@book{Lamport:Book:1989,
 author = {Lamport, Leslie},
 title = {Latex: A Document Preparation System},
 year = {1986},
 isbn = {0-201-15790-X},
 publisher = {Addison-Wesley Longman Publishing Co., Inc.},
 address = {Boston, MA, USA},
}

@misc{Hinton:arXiv:2015:Distilling,
 title={Distilling the knowledge in a neural network},
 author={Hinton, Geoffrey and Vinyals, Oriol and Dean, Jeff},
 OPTeprinttype={arXiv},
 OPTeprint={1503.02531},
 howpublished={Eprint \href{http://arxiv.org/abs/1503.02531}{arXiv:1503.02531}},
 OPTurl={http://arxiv.org/abs/1503.02531},
 year=2015
}

@article{glocker2023algorithmic,
  title={Algorithmic encoding of protected characteristics in chest X-ray disease detection models},
  author={Glocker, Ben and Jones, Charles and Bernhardt, M{\'e}lanie and Winzeck, Stefan},
  journal={EBioMedicine},
  volume={89},
  year={2023},
  publisher={Elsevier}
}

@article{gichoya2022ai,
  title={AI recognition of patient race in medical imaging: a modelling study},
  author={Gichoya, Judy Wawira and Banerjee, Imon and Bhimireddy, Ananth Reddy and Burns, John L and Celi, Leo Anthony and Chen, Li-Ching and Correa, Ramon and Dullerud, Natalie and Ghassemi, Marzyeh and Huang, Shih-Cheng and others},
  journal={The Lancet Digital Health},
  volume={4},
  number={6},
  pages={e406--e414},
  year={2022},
  publisher={Elsevier}
}

@inproceedings{pegios2023leveraging,
  title={Leveraging shape and spatial information for spontaneous preterm birth prediction},
  author={Pegios, Paraskevas and Sejer, Emilie Pi Fogtmann and Lin, Manxi and Bashir, Zahra and Svendsen, Morten Bo S{\o}ndergaard and Nielsen, Mads and Petersen, Eike and Christensen, Anders Nymark and Tolsgaard, Martin and Feragen, Aasa},
  booktitle={International Workshop on Advances in Simplifying Medical Ultrasound},
  pages={57--67},
  year={2023},
  organization={Springer}
}

@article{baumgartner2017sononet,
  title={SonoNet: real-time detection and localisation of fetal standard scan planes in freehand ultrasound},
  author={Baumgartner, Christian F and Kamnitsas, Konstantinos and Matthew, Jacqueline and Fletcher, Tara P and Smith, Sandra and Koch, Lisa M and Kainz, Bernhard and Rueckert, Daniel},
  journal={IEEE transactions on medical imaging},
  volume={36},
  number={11},
  pages={2204--2215},
  year={2017},
  publisher={IEEE}
}

@article{geirhos2020shortcut,
  title={Shortcut learning in deep neural networks},
  author={Geirhos, Robert and Jacobsen, J{\"o}rn-Henrik and Michaelis, Claudio and Zemel, Richard and Brendel, Wieland and Bethge, Matthias and Wichmann, Felix A},
  journal={Nature Machine Intelligence},
  volume={2},
  number={11},
  pages={665--673},
  year={2020},
  publisher={Nature Publishing Group UK London}
}

@article{obermeyer2019dissecting,
  title={Dissecting racial bias in an algorithm used to manage the health of populations},
  author={Obermeyer, Ziad and Powers, Brian and Vogeli, Christine and Mullainathan, Sendhil},
  journal={Science},
  volume={366},
  number={6464},
  pages={447--453},
  year={2019},
  publisher={American Association for the Advancement of Science}
}

@article{de2018clinically,
  title={Clinically applicable deep learning for diagnosis and referral in retinal disease},
  author={De Fauw, Jeffrey and Ledsam, Joseph R and Romera-Paredes, Bernardino and Nikolov, Stanislav and Tomasev, Nenad and Blackwell, Sam and Askham, Harry and Glorot, Xavier and O’Donoghue, Brendan and Visentin, Daniel and others},
  journal={Nature medicine},
  volume={24},
  number={9},
  pages={1342--1350},
  year={2018},
  publisher={Nature Publishing Group US New York}
}


@article{esteva2017dermatologist,
  title={Dermatologist-level classification of skin cancer with deep neural networks},
  author={Esteva, Andre and Kuprel, Brett and Novoa, Roberto A and Ko, Justin and Swetter, Susan M and Blau, Helen M and Thrun, Sebastian},
  journal={nature},
  volume={542},
  number={7639},
  pages={115--118},
  year={2017},
  publisher={Nature Publishing Group UK London}
}


@inproceedings{jabbour2020deep,
  title={Deep learning applied to chest X-rays: exploiting and preventing shortcuts},
  author={Jabbour, Sarah and Fouhey, David and Kazerooni, Ella and Sjoding, Michael W and Wiens, Jenna},
  booktitle={Machine Learning for Healthcare Conference},
  pages={750--782},
  year={2020},
  organization={PMLR}
}

@inproceedings{neuhaus2023spurious,
  title={Spurious features everywhere-large-scale detection of harmful spurious features in imagenet},
  author={Neuhaus, Yannic and Augustin, Maximilian and Boreiko, Valentyn and Hein, Matthias},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={20235--20246},
  year={2023}
}


@ARTICLE{bengio2013representation,
  author={Bengio, Yoshua and Courville, Aaron and Vincent, Pascal},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={Representation Learning: A Review and New Perspectives}, 
  year={2013},
  volume={35},
  number={8},
  pages={1798-1828},
  keywords={Learning systems;Machine learning;Abstracts;Feature extraction;Manifolds;Neural networks;Speech recognition;Deep learning;representation learning;feature learning;unsupervised learning;Boltzmann machine;autoencoder;neural nets},
  doi={10.1109/TPAMI.2013.50}}

@article{sendra2023generalisability,
  title={Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries},
  author={Sendra-Balcells, Carla and Campello, V{\'\i}ctor M and Torrents-Barrena, Jordina and Ahmed, Yahya Ali and Elattar, Mustafa and Ohene-Botwe, Benard and Nyangulu, Pempho and Stones, William and Ammar, Mohammed and Benamer, Lamya Nawal and others},
  journal={Scientific reports},
  volume={13},
  number={1},
  pages={2728},
  year={2023},
  publisher={Nature Publishing Group UK London}
}


@article{sejer2025combined,
  title={The combined use of cervical ultrasound and deep learning improves the detection of patients at risk for spontaneous preterm delivery},
  author={Sejer, Emilie PF and Pegios, Paraskevas and Lin, Manxi and Bashir, Zahra and Wulff, Camilla B and Christensen, Anders N and Nielsen, Mads and Feragen, Aasa and Tolsgaard, Martin G},
  journal={American Journal of Obstetrics and Gynecology},
  year={2025},
  publisher={Elsevier}
}

@inproceedings{fournel2025cervix,
  title={The Cervix in Context: Bias Assessment in Preterm Birth Prediction},
  author={Fournel, Joris and Pegios, Paraskevas and Sejer, Emilie Pi Fogtmann and Tolsgaard, Martin and Feragen, Aasa},
  booktitle={MICCAI Workshop on Fairness of AI in Medical Imaging},
  pages={43--52},
  year={2025},
  organization={Springer}
}


@article{mikolaj2023removing,
  title={Removing confounding information from fetal ultrasound images},
  author={Mikolaj, Kamil and Lin, Manxi and Bashir, Zahra and Svendsen, Morten Bo S{\o}ndergaard and Tolsgaard, Martin and Nymark, Anders and Feragen, Aasa},
  journal={arXiv preprint arXiv:2303.13918},
  year={2023}
}

@inproceedings{lin2023dtu,
  title={Dtu-net: Learning topological similarity for curvilinear structure segmentation},
  author={Lin, Manxi and Zepf, Kilian and Christensen, Anders Nymark and Bashir, Zahra and Svendsen, Morten Bo S{\o}ndergaard and Tolsgaard, Martin and Feragen, Aasa},
  booktitle={International Conference on Information Processing in Medical Imaging},
  pages={654--666},
  year={2023},
  organization={Springer}
}

@inproceedings{pegios2025diffusion,
  title={Diffusion-based iterative counterfactual explanations for fetal ultrasound image quality assessment},
  author={Pegios, Paraskevas and Lin, Manxi and Weng, Nina and Svendsen, Morten Bo S{\o}ndergaard and Bashir, Zahra and Bigdeli, Siavash and Christensen, Anders Nymark and Tolsgaard, Martin and Feragen, Aasa},
  booktitle={International Workshop on Advances in Simplifying Medical Ultrasound},
  pages={174--184},
  year={2025},
  organization={Springer}
}


@inproceedings{lin2024shortcut,
  title={Shortcut learning in medical image segmentation},
  author={Lin, Manxi and Weng, Nina and Mikolaj, Kamil and Bashir, Zahra and Svendsen, Morten BS and Tolsgaard, Martin G and Christensen, Anders N and Feragen, Aasa},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={623--633},
  year={2024},
  organization={Springer}
}


@inproceedings{lin2024learning,
  title={Learning semantic image quality for fetal ultrasound from noisy ranking annotation},
  author={Lin, Manxi and Ambsdorf, Jakob and Sejer, Emilie Pi Fogtmann and Bashir, Zahra and Wong, Chun Kit and Pegios, Paraskevas and Raheli, Alberto and Svendsen, Morten Bo S{\o}ndergaard and Nielsen, Mads and Tolsgaard, Martin Gr{\o}nneb{\ae}k and others},
  booktitle={2024 IEEE International Symposium on Biomedical Imaging (ISBI)},
  pages={1--5},
  year={2024},
  organization={IEEE}
}


@inproceedings{wisniewski2025determining,
  title={Determining Fetal Orientations From Blind Sweep Ultrasound Video},
  author={Wi{\'s}niewski, Jakub Maciej and Christensen, Anders Nymark and Ngo, Mary Le and Tolsgaard, Martin Gr{\o}nneb{\ae}k and Wong, Chun Kit},
  booktitle={Scandinavian Conference on Image Analysis},
  pages={254--263},
  year={2025},
  organization={Springer}
}


@inproceedings{weng2024fast,
  title={Fast diffusion-based counterfactuals for shortcut removal and generation},
  author={Weng, Nina and Pegios, Paraskevas and Petersen, Eike and Feragen, Aasa and Bigdeli, Siavash},
  booktitle={European Conference on Computer Vision},
  pages={338--357},
  year={2024},
  organization={Springer}
}


@inproceedings{fathi2024decodex,
  title={DeCoDEx: Confounder Detector Guidance for Improved Diffusion-based Counterfactual Explanations},
  author={Fathi, Nima and Kumar, Amar and Nichyporuk, Brennan and Havaei, Mohammad and Arbel, Tal},
  booktitle={Medical Imaging with Deep Learning},
  pages={439--451},
  year={2024},
  organization={PMLR}
}



@inproceedings{kumar2023debiasing,
  title={Debiasing counterfactuals in the presence of spurious correlations},
  author={Kumar, Amar and Fathi, Nima and Mehta, Raghav and Nichyporuk, Brennan and Falet, Jean-Pierre R and Tsaftaris, Sotirios and Arbel, Tal},
  booktitle={Workshop on Clinical Image-Based Procedures},
  pages={276--286},
  year={2023},
  organization={Springer}
}


@article{bender2026visual,
  title={Visual Disentangled Diffusion Autoencoders: Scalable Counterfactual Generation for Foundation Models},
  author={Bender, Sidney and Morik, Marco},
  journal={arXiv preprint arXiv:2601.21851},
  year={2026}
}

@inproceedings{olsen2024unsupervised,
  title={Unsupervised detection of fetal brain anomalies using denoising diffusion models},
  author={Olsen, Markus Ditlev Sj{\o}gren and Ambsdorf, Jakob and Lin, Manxi and Taks{\o}e-Vester, Caroline and Svendsen, Morten Bo S{\o}ndergaard and Christensen, Anders Nymark and Nielsen, Mads and Tolsgaard, Martin Gr{\o}nneb{\ae}k and Feragen, Aasa and Pegios, Paraskevas},
  booktitle={International Workshop on Advances in Simplifying Medical Ultrasound},
  pages={209--219},
  year={2024},
  organization={Springer}
}

@inproceedings{wong2025influence,
  title={Influence of Classification Task and Distribution Shift Type on OOD Detection in Fetal Ultrasound},
  author={Wong, Chun Kit and Christensen, Anders N and Bercea, Cosmin I and Schnabel, Julia A and Tolsgaard, Martin G and Feragen, Aasa},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={293--303},
  year={2025},
  organization={Springer}
}


@article{bender2025mitigating,
  title={Mitigating clever hans strategies in image classifiers through generating counterexamples},
  author={Bender, Sidney and Delzer, Ole and Herrmann, Jan and Marxfeld, Heike Antje and M{\"u}ller, Klaus-Robert and Montavon, Gr{\'e}goire},
  journal={arXiv preprint arXiv:2510.17524},
  year={2025}
}


@inproceedings{wlodarczyk2020spontaneous,
  title={Spontaneous preterm birth prediction using convolutional neural networks},
  author={W{\l}odarczyk, Tomasz and P{\l}otka, Szymon and Rokita, Przemys{\l}aw and Sochacki-W{\'o}jcicka, Nicole and W{\'o}jcicki, Jakub and Lipa, Micha{\l} and Trzci{\'n}ski, Tomasz},
  booktitle={International Workshop on Advances in Simplifying Medical Ultrasound},
  pages={274--283},
  year={2020},
  organization={Springer}
}


@inproceedings{wlodarczyk2019estimation,
  title={Estimation of preterm birth markers with U-Net segmentation network},
  author={W{\l}odarczyk, Tomasz and P{\l}otka, Szymon and Trzci{\'n}ski, Tomasz and Rokita, Przemys{\l}aw and Sochacki-W{\'o}jcicka, Nicole and Lipa, Micha{\l} and W{\'o}jcicki, Jakub},
  booktitle={International Workshop on Preterm, Perinatal and Paediatric Image Analysis},
  pages={95--103},
  year={2019},
  organization={Springer}
}

@article{stanley2025and,
  title={Where, why, and how is bias learned in medical image analysis models? a study of bias encoding within convolutional networks using synthetic data},
  author={Stanley, Emma AM and Souza, Raissa and Wilms, Matthias and Forkert, Nils D},
  journal={EBioMedicine},
  volume={111},
  year={2025},
  publisher={Elsevier}
}