Back to the list
Congress: ECR25
Poster Number: C-19654
Type: Poster: EPOS Radiologist (scientific)
Authorblock: M. Shiri1, C. Bortolotto2, A. Bruno1, A. Consonni2, D. M. Grasso2, D. Loiacono1, L. Preda2; 1Milan/IT, 2Pavia/IT
Disclosures:
Mahshid Shiri: Nothing to disclose
Chandra Bortolotto: Nothing to disclose
Alessandro Bruno: Nothing to disclose
Alessio Consonni: Nothing to disclose
Daniela Maria Grasso: Nothing to disclose
Daniele Loiacono: Nothing to disclose
Lorenzo Preda: Nothing to disclose
Keywords: Artificial Intelligence, Lung, Thorax, CT, Image manipulation / Reconstruction, Neural networks, Computer Applications-3D, Computer Applications-Virtual imaging, Image verification
References

1. Zechen Zheng, Miao Wang, Chao Fan, Congqian Wang, Xuelei He, and Xiaowei He. Light&fast generative adversarial network for high-fidelity ct image synthesis of liver tumor. Computer Methods and Programs in Biomedicine, page 108252, 2024.

2. Youssef Skandarani, Pierre-Marc Jodoin, and Alain Lalande. Gans for medical image synthesis: An empirical study. Journal of Imaging, 9(3):69, 2023.

3. José Mendes, Tania Pereira, Francisco Silva, Julieta Frade, Joana Morgado, Cláudia Freitas, Eduardo Negrão, Beatriz Flor De Lima, Miguel Correia Da Silva, António J Madureira, et Lung ct image synthesis using gans. Expert Systems with Applications, 215:119350, 2023.

4. Changhee Han, Yoshiro Kitamura, Akira Kudo, Akimichi Ichinose, Leonardo Rundo, Yujiro Furukawa, Kazuki Umemoto, Yuanzhong Li, and Hideki Nakayama. Synthesizing diverse lung nodules wherever massively: 3d multi-conditional gan-based ct image augmentation for object In 2019 International Conference on 3D Vision (3DV), pages 729–737. IEEE, 2019.

5. Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. Generative adversarial nets. Advances in neural information processing systems, 27, 2014.

6. Artur Ferreira, Tania Pereira, Francisco Silva, Ana T Vilares, Miguel C Silva, António Cunha, and Hélder P Oliveira. Synthesizing 3d lung ct scans with generative adversarial In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pages 2033–2036. IEEE, 2022.

7. Li Sun, Junxiang Chen, Yanwu Xu, Mingming Gong, Ke Yu, and Kayhan Hierarchical amortized gan for 3d high resolution medical image synthesis. IEEE journal of biomedical and health informatics, 26(8):3966– 3975, 2022.

8. Yang Lei, Tonghe Wang, Yingzi Liu, Kristin Higgins, Sibo Tian, Tian Liu, Hui Mao, Hyunsuk Shim, Walter J Curran, Hui-Kuo Shu, et al. Mri-based synthetic ct generation using deep convolutional neural network. In Medical Imaging 2019: Image Processing, volume 10949, pages 716–721. SPIE, 2019.

9. Biting Yu, Luping Zhou, Lei Wang, Jurgen Fripp, and Pierrick 3d cgan based cross-modality mr image synthesis for brain tumor segmentation. In 2018 IEEE 15th international symposium on biomedical imaging (ISBI 2018), pages 626–630. IEEE, 2018.

10. Hristina Uzunova, Jan Ehrhardt, Fabian Jacob, Alex Frydrychowicz, and Heinz Handels. Multi-scale gans for memory-efficient generation of high resolution medical images. In Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI 22, pages 112–120. Springer, 2019.

11. Yi Li and Wei Ping. Cancer metastasis detection with neural conditional random field. arXiv preprint arXiv:1806.07064, 2018.

12. Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Improved training of wasserstein gans. Advances in neural information processing systems, 30, 2017.

13. Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, and Ole Autoencoding beyond pixels using a learned similarity metric. In International conference on machine learning, pages 1558–1566. PMLR, 2016.

14. Sungmin Hong, Razvan Marinescu, Adrian V Dalca, Anna K Bonkhoff, Martin Bretzner, Natalia S Rost, and Polina Golland. 3d-stylegan: A style-based generative adversarial network for generative modeling of three- dimensional medical In Deep Generative Models, and Data Augmentation, Labelling, and Imperfections: First Workshop, DGM4MICCAI 2021, and First Workshop, DALI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings 1, pages 24–34. Springer, 2021.

15. Arnaud Arindra Adiyoso Setio, Alberto Traverso, Thomas De Bel, Moira SN Berens, Cas Van Den Bogaard, Piergiorgio Cerello, Hao Chen, Qi Dou, Maria Evelina Fantacci, Bram Geurts, et Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the luna16 challenge. Medical image analysis, 42:1–13, 2017.

16. Samuel G Armato III, Geoffrey McLennan, Luc Bidaut, Michael F McNitt-Gray, Charles R Meyer, Anthony P Reeves, Binsheng Zhao, Denise R Aberle, Claudia I Henschke, Eric A Hoffman, et The lung image database consortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans. Medical physics, 38(2):915–931, 2011.
GALLERY