@article{ojala2002multiresolution,
  title={Multiresolution gray-scale and rotation invariant texture classification with local binary patterns},
  author={Ojala, Timo and Pietikainen, Matti and Maenpaa, Topi},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume={24},
  number={7},
  pages={971--987},
  year={2002},
  publisher={IEEE}
}

@article{fetit2015three,
  title={Three-dimensional textural features of conventional MRI improve diagnostic classification of childhood brain tumours},
  author={Fetit, Ahmed E. and Novak, Jan and Peet, Andrew C. and Arvanitis, Theodoros N.},
  journal={NMR in Biomedicine},
  volume={28},
  number={9},
  pages={1174--1184},
  year={2015},
  publisher={Wiley Online Library}
}

@article{orphanidou2014texture,
  title={Texture analysis of {T1-and T2-weighted MR} images and use of probabilistic neural network to discriminate posterior fossa tumours in children},
  author={Orphanidou-Vlachou, Eleni and Vlachos, Nikolaos and Davies, Nigel P. and Arvanitis, Theodoros N. and Grundy, Richard G. and Peet, Andrew C.},
  journal={NMR in Biomedicine},
  volume={27},
  number={6},
  pages={632--639},
  year={2014},
  publisher={Wiley Online Library}
}

@article{bastiani2019automated,
  title={Automated processing pipeline for neonatal diffusion {MRI in the developing Human Connectome Project}},
  author={Bastiani, Matteo and Andersson, Jesper L.R. and Cordero-Grande, Lucilio and Murgasova, Maria and Hutter, Jana and Price, Anthony N. and Makropoulos, Antonios and Fitzgibbon, Sean P. and Hughes, Emer and Rueckert, Daniel and others},
  journal={NeuroImage},
  volume={185},
  pages={750--763},
  year={2019},
  publisher={Elsevier}
}

@misc{
lin2019local,
title={Local Binary Pattern Networks for Character Recognition},
author={Jeng-Hau Lin and Yunfan Yang and Rajesh K. Gupta and Zhuowen Tu},
year={2019},
url={https://openreview.net/forum?id=rJxcHnRqYQ},
}

@inproceedings{zhang2017face,
  title={A face recognition method based on LBP feature for CNN},
  author={Zhang, Hongshuai and Qu, Zhiyi and Yuan, Liping and Li, Gang},
  booktitle={2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)},
  pages={544--547},
  year={2017},
  organization={IEEE}
}

@ARTICLE{Pietikainen:2010,
    AUTHOR = {Pietikäinen, Matti },
    TITLE   = {{L}ocal {B}inary {P}atterns},
    YEAR    = {2010},
    JOURNAL = {Scholarpedia},
    VOLUME  = {5},
    NUMBER  = {3},
    PAGES   = {9775},
    DOI     = {10.4249/scholarpedia.9775},
    NOTE    = {revision \#188481}
}

@article{van2014scikit,
  title={scikit-image: image processing in Python},
  author={Van der Walt, Stefan and Sch{\"o}nberger, Johannes L. and Nunez-Iglesias, Juan and Boulogne, Fran{\c{c}}ois and Warner, Joshua D. and Yager, Neil and Gouillart, Emmanuelle and Yu, Tony},
  journal={PeerJ},
  volume={2},
  pages={e453},
  year={2014},
  publisher={PeerJ Inc.}
}

@article{anwer2018binary,
  title={Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification},
  author={Anwer, Rao Muhammad and Khan, Fahad Shahbaz and van de Weijer, Joost and Molinier, Matthieu and Laaksonen, Jorma},
  journal={ISPRS Journal of Photogrammetry and Remote Sensing},
  volume={138},
  pages={74--85},
  year={2018},
  publisher={Elsevier}
}

@inproceedings{
geirhos2018imagenettrained,
title={ImageNet-trained {CNN}s are biased towards texture; increasing shape bias improves accuracy and robustness.},
author={Robert Geirhos and Patricia Rubisch and Claudio Michaelis and Matthias Bethge and Felix A. Wichmann and Wieland Brendel},
booktitle={International Conference on Learning Representations},
year={2019},
url={https://openreview.net/forum?id=Bygh9j09KX},
}

@inproceedings{pawlowski:MIDLAbstract2019a,
title={Is Texture Predictive for Age and Sex in Brain {MRI}?},
author={Nick Pawlowski and Ben Glocker},
booktitle={International Conference on Medical Imaging with Deep Learning -- Extended Abstract Track},
address={London, United Kingdom},
year={2019},
month={08--10 Jul},
url={https://openreview.net/forum?id=BJxgXfab94},
abstract={Deep learning builds the foundation for many medical image analysis tasks where neural networks are often designed to have a large receptive field to incorporate long spatial dependencies. Recent work has shown that large receptive fields are not always necessary for computer vision tasks on natural images. We explore whether this translates to certain medical imaging tasks such as age and sex prediction from a T1-weighted brain MRI scans.},
}

@inproceedings{ritter2017cognitive,
  title={Cognitive psychology for deep neural networks: A shape bias case study},
  author={Ritter, Samuel and Barrett, David G.T. and Santoro, Adam and Botvinick, Matt M.},
  booktitle={Proceedings of the 34th International Conference on Machine Learning-Volume 70},
  pages={2940--2949},
  year={2017},
  organization={JMLR. org}
}

@inproceedings{van2019disentangled,
  title={Are Disentangled Representations Helpful for Abstract Visual Reasoning?},
  author={van Steenkiste, Sjoerd and Locatello, Francesco and Schmidhuber, J{\"u}rgen and Bachem, Olivier},
  booktitle={Advances in Neural Information Processing Systems},
  pages={14222--14235},
  year={2019}
}
@article{lindeberg1998feature,
  title={Feature detection with automatic scale selection},
  author={Lindeberg, Tony},
  journal={International Journal of Computer Vision},
  volume={30},
  number={2},
  pages={79--116},
  year={1998},
  publisher={Springer}
}

@article{lowe2004distinctive,
  title={Distinctive image features from scale-invariant keypoints},
  author={Lowe, David G.},
  journal={International Journal of Computer Vision},
  volume={60},
  number={2},
  pages={91--110},
  year={2004},
  publisher={Springer}
}
@inproceedings{toews2012feature,
  title={A feature-based developmental model of the infant brain in structural MRI},
  author={Toews, Matthew and Wells, William M. and Z{\"o}llei, Lilla},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={204--211},
  year={2012},
  organization={Springer}
}
@article{lecun2015deep,
  title={Deep learning},
  author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
  journal={Nature},
  volume={521},
  number={7553},
  pages={436--444},
  year={2015},
  publisher={Nature Publishing Group}
}

@inproceedings{zeiler2014visualizing,
  title={Visualizing and understanding convolutional networks},
  author={Zeiler, Matthew D. and Fergus, Rob},
  booktitle={European Conference on Computer Vision},
  pages={818--833},
  year={2014},
  organization={Springer}
}

@article{gutierrez2014metrics,
  title={Metrics and textural features of {MRI} diffusion to improve classification of pediatric posterior fossa tumors},
  author={Gutierrez, D. Rodriguez and Awwad, A. and Meijer, Lisethe and Manita, M. and Jaspan, T and Dineen, Robert A. and Grundy, Richard G. and Auer, Dorothee P},
  journal={American Journal of Neuroradiology},
  volume={35},
  number={5},
  pages={1009--1015},
  year={2014},
  publisher={Am Soc Neuroradiology}
}

@article{chauvin2020neuroimage,
  title={Neuroimage signature from salient keypoints is highly specific to individuals and shared by close relatives},
  author={Chauvin, Laurent and Kumar, Kuldeep and Wachinger, Christian and Vangel, Marc and de Guise, Jacques and Desrosiers, Christian and Wells, William and Toews, Matthew and Alzheimer’s Disease Neuroimaging Initiative and others},
  journal={NeuroImage},
  volume={204},
  pages={116208},
  year={2020},
  publisher={Elsevier}
}

@article{ILSVRC15,
Author = {Olga Russakovsky and Jia Deng and Hao Su and Jonathan Krause and Sanjeev Satheesh and Sean Ma and Zhiheng Huang and Andrej Karpathy and Aditya Khosla and Michael Bernstein and Alexander C. Berg and Li Fei-Fei},
Title = {{ImageNet Large Scale Visual Recognition Challenge}},
Year = {2015},
journal   = {International Journal of Computer Vision (IJCV)},
doi = {10.1007/s11263-015-0816-y},
volume={115},
number={3},
pages={211-252}
}

@inproceedings{
 brendel2018approximating,
 title={Approximating {CNN}s with Bag-of-local-Features models works surprisingly well on ImageNet},
 author={Wieland Brendel and Matthias Bethge},
 booktitle={International Conference on Learning Representations},
 year={2019},
 url={https://openreview.net/forum?id=SkfMWhAqYQ},
}

@article{Kamnitsas2017EfficientSegmentation,
    title = {{Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation}},
    year = {2017},
    journal = {Medical Image Analysis},
    author = {Kamnitsas, Konstantinos and Ledig, Christian and Newcombe, Virginia F.J. and Simpson, Joanna P. and Kane, Andrew D. and Menon, David K. and Rueckert, Daniel and Glocker, Ben},
    month = {2},
    pages = {61--78},
    volume = {36},
    publisher = {Elsevier},
    url = {https://www.sciencedirect.com/science/article/pii/S1361841516301839},
    doi = {10.1016/J.MEDIA.2016.10.004},
    issn = {1361-8415}
}

@article{van2013wu,
  title={The WU-Minn human connectome project: an overview},
  author={Van Essen, David C and Smith, Stephen M and Barch, Deanna M and Behrens, Timothy EJ and Yacoub, Essa and Ugurbil, Kamil and Wu-Minn HCP Consortium and others},
  journal={Neuroimage},
  volume={80},
  pages={62--79},
  year={2013},
  publisher={Elsevier}
}

@article{makropoulos2018review,
  title={A review on automatic fetal and neonatal brain MRI segmentation},
  author={Makropoulos, Antonios and Counsell, Serena J and Rueckert, Daniel},
  journal={NeuroImage},
  volume={170},
  pages={231--248},
  year={2018},
  publisher={Elsevier}
}

@article{Makropoulos2018TheReconstruction,
    title = {{The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction}},
    year = {2018},
    journal = {NeuroImage},
    author = {Makropoulos, Antonios and Robinson, Emma C. and Schuh, Andreas and Wright, Robert and Fitzgibbon, Sean and Bozek, Jelena and Counsell, Serena J. and Steinweg, Johannes and Vecchiato, Katy and Passerat-Palmbach, Jonathan and Lenz, Gregor and Mortari, Filippo and Tenev, Tencho and Duff, Eugene P. and Bastiani, Matteo and Cordero-Grande, Lucilio and Hughes, Emer and Tusor, Nora and Tournier, Jacques-Donald and Hutter, Jana and Price, Anthony N. and Teixeira, Rui Pedro A.G. and Murgasova, Maria and Victor, Suresh and Kelly, Christopher and Rutherford, Mary A. and Smith, Stephen M. and Edwards, A. David and Hajnal, Joseph V. and Jenkinson, Mark and Rueckert, Daniel},
    month = {6},
    pages = {88--112},
    volume = {173},
    url = {http://www.ncbi.nlm.nih.gov/pubmed/29409960 https://linkinghub.elsevier.com/retrieve/pii/S1053811918300545},
    doi = {10.1016/j.neuroimage.2018.01.054},
    issn = {10538119},
    pmid = {29409960},
    keywords = {Cortical surface reconstruction, Developing human connectome project, Neonatal MRI, Pipeline, Segmentation, dHCP}
}

@article{Makropoulos2014AutomaticBrain,
    title = {{Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain}},
    year = {2014},
    journal = {IEEE Transactions on Medical Imaging},
    author = {Makropoulos, Antonios and Gousias, Ioannis S. and Ledig, Christian and Aljabar, Paul and Serag, Ahmed and Hajnal, Joseph V. and Edwards, A. David and Counsell, Serena J. and Rueckert, Daniel},
    number = {9},
    month = {9},
    pages = {1818--1831},
    volume = {33},
    url = {http://ieeexplore.ieee.org/document/6810848/},
    doi = {10.1109/TMI.2014.2322280},
    issn = {0278-0062}
}

@article{serag2013spatio,
  title={Spatio-temporal modeling and analysis of brain development},
  author={Serag, Ahmed},
  year={2013},
  publisher={Imperial College London}
}

@inproceedings{habas2008atlas,
  title={Atlas-based segmentation of the germinal matrix from in utero clinical MRI of the fetal brain},
  author={Habas, Piotr A and Kim, Kio and Rousseau, Francois and Glenn, Orit A and Barkovich, A James and Studholme, Colin},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={351--358},
  year={2008},
  organization={Springer}
}
