%intro 
@article{siegel2023cancer,
  title={Cancer statistics, 2023.},
  author={Siegel, Rebecca L and Miller, Kimberly D and Wagle, Nikita Sandeep and Jemal, Ahmedin},
  journal={{CA}: a cancer journal for clinicians},
  volume={73},
  number={1},
  year={2023}
}
@article{nlst,
  title={Reduced lung-cancer mortality with low-dose computed tomographic screening},
  author={National Lung Screening Trial Research Team},
  journal={New England Journal of Medicine},
  volume={365},
  number={5},
  pages={395--409},
  year={2011},
  publisher={Mass Medical Soc}
}

@article{potter2022association,
  title={Association of computed tomography screening with lung cancer stage shift and survival in the United States: quasi-experimental study},
  author={Potter, Alexandra L and Rosenstein, Allison L and Kiang, Mathew V and Shah, Shivani A and Gaissert, Henning A and Chang, David C and Fintelmann, Florian J and Yang, Chi-Fu Jeffrey},
  journal={Bmj},
  volume={376},
  year={2022},
  publisher={British Medical Journal Publishing Group}
}

@inproceedings{dlstm,
  title={Distanced {LSTM}: time-distanced gates in long short-term memory models for lung cancer detection},
  author={Gao, Riqiang and Huo, Yuankai and Bao, Shunxing and Tang, Yucheng and Antic, Sanja L and Epstein, Emily S and Balar, Aneri B and Deppen, Steve and Paulson, Alexis B and Sandler, Kim L and others},
  booktitle={International Workshop on Machine Learning in Medical Imaging},
  pages={310--318},
  year={2019},
  organization={Springer}
}

@inproceedings{litransformer,
  title={Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography},
  author={Li, Thomas Z and Xu, Kaiwen and Gao, Riqiang and Tang, Yucheng and Lasko, Thomas A and Maldonado, Fabien and Sandler, Kim L and Landman, Bennett A},
  booktitle={Medical Imaging 2023: Image Processing},
  volume={12464},
  pages={229--238},
  year={2023},
  organization={SPIE}
}

@article{endtoend,
  title={End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography},
  author={Ardila, Diego and Kiraly, Atilla P and Bharadwaj, Sujeeth and Choi, Bokyung and Reicher, Joshua J and Peng, Lily and Tse, Daniel and Etemadi, Mozziyar and Ye, Wenxing and Corrado, Greg and others},
  journal={Nature medicine},
  volume={25},
  number={6},
  pages={954--961},
  year={2019},
  publisher={Nature Publishing Group US New York}
}


@article{monocle,
  title={The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells},
  author={Trapnell, Cole and Cacchiarelli, Davide and Grimsby, Jonna and Pokharel, Prapti and Li, Shuqiang and Morse, Michael and Lennon, Niall J and Livak, Kenneth J and Mikkelsen, Tarjei S and Rinn, John L},
  journal={Nature biotechnology},
  volume={32},
  number={4},
  pages={381--386},
  year={2014},
  publisher={Nature Publishing Group US New York}
}

@article{slingshot,
  title={Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics},
  author={Street, Kelly and Risso, Davide and Fletcher, Russell B and Das, Diya and Ngai, John and Yosef, Nir and Purdom, Elizabeth and Dudoit, Sandrine},
  journal={BMC genomics},
  volume={19},
  number={1},
  pages={477},
  year={2018},
  publisher={Springer}
}

@article{scvi,
  title={Deep generative modeling for single-cell transcriptomics},
  author={Lopez, Romain and Regier, Jeffrey and Cole, Michael B and Jordan, Michael I and Yosef, Nir},
  journal={Nature methods},
  volume={15},
  number={12},
  pages={1053--1058},
  year={2018},
  publisher={Nature Publishing Group US New York}
}

@article{cannoodt2016computational,
  title={Computational methods for trajectory inference from single-cell transcriptomics},
  author={Cannoodt, Robrecht and Saelens, Wouter and Saeys, Yvan},
  journal={European journal of immunology},
  volume={46},
  number={11},
  pages={2496--2506},
  year={2016},
  publisher={Wiley Online Library}
}

@inproceedings{he2024multi,
  title={Multi-modal imaging-based pseudotime analysis of {A}lzheimer progression},
  author={He, Bing and Zhang, Shu and Risacher, Shannon L and Saykin, Andrew J and Yan, Jingwen},
  booktitle={Biocomputing 2025: Proceedings of the Pacific Symposium},
  pages={664--674},
  year={2024},
  organization={World Scientific}
}

@article{glazman2025dynamic,
  title={Dynamic causal discovery in {A}lzheimer's disease through latent pseudotime modelling},
  author={Glazman, Natalia and Mangal, Jyoti and Borges, Pedro and Ourselin, Sebastien and Cardoso, M Jorge},
  journal={arXiv preprint arXiv:2511.04619},
  year={2025}
}

@article{lee2024prognostic,
  title={Prognostic value of pseudotime from texture parameters of {FDG PET/CT} in locally advanced rectal cancer with neoadjuvant concurrent chemoradiotherapy},
  author={Lee, Hyunjong and Hyun, Seung Hyup and Cho, Yong Beom and Kim, Hee Cheol and Park, Hee Chul and Park, Young Suk and Choi, Joon Young},
  journal={Scientific Reports},
  volume={14},
  number={1},
  pages={31437},
  year={2024},
  publisher={Nature Publishing Group UK London}
}


% preprocessing
@inproceedings{maskedseg,
  title={Enhancing lung segmentation algorithms to ensure inclusion of juxtapleural nodules},
  author={Zhuang, Luoting and Tabatabaei, Seyed Mohammad Hossein and Prosper, Ashley E and Hsu, William},
  booktitle={2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)},
  pages={1--5},
  year={2025},
  organization={IEEE}
}

@article{liao,
  title={Evaluate the malignancy of pulmonary nodules using the 3-d deep leaky noisy-or network},
  author={Liao, Fangzhou and Liang, Ming and Li, Zhe and Hu, Xiaolin and Song, Sen},
  journal={IEEE transactions on neural networks and learning systems},
  volume={30},
  number={11},
  pages={3484--3495},
  year={2019},
  publisher={IEEE}
}

@article{monai,
  title={Monai: An open-source framework for deep learning in healthcare},
  author={Cardoso, M Jorge and Li, Wenqi and Brown, Richard and Ma, Nic and Kerfoot, Eric and Wang, Yiheng and Murrey, Benjamin and Myronenko, Andriy and Zhao, Can and Yang, Dong and others},
  journal={arXiv preprint arXiv:2211.02701},
  year={2022}
}

@inproceedings{corrfields,
  title={Estimating large lung motion in {COPD} patients by symmetric regularised correspondence fields},
  author={Heinrich, Mattias P and Handels, Heinz and Simpson, Ivor JA},
  booktitle={International conference on medical image computing and computer-assisted intervention},
  pages={338--345},
  year={2015},
  organization={Springer}
}

@article{sybil,
  title={Sybil: a validated deep learning model to predict future lung cancer risk from a single low-dose chest computed tomography},
  author={Mikhael, Peter G and Wohlwend, Jeremy and Yala, Adam and Karstens, Ludvig and Xiang, Justin and Takigami, Angelo K and Bourgouin, Patrick P and Chan, PuiYee and Mrah, Sofiane and Amayri, Wael and others},
  journal={Journal of Clinical Oncology},
  volume={41},
  number={12},
  pages={2191--2200},
  year={2023},
  publisher={Wolters Kluwer Health}
}

@misc{luna25,
  author       = {Peeters, D. and Obreja, B. and Antonissen, N. and Jacobs, C.},
  title        = {The {LUNA25} Challenge: Public Training and Development Set - Annotation Data},
  howpublished = {Zenodo},
  year         = {2025},
  month        = feb,
  doi          = {10.5281/zenodo.14673658}
}

@article{fmcib,
  title={Foundation model for cancer imaging biomarkers},
  author={Pai, Suraj and Bontempi, Dennis and Hadzic, Ibrahim and Prudente, Vasco and Soka{\v{c}}, Mateo and Chaunzwa, Tafadzwa L and Bernatz, Simon and Hosny, Ahmed and Mak, Raymond H and Birkbak, Nicolai J and others},
  journal={Nature machine intelligence},
  volume={6},
  number={3},
  pages={354--367},
  year={2024},
  publisher={Nature Publishing Group UK London}
}

@article{sctour,
  title={sc{T}our: a deep learning architecture for robust inference and accurate prediction of cellular dynamics},
  author={Li, Qian},
  journal={Genome Biology},
  volume={24},
  number={1},
  pages={149},
  year={2023},
  publisher={Springer}
}

@article{diffusion,
  title={Diffusion pseudotime robustly reconstructs lineage branching},
  author={Haghverdi, Laleh and B{\"u}ttner, Maren and Wolf, F Alexander and Buettner, Florian and Theis, Fabian J},
  journal={Nature methods},
  volume={13},
  number={10},
  pages={845--848},
  year={2016},
  publisher={Nature Publishing Group US New York}
}

@article{paga,
  title={{PAGA}: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells},
  author={Wolf, F Alexander and Hamey, Fiona K and Plass, Mireya and Solana, Jordi and Dahlin, Joakim S and G{\"o}ttgens, Berthold and Rajewsky, Nikolaus and Simon, Lukas and Theis, Fabian J},
  journal={Genome biology},
  volume={20},
  number={1},
  pages={59},
  year={2019},
  publisher={Springer}
}

@article{leiden,
  title={From {L}ouvain to {L}eiden: guaranteeing well-connected communities},
  author={Traag, Vincent A and Waltman, Ludo and Van Eck, Nees Jan},
  journal={Scientific reports},
  volume={9},
  number={1},
  pages={1--12},
  year={2019},
  publisher={Nature Publishing Group}
}

@article{dlcs,
  title={The Duke Lung Cancer Screening ({DLCS}) dataset: a reference dataset of annotated low-dose screening thoracic {CT}},
  author={Wang, Avivah J and Tushar, Fakrul Islam and Harowicz, Michael R and Tong, Betty C and Lafata, Kyle J and Tailor, Tina D and Lo, Joseph Y},
  journal={Radiology: Artificial Intelligence},
  volume={7},
  number={4},
  pages={e240248},
  year={2025},
  publisher={Radiological Society of North America}
}

@article{scanpy,
  title={{SCANPY}: large-scale single-cell gene expression data analysis},
  author={Wolf, F Alexander and Angerer, Philipp and Theis, Fabian J},
  journal={Genome biology},
  volume={19},
  number={1},
  pages={15},
  year={2018},
  publisher={Springer}
}

@article{qiu2025quantifying,
  title={Quantifying Early-Stage Lung Adenocarcinoma Progression with a Radiomic Trajectory},
  author={Qiu, Zhen-Bin and Li, Jiaqi and Dou, Shihua and Meng, Qiuchen and Wang, Meng-Min and Li, Hong-Ji and Zhang, Chao and Xie, Hongsheng and Jiang, Ben-Yuan and Lin, Jun-Tao and others},
  journal={npj Digital Medicine},
  volume={8},
  number={1},
  pages={664},
  year={2025},
  publisher={Nature Publishing Group UK London}
}