Recent publications
Article
von Chamier, L, Laine, RF, Jukkala, J, Spahn, C, Krentzel, D, Nehme, E, Lerche, M, Hernández-Pérez, S, Mattila, PK, Karinou, E, Holden, S, Solak, AC, Krull, A, Buchholz, T-O, Jones, ML, Royer, LA, Leterrier, C, Shechtman, Y, Jug, F, Heilemann, M, Jacquemet, G & Henriques, R 2021, 'Democratising deep learning for microscopy with ZeroCostDL4Mic', Nature Communications, vol. 12, no. 1, 2276. https://doi.org/10.1038/s41467-021-22518-0
Laine, RF, Jacquemet, G & Krull, A 2021, 'Imaging in focus: an introduction to denoising bioimages in the era of deep learning', The International Journal of Biochemistry & Cell Biology, vol. 140, 106077. https://doi.org/10.1016/j.biocel.2021.106077
Krull, A, Hirsch, P, Rother, C, Schiffrin, A & Krull, C 2020, 'Artificial-intelligence-driven scanning probe microscopy', Communications Physics, vol. 3, no. 1, pp. 1-8.
Krull, A, Vičar, T, Prakash, M, Lalit, M & Jug, F 2020, 'Probabilistic noise2void: Unsupervised content-aware denoising', Frontiers in Computer Science, vol. 2, pp. 5. https://doi.org/10.3389/fcomp.2020.00005
Buchholz, T-O, Krull, A, Shahidi, R, Pigino, G, Jékely, G & Jug, F 2019, 'Content-aware image restoration for electron microscopy', Methods in Cell Biology, vol. 152, pp. 277-289.
Chapter
Buchholz, T-O, Prakash, M, Schmidt, D, Krull, A & Jug, F 2020, DenoiSeg: Joint Denoising and Segmentation. in DenoiSeg: Joint Denoising and Segmentation. https://doi.org/10.1007/978-3-030-66415-2_21
Goncharova, AS, Honigmann, A, Jug, F & Krull, A 2020, Improving Blind Spot Denoising for Microscopy. in Improving Blind Spot Denoising for Microscopy. https://doi.org/10.1007/978-3-030-66415-2_25
Conference contribution
Krull, A, Basevi, H, Salmon, B, Zeug, A, Müller, F, Tonks, S, Muppala, L & Leonardis, A 2024, Image Denoising and the Generative Accumulation of Photons. in 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE Workshop on Applications of Computer Vision (WACV), IEEE, pp. 1528-1537, 2024 IEEE/CVF Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii, United States, 4/01/24. https://doi.org/10.1109/WACV57701.2024.00155
Cheng, X, Jia, X, Lu, W, Li, Q, Shen, L, Krull, A & Duan, J 2024, WiNet: Wavelet-based Incremental Learning for Efficient Medical Image Registration. in Medical Image Computing and Computer Assisted Intervention – MICCAI 2024: 27th International Conference. Lecture Notes in Computer Science, Springer, 27th International Conference on Medical Image Computing and Computer Assisted Intervention, Marrakesh, Morocco, 6/10/24.
Tonks, S, Hsu, C, Hood, S, Musso, R, Hopely, C, Doan, M, Edwards, E, Krull, A & Styles, I 2023, Evaluating virtual staining for high-throughput screening. in 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)., 10230501, ISBI, IEEE, 20th IEEE International Symposium on Biomedical Imaging, Cartagena , Colombia, 18/04/23. https://doi.org/10.1109/ISBI53787.2023.10230501
Salmon, B & Krull, A 2023, Towards structured noise models for unsupervised denoising. in L Karlinsky, T Michaeli & K Nishino (eds), Computer Vision – ECCV 2022 Workshops: Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IV. 1 edn, Lecture Notes in Computer Science, vol. 13804, Springer, Cham, pp. 379–394. https://doi.org/10.1007/978-3-031-25069-9_25
Prakash, M, Lalit, M, Tomancak, P, Krull, A & Jug, F 2020, Fully unsupervised probabilistic noise2void. in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). pp. 154-158.
Prakash, M, Buchholz, T-O, Lalit, M, Tomancak, P, Jug, F & Krull, A 2020, Leveraging self-supervised denoising for image segmentation. in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). pp. 428-432.
Broaddus, C, Krull, A, Weigert, M, Schmidt, U & Myers, G 2020, Removing structured noise with self-supervised blind-spot networks. in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). pp. 159-163.
Krull, A, Buchholz, T-O & Jug, F 2019, Noise2void-learning denoising from single noisy images. in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2129-2137. <https://openaccess.thecvf.com/content_CVPR_2019/papers/Krull_Noise2Void_-_Learning_Denoising_From_Single_Noisy_Images_CVPR_2019_paper.pdf>
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