| Hierarchical Graph Representations in Digital Pathology P Pati*, G Jaume*, A Foncubierta, F Feroce, AM Anniciello, ... Medical Image Analysis, 2021 | 106 | 2021 |
| Quantifying Explainers of Graph Neural Networks in Computational Pathology G Jaume*, P Pati*, B Bozorgtabar, A Foncubierta-Rodríguez, F Feroce, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 89 | 2020 |
| HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification P Pati*, G Jaume*, LA Fernandes, A Foncubierta, F Feroce, AM Anniciello, ... MICCAI, Graphs in Biomedical Image Analysis Workshop, 2020 | 79 | 2020 |
| Bracs: A dataset for breast carcinoma subtyping in h&e histology images N Brancati, AM Anniciello, P Pati, D Riccio, G Scognamiglio, G Jaume, ... Database 2022, baac093, 2022 | 69 | 2022 |
| HistoCartography: A Toolkit for Graph Analytics in Digital Pathology G Jaume*, P Pati*, V Anklin, A Foncubierta, M Gabrani MICCAI, Computational Pathology Workshop, 2021 | 46 | 2021 |
| Towards Explainable Graph Representations in Digital Pathology G Jaume*, P Pati*, A Foncubierta-Rodriguez, F Feroce, G Scognamiglio, ... ICML, Computational Biology Workshop, 2020 | 44 | 2020 |
| Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs V Anklin*, P Pati*, G Jaume*, B Bozorgtabar, A Foncubierta-Rodríguez, ... MICCAI, 2021 | 43 | 2021 |
| Multi-organ gland segmentation using deep learning T Binder, EM Tantaoui, P Pati, R Catena, A Set-Aghayan, M Gabrani Frontiers in Medicine, 2019 | 37 | 2019 |
| Tissue staining quality determination NM Arar, M Gabrani, G Kaigala, A Kashyap, AF Khartchenko, P Pati US Patent 10,706,535, 2020 | 36 | 2020 |
| Reducing annotation effort in digital pathology: A Co-Representation learning framework for classification tasks P Pati, A Foncubierta-Rodríguez, O Goksel, M Gabrani Medical image analysis 67, 101859, 2021 | 34 | 2021 |
| Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images K Thandiackal*, B Chen*, P Pati, G Jaume, DFK Williamson, M Gabrani, ... ECCV, 2022 | 32 | 2022 |
| Quantitative microimmunohistochemistry (qμIC): a method to grade immunostains in tumor tissues using saturation kinetics A Kashyap*, A Fomitcheva Khartchenko*, P Pati, M Gabrani, P Schraml, ... Nature Biomedical Engineering, 2019 | 22 | 2019 |
| Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancer P Pati, G Jaume, Z Ayadi, K Thandiackal, B Bozorgtabar, M Gabrani, ... Medical Image Analysis, 2023 | 14 | 2023 |
| A Fast and Scalable Pipeline for Stain Normalization of Whole-Slide Images in Histopathology M Stanisavljevic, A Anghel, N Papandreou, S Andani, P Pati, ... ECCV, BioImage Computing Workshop, 2018 | 11 | 2018 |
| Generative appearance replay for continual unsupervised domain adaptation B Chen, K Thandiackal, P Pati, O Goksel Medical Image Analysis, 2023 | 9 | 2023 |
| Ninepins: Nuclei instance segmentation with point annotations TA Yen, HC Hsu, P Pati, M Gabrani, A Foncubierta-Rodríguez, PC Chung arXiv preprint arXiv:2006.13556, 2020 | 9 | 2020 |
| High-Quality Immunohistochemical Stains through Computational Assay Parameter Optimization P Pati*, N Murat Arar*, A Kashyap, A Fomitcheva Khartchenko, O Goksel, ... IEEE Transactions on Biomedical Engineering, 2019 | 9 | 2019 |
| Deep positive-unlabeled learning for region of interest localization in breast tissue images P Pati, S Andani, M Pediaditis, MP Viana, JH Ruschoff, P Wild, M Gabrani SPIE Medical Imaging 2018: Digital Pathology, 2018 | 9 | 2018 |
| Matching single cells across modalities with contrastive learning and optimal transport F Gossi, P Pati, P Chouvardas, AL Martinelli, M Kruithof-de Julio, ... Briefings in bioinformatics 24 (3), bbad130, 2023 | 8 | 2023 |
| Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis P Pati, G Jaume, LA Fernandes, A Foncubierta-Rodríguez, F Feroce, ... | 8 | 2020 |
Orcun GokselUppsala University在 it.uu.se 的电子邮件经过验证
