Publications of David Tellez
2024
Papers in international journals
- D. Höppener, W. Aswolinskiy, Z. Qian, D. Tellez, P. Nierop, M. Starmans, I. Nagtegaal, M. Doukas, J. de Wilt, D. Grünhagen, J. van der Laak, P. Vermeulen, F. Ciompi and C. Verhoef, "Classifying histopathological growth patterns for resected colorectal liver metastasis with a deep learning analysis", BJS Open, 2024;8.
Abstracts
- L. Tessier, C. Gonzalez-Gonzalo, D. Tellez, W. Bulten and M. van der Laak, "Large-scale validation of AI-assisted mitosis counting in breast cancer", European Congress on Digital Pathology, 2024.
2022
Papers in international journals
- S. Otálora, N. Marini, D. Podareanu, R. Hekster, D. Tellez, J. Der Van Laak, H. Müller and M. Atzori, "stainlib: a python library for augmentation and normalization of histopathology H&E images", Preprint, 2022.
2021
Papers in international journals
- D. Tellez, G. Litjens, J. van der Laak and F. Ciompi, "Neural Image Compression for Gigapixel Histopathology Image Analysis.", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021;43(2):567-578.
Papers in conference proceedings
- W. Aswolinskiy, D. Tellez, G. Raya, L. van der Woude, M. Looijen-Salamon, J. van der Laak, K. Grunberg and F. Ciompi, "Neural image compression for non-small cell lung cancer subtype classification in H&E stained whole-slide images", Medical Imaging 2021: Digital Pathology, 2021;11603:1 - 7.
PhD theses
- D. Tellez, "Advancing computational pathology with deep learning: from patches to gigapixel image-level classification", PhD thesis, 2021.
2020
Papers in conference proceedings
- D. Tellez, D. Hoppener, C. Verhoef, D. Grunhagen, P. Nierop, M. Drozdzal, J. van der Laak and F. Ciompi, "Extending Unsupervised Neural Image Compression With Supervised Multitask Learning", Medical Imaging with Deep Learning, 2020.
Abstracts
- M. Balkenhol, P. Bult, D. Tellez, W. Vreuls, P. Clahsen, F. Ciompi and J. der Laak, "Deep learning enables fully automated mitotic density assessment in breast cancer histopathology", European Journal of Cancer, 2020.
2019
Papers in international journals
- D. Tellez, G. Litjens, P. Bándi, W. Bulten, J. Bokhorst, F. Ciompi and J. van der Laak, "Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology", Medical Image Analysis, 2019;58:101544.
- M. Balkenhol, D. Tellez, W. Vreuls, P. Clahsen, H. Pinckaers, F. Ciompi, P. Bult and J. van der Laak, "Deep learning assisted mitotic counting for breast cancer", Laboratory Investigation, 2019.
- M. Balkenhol, P. Bult, D. Tellez, W. Vreuls, P. Clahsen, F. Ciompi and J. van der Laak, "Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer", Cellular Oncology, 2019;42:4555-4569.
- M. Veta, Y. Heng, N. Stathonikos, B. Bejnordi, F. Beca, T. Wollmann, K. Rohr, M. Shah, D. Wang, M. Rousson, M. Hedlund, D. Tellez, F. Ciompi, E. Zerhouni, D. Lanyi, M. Viana, V. Kovalev, V. Liauchuk, H. Phoulady, T. Qaiser, S. Graham, N. Rajpoot, E. Sjoblom, J. Molin, K. Paeng, S. Hwang, S. Park, Z. Jia, E. Chang, Y. Xu, A. Beck, P. van Diest and J. Pluim, "Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge", Medical Image Analysis, 2019;54(5):111-121.
2018
Papers in international journals
- 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.
Papers in conference proceedings
- D. Tellez, J. van der Laak and F. Ciompi, "Gigapixel Whole-Slide Image Classification Using Unsupervised Image Compression And Contrastive Training", Medical Imaging with Deep Learning, 2018.
- 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.
2017
Papers in international journals
- B. Ehteshami Bejnordi, M. Veta, P. van Diest, B. van Ginneken, N. Karssemeijer, G. Litjens, J. van der Laak, T. Consortium, M. Hermsen, Q. Manson, M. Balkenhol, O. Geessink, N. Stathonikos, M. van Dijk, P. Bult, F. Beca, A. Beck, D. Wang, A. Khosla, R. Gargeya, H. Irshad, A. Zhong, Q. Dou, Q. Li, H. Chen, H. Lin, P. Heng, C. Haß, E. Bruni, Q. Wong, U. Halici, M. Öner, R. Cetin-Atalay, M. Berseth, V. Khvatkov, A. Vylegzhanin, O. Kraus, M. Shaban, N. Rajpoot, R. Awan, K. Sirinukunwattana, T. Qaiser, Y. Tsang, D. Tellez, J. Annuscheit, P. Hufnagl, M. Valkonen, K. Kartasalo, L. Latonen, P. Ruusuvuori, K. Liimatainen, S. Albarqouni, B. Mungal, A. George, S. Demirci, N. Navab, S. Watanabe, S. Seno, Y. Takenaka, H. Matsuda, H. Ahmady Phoulady, V. Kovalev, A. Kalinovsky, V. Liauchuk, G. Bueno, M. Fernandez-Carrobles, I. Serrano, O. Deniz, D. Racoceanu and R. Venâncio, "Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer", Journal of the American Medical Association, 2017;318(22):2199-2210.