Generative Adversarial Networks in Digital Pathology: A Survey on Trends
and Future Potential

Generative Adversarial Networks in Digital Pathology: A Survey on Trends and Future Potential

30 April 2020

Papers citing "Generative Adversarial Networks in Digital Pathology: A Survey on Trends and Future Potential"

7 / 7 papers shown

Title
Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancer Pushpak Pati Guillaume Jaume Zeineb Ayadi Kevin Thandiackal Behzad Bozorgtabar M. Gabrani O. Goksel 20 17 0 07 Jan 2023
Deep Learning Generates Synthetic Cancer Histology for Explainability and Education J. Dolezal Rachelle Wolk Hanna M. Hieromnimon Frederick M. Howard Andrew Srisuwananukorn ... A. Husain Huihua Li Robert L. Grossman N. Cipriani A. Pearson MedIm 33 40 0 12 Nov 2022
Region-guided CycleGANs for Stain Transfer in Whole Slide Images Joseph Boyd I. Villa M. Mathieu Eric Deutsch Nikos Paragios Maria Vakalopoulou Stergios Christodoulidis MedIm 18 13 0 26 Aug 2022
Improving Unsupervised Stain-To-Stain Translation using Self-Supervision and Meta-Learning Nassim Bouteldja B. Klinkhammer Tarek Schlaich P. Boor Dorit Merhof MedIm 37 20 0 16 Dec 2021
Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations S. J. Wagner Nadieh Khalili Raghav Sharma Melanie Boxberg Carsten Marr Walter de Back Tingying Peng OOD MedIm 18 52 0 26 Jul 2021
Objective Diagnosis for Histopathological Images Based on Machine Learning Techniques: Classical Approaches and New Trends Naira Elazab Hassan H. Soliman Shaker El-Sappagh S. Islam Mohammed M Elmogy 17 20 0 10 Nov 2020
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 343 10,633 0 19 Feb 2017