34%, 3.58% for BPD and −5.50%, 4.45% for HC. The results demonstrated that the automatic measurements were consistent and accurate. This method provides a valuable tool for fetal examinations. (E-mail: TanJ@missouri.edu)"
}

@inproceedings{HC2019confident,
  title={Confident Head Circumference Measurement from Ultrasound with Real-time Feedback for Sonographers},
  author={Budd, Samuel and Sinclair, Matthew and Khanal, Bishesh and Matthew, Jacqueline and Lloyd, David and Gomez, Alberto and Toussaint, Nicolas and Robinson, Emma C and Kainz, Bernhard},
  booktitle={MICCAI},
  pages={683--691},
  year={2019},
}

@article{HCchallenge,
    author = {van den Heuvel, Thomas L. A. AND de Bruijn, Dagmar AND de Korte, Chris L. AND Ginneken, Bram van},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Automated measurement of fetal head circumference using 2D ultrasound images},
    year = {2018},
    month = {08},
    volume = {13},
    url = {https://doi.org/10.1371/journal.pone.0200412},
    pages = {1-20},
    number = {8}
}

@article{hcdataset,
    author = {van den Heuvel, Thomas L. A. AND de Bruijn, Dagmar AND de Korte, Chris L. AND Ginneken, Bram van},
    year = {2018},
    journal = {Zenodo},
    title = {Automated measurement of fetal head circumference using 2D ultrasound images [Data set]},
    url = { http://doi.org/10.5281/zenodo.1322001},

}

@inproceedings{2015unet,
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  booktitle={MICCAI},
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  year={2015},
  organization={Springer}
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@inproceedings{2019fetalseg,
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  year={2019},
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@article{li2017randomf,
  title={Automatic fetal head circumference measurement in ultrasound using random forest and fast ellipse fitting},
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  publisher={IEEE}
}

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  publisher={IEEE}
}

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@inproceedings{headpose20163d,
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@inproceedings{2014bodypose,
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@article{kim2019automatic,
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