← Back to papers

2024 MIDL MIDL 2024

IHCScoreGAN: An unsupervised generative adversarial network for end-to-end ki67 scoring for clinical breast cancer diagnosis

Authors

Carl Molnar , Thomas E. Tavolara , Christopher A. Garcia , David S. McClintock , Mark D. Zarella , Wenchao Han

Related papers

Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training 2024

HoVer-NeXt: A Fast Nuclei Segmentation and Classification Pipeline for Next Generation Histopathology 2024

Network conditioning for synergistic learning on partial annotations 2024

Real-time MR-based 3D motion monitoring using raw k-space data 2024

Target and task specific source-free domain adaptive image segmentation 2024