Publications of Geert Litjens
2018
Papers in international journals
- P. Bándi, O. Geessink, Q. Manson, M. van Dijk, M. Balkenhol, M. Hermsen, B. Bejnordi, B. Lee, K. Paeng, A. Zhong, Q. Li, F. Zanjani, S. Zinger, K. Fukuta, D. Komura, V. Ovtcharov, S. Cheng, S. Zeng, J. Thagaard, A. Dahl, H. Lin, H. Chen, L. Jacobsson, M. Hedlund, M. Cetin, E. Halici, H. Jackson, R. Chen, F. Both, J. Franke, H. Kusters-Vandevelde, W. Vreuls, P. Bult, B. van Ginneken, J. van der Laak and G. Litjens, "From detection of individual metastases to classification of lymph node status at the patient level: the CAMELYON17 challenge", IEEE Transactions on Medical Imaging, 2018;38(2):550-560.
- D. Tellez, M. Balkenhol, I. Otte-Holler, R. van de Loo, R. Vogels, P. Bult, C. Wauters, W. Vreuls, S. Mol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks", IEEE Transactions on Medical Imaging, 2018;37(9):2126 - 2136.
- G. Litjens, P. Bándi, B. Ehteshami Bejnordi, O. Geessink, M. Balkenhol, P. Bult, A. Halilovic, M. Hermsen, R. van de Loo, R. Vogels, Q. Manson, N. Stathonikos, A. Baidoshvili, P. van Diest, C. Wauters, M. van Dijk and J. van der Laak, "1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset", GigaScience, 2018;7(6):1-8.
- B. Bejnordi, G. Litjens and J. van der Laak, "Machine Learning Compared With Pathologist Assessment-Reply", Journal of the American Medical Association, 2018;319(16):1726.
Preprints
- Z. Li, Z. Hu, J. Xu, T. Tan, H. Chen, Z. Duan, P. Liu, J. Tang, G. Cai, Q. Ouyang, Y. Tang, G. Litjens and Q. Li, "Computer-aided diagnosis of lung carcinoma using deep learning - a pilot study", arXiv:1803.05471, 2018.
Papers in conference proceedings
- D. Tellez, M. Balkenhol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection", Medical Imaging, 2018;10581.
- W. Bulten, C. de Kaa, J. van der Laak and G. Litjens, "Automated segmentation of epithelial tissue in prostatectomy slides using deep learning", Medical Imaging, 2018;10581:105810S.
- Z. Swiderska-Chadaj, H. Pinckaers, M. van Rijthoven, M. Balkenhol, M. Melnikova, O. Geessink, Q. Manson, G. Litjens, J. van der Laak and F. Ciompi, "Convolutional Neural Networks for Lymphocyte detection in Immunohistochemically Stained Whole-Slide Images", Medical Imaging with Deep Learning, 2018.
- W. Bulten and G. Litjens, "Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders", Medical Imaging with Deep Learning, 2018.
- D. Geijs, M. Intezar, J. van der Laak and G. Litjens, "Automatic color unmixing of IHC stained whole slide images", Medical Imaging, 2018;10581.
- T. de Bel, M. Hermsen, J. van der Laak, G. Litjens, B. Smeets and L. Hilbrands, "Automatic segmentation of histopathological slides of renal tissue using deep learning", Medical Imaging 2018: Digital Pathology, 2018.
Abstracts
- H. Pinckaers and G. Litjens, "Training convolutional neural networks with megapixel images", Medical Imaging with Deep Learning, 2018.
Other publications
- T. de Bel, M. Hermsen, G. Litjens and J. van der Laak, "Structure Instance Segmentation in Renal Tissue: A Case Study on Tubular Immune Cell Detection", Computational Pathology and Ophthalmic Medical Image Analysis, 2018:112-119.