33 citations · 71 across the 8 of their papers we have counts for
8 papers · 1 filter
Joint Debiased Representation and Image Clustering Learning with Self-Supervision
Shunjie-Fabian Zheng, JaeEun Nam, Emilio Dorigatti +3
Contrastive learning is among the most successful methods for visual representation learning, and its performance can be further improved by jointly performing clustering on the le…
Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images
Farzin Soleymani, Mohammad Eslami, Tobias Elze +2
We propose a Deep Variational Clustering (DVC) framework for unsupervised representation learning and clustering of large-scale medical images. DVC simultaneously learns the multiv…
Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data
Mina Rezaei, Haojin Yang, Christoph Meinel
We propose a new generative adversarial architecture to mitigate imbalance data problem for the task of medical image semantic segmentation where the majority of pixels belong to a…
Conditional Generative Refinement Adversarial Networks for Unbalanced Medical Image Semantic Segmentation
Mina Rezaei, Haojin Yang, Christoph Meinel
We propose a new generative adversarial architecture to mitigate imbalance data problem in medical image semantic segmentation where the majority of pixels belongs to a healthy reg…
Deep Learning for Medical Image Analysis
Mina Rezaei, Haojin Yang, Christoph Meinel
This report describes my research activities in the Hasso Plattner Institute and summarizes my Ph.D. plan and several novels, end-to-end trainable approaches for analyzing medical…
Conditional Adversarial Network for Semantic Segmentation of Brain Tumor
Mina Rezaei, Konstantin Harmuth, Willi Gierke +4
Automated medical image analysis has a significant value in diagnosis and treatment of lesions. Brain tumors segmentation has a special importance and difficulty due to the differe…