| Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification N Marini, S Otálora, H Müller, M Atzori Medical image analysis 73, 102165, 2021 | 62 | 2021 |
| Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations N Marini, S Marchesin, S Otálora, M Wodzinski, A Caputo, ... NPJ digital medicine 5 (1), 102, 2022 | 50* | 2022 |
| Data-driven color augmentation for H&E stained images in computational pathology N Marini, S Otalora, M Wodzinski, S Tomassini, AF Dragoni, ... Journal of Pathology Informatics 14, 100183, 2023 | 33 | 2023 |
| Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification S Otálora, N Marini, H Müller, M Atzori BMC Medical Imaging 21 (1), 77, 2021 | 28 | 2021 |
| Multi-scale task multiple instance learning for the classification of digital pathology images with global annotations N Marini, S Otálora, F Ciompi, G Silvello, S Marchesin, S Vatrano, ... MICCAI Workshop on Computational Pathology, 170-181, 2021 | 26 | 2021 |
| Multi_scale_tools: a python library to exploit multi-scale whole slide images N Marini, S Otálora, D Podareanu, M van Rijthoven, J van der Laak, ... Frontiers in Computer Science 3, 684521, 2021 | 22 | 2021 |
| H&E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin & Eosin regression N Marini, M Atzori, S Otálora, S Marchand-Maillet, H Müller Proceedings of the IEEE/CVF International Conference on Computer Vision, 601-610, 2021 | 22 | 2021 |
| Empowering digital pathology applications through explainable knowledge extraction tools S Marchesin, F Giachelle, N Marini, M Atzori, S Boytcheva, G Buttafuoco, ... Journal of pathology informatics 13, 100139, 2022 | 21 | 2022 |
| Semi-weakly supervised learning for prostate cancer image classification with teacher-student deep convolutional networks S Otálora, N Marini, H Müller, M Atzori Interpretable and Annotation-Efficient Learning for Medical Image Computing …, 2020 | 20 | 2020 |
| The ACROBAT 2022 challenge: automatic registration of breast cancer tissue P Weitz, M Valkonen, L Solorzano, C Carr, K Kartasalo, C Boissin, ... Medical image analysis 97, 103257, 2024 | 14 | 2024 |
| Stainlib: a python library for augmentation and normalization of histopathology H&E images S Otálora, N Marini, D Podareanu, R Hekster, D Tellez, J Van Der Laak, ... BioRxiv, 2022.05. 17.492245, 2022 | 12* | 2022 |
| A DEXiRE for extracting propositional rules from neural networks via binarization V Contreras, N Marini, L Fanda, G Manzo, Y Mualla, JP Calbimonte, ... Electronics 11 (24), 4171, 2022 | 11 | 2022 |
| On-cloud decision-support system for non-small cell lung cancer histology characterization from thorax computed tomography scans S Tomassini, N Falcionelli, G Bruschi, A Sbrollini, N Marini, P Sernani, ... Computerized Medical Imaging and Graphics 110, 102310, 2023 | 7 | 2023 |
| Caption generation from histopathology whole-slide images using pre-trained transformers BC Guevara, N Marini, S Marchesin, W Aswolinskiy, RJ Schlimbach, ... Medical Imaging with Deep Learning, short paper track, 2023 | 7 | 2023 |
| Semi-supervised learning with a teacher-student paradigm for histopathology classification: a resource to face data heterogeneity and lack of local annotations N Marini, S Otálora, H Müller, M Atzori Pattern Recognition. ICPR International Workshops and Challenges: Virtual …, 2021 | 7 | 2021 |
| A systematic comparison of deep learning methods for Gleason grading and scoring JP Dominguez-Morales, L Duran-Lopez, N Marini, S Vicente-Diaz, ... Medical Image Analysis 95, 103191, 2024 | 6 | 2024 |
| RegWSI: Whole slide image registration using combined deep feature-and intensity-based methods: Winner of the ACROBAT 2023 challenge M Wodzinski, N Marini, M Atzori, H Müller Computer Methods and Programs in Biomedicine 250, 108187, 2024 | 6 | 2024 |
| Attention-based interpretable regression of gene expression in histology M Graziani, N Marini, N Deutschmann, N Janakarajan, H Müller, ... International Workshop on Interpretability of Machine Intelligence in …, 2022 | 6 | 2022 |
| Unsupervised method for intra-patient registration of brain magnetic resonance images based on objective function weighting by inverse consistency: Contribution to the brats … M Wodzinski, A Jurgas, N Marini, M Atzori, H Müller International MICCAI Brainlesion Workshop, 241-251, 2022 | 6 | 2022 |
| A multi-task multiple instance learning algorithm to analyze large whole slide images from bright challenge 2022 N Marini, M Wodzinski, M Atzori, H Müller 2022 IEEE International Symposium on Biomedical Imaging Challenges (ISBIC), 1-4, 2022 | 6 | 2022 |
