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Jacob Gildenblat
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2020 – today
- 2024
- [i6]Jacob Gildenblat, Ofir Hadar:
Segmentation by Factorization: Unsupervised Semantic Segmentation for Pathology by Factorizing Foundation Model Features. CoRR abs/2409.05697 (2024) - 2023
- [c3]Jacob Gildenblat, Anil Yüce, Samaneh Abbasi-Sureshjani, Konstanty Korski:
Deep Cellular Embeddings: An Explainable Plug and Play Improvement for Feature Representation in Histopathology. MICCAI (6) 2023: 776-785 - 2022
- [j2]Eduardo Conde-Sousa, João Vale, Ming Feng, Kele Xu, Yin Wang, Vincenzo Della Mea, David La Barbera, Ehsan Montahaei, Mahdieh Soleymani Baghshah, Andreas Turzynski, Jacob Gildenblat, Eldad Klaiman, Yiyu Hong, Guilherme Aresta, Teresa Araújo, Paulo Aguiar, Catarina Eloy, António Polónia:
HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin-Eosin Whole-Slide Imaging. J. Imaging 8(8): 213 (2022) - 2021
- [i5]Eduardo Conde-Sousa, João Vale, Ming Feng, Kele Xu, Yin Wang, Vincenzo Della Mea, David La Barbera, Ehsan Montahaei, Mahdieh Soleymani Baghshah, Andreas Turzynski, Jacob Gildenblat, Eldad Klaiman, Yiyu Hong, Guilherme Aresta, Teresa Araújo, Paulo Aguiar, Catarina Eloy, António Polónia:
HEROHE Challenge: assessing HER2 status in breast cancer without immunohistochemistry or in situ hybridization. CoRR abs/2111.04738 (2021) - 2020
- [c2]Jacob Gildenblat, Ido Ben-Shaul, Zvi Lapp, Eldad Klaiman:
Certainty Pooling for Multiple Instance Learning. ICPR Workshops (1) 2020: 141-153 - [i4]Jacob Gildenblat, Ido Ben-Shaul, Zvi Lapp, Eldad Klaiman:
Certainty Pooling for Multiple Instance Learning. CoRR abs/2008.10548 (2020)
2010 – 2019
- 2019
- [j1]Amal Lahiani, Jacob Gildenblat, Irina Klaman, Nassir Navab, Eldad Klaiman:
Generalising multistain immunohistochemistry tissue segmentation using end-to-end colour deconvolution deep neural networks. IET Image Process. 13(7): 1066-1073 (2019) - [c1]Amal Lahiani, Jacob Gildenblat, Irina Klaman, Shadi Albarqouni, Nassir Navab, Eldad Klaiman:
Virtualization of Tissue Staining in Digital Pathology Using an Unsupervised Deep Learning Approach. ECDP 2019: 47-55 - [i3]Jacob Gildenblat, Eldad Klaiman:
Self-Supervised Similarity Learning for Digital Pathology. CoRR abs/1905.08139 (2019) - 2018
- [i2]Amal Lahiani, Jacob Gildenblat, Irina Klaman, Nassir Navab, Eldad Klaiman:
Generalizing multistain immunohistochemistry tissue segmentation using one-shot color deconvolution deep neural networks. CoRR abs/1805.06958 (2018) - [i1]Amal Lahiani, Jacob Gildenblat, Irina Klaman, Shadi Albarqouni, Nassir Navab, Eldad Klaiman:
Virtualization of tissue staining in digital pathology using an unsupervised deep learning approach. CoRR abs/1810.06415 (2018)
Coauthor Index
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