David Tellez - RankMe

14 papers Journal 9Unranked 5

Year	Rank	Type	Title / Venue / Authors
2021	J	`jnl`	Neural Image Compression for Gigapixel Histopathology Image Analysis. IEEE Trans. Pattern Anal. Mach. Intell. David Tellez, Geert Litjens, Jeroen van der Laak, Francesco Ciompi
2021	—	`conf`	Neural image compression for non-small cell lung cancer subtype classification in H&E stained whole-slide images. Digital Pathology Witali Aswolinskiy, David Tellez, Gabriel Raya, Lieke van der Woude, Monika Looijen-Salamon, Jeroen van der Laak, Katrien Grunberg, Francesco Ciompi
2020	—	`conf`	Extending Unsupervised Neural Image Compression With Supervised Multitask Learning. MIDL David Tellez, Diederik Höppener, Cornelis Verhoef, Dirk J. Grünhagen, Pieter Nierop, Michal Drozdzal, Jeroen van der Laak, Francesco Ciompi
2020	J	`jnl`	Extending Unsupervised Neural Image Compression With Supervised Multitask Learning. CoRR David Tellez, Diederik Höppener, Cornelis Verhoef, Dirk J. Grünhagen, Pieter Nierop, Michal Drozdzal, Jeroen van der Laak, Francesco Ciompi
2020	—	`conf`	Virtual Staining for Mitosis Detection in Breast Histopathology. ISBI Caner Mercan, G. C. A. M. Mooij, David Tellez, Johannes Lotz, Nick Weiss, Marcel van Gerven, Francesco Ciompi
2019	J	`jnl`	Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge. Medical Image Anal. Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikaël Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Josien P. W. Pluim
2019	J	`jnl`	Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology. CoRR David Tellez, Geert Litjens, Péter Bándi, Wouter Bulten, John-Melle Bokhorst, Francesco Ciompi, Jeroen van der Laak
2019	J	`jnl`	Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology. Medical Image Anal. David Tellez, Geert Litjens, Péter Bándi, Wouter Bulten, John-Melle Bokhorst, Francesco Ciompi, Jeroen van der Laak
2018	—	`conf`	H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection. Digital Pathology David Tellez, Maschenka Balkenhol, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak, Francesco Ciompi
2018	J	`jnl`	Neural Image Compression for Gigapixel Histopathology Image Analysis. CoRR David Tellez, Geert Litjens, Jeroen van der Laak, Francesco Ciompi
2018	J	`jnl`	Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge. CoRR Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikaël Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir M. Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric I-Chao Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim
2018	J	`jnl`	Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks. CoRR David Tellez, Maschenka Balkenhol, Irene Otte-Höller, Rob van de Loo, Rob Vogels, Peter Bult, Carla Wauters, Willem Vreuls, Suzanne Mol, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak, Francesco Ciompi
2018	J	`jnl`	Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks. IEEE Trans. Medical Imaging David Tellez, Maschenka Balkenhol, Irene Otte-Höller, Rob van de Loo, Rob Vogels, Peter Bult, Carla Wauters, Willem Vreuls, Suzanne Mol, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak, Francesco Ciompi
2014	—	`conf`	Predicting arousal with machine learning of EEG signals. CogInfoCom Tamás Nagy, David Tellez, Ádám Divák, Emma Lógó, Máté Köles, Balázs Péter Hámornik