2022

Laxmi Gupta, Barbara Mara Klinkhammer, Claudia Seikrit, Nina Fan, Nassim Bouteldja, Philipp Gräbel, Michael Gadermayr, Peter Boor and Dorit Merhof
Large-scale extraction of interpretable features provides new insights into kidney histopathology – a proof-of-concept study
In: Journal of Pathology Informatics

2019

Michael Gadermayr, Laxmi Gupta, Vitus Appel, Peter Boor, Barbara Mara Klinkhammer and Dorit Merhof
Generative Adversarial Networks for Facilitating Stain-Independent Supervised & Unsupervised Segmentation: A Study on Kidney Histology
In: IEEE Transactions on Medical Imaging

2021

Michael Gadermayr, Maximilian Tschuchnig, Laxmi Gupta, Nils Krämer, Daniel Truhn, Dorit Merhof and Burkhard Gess
An asymmetric cycle-consistency loss for dealing with many-to-one mappings in image translation: a study on thigh MR scans
In: IEEE International Symposium on Biomedical Imaging (ISBI)

2019

Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof and Michael Gadermayr
GAN-Based Image Enrichment in Digital Pathology Boosts Segmentation Accuracy
In: International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)

2019

Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof and Michael Gadermayr
Iterative learning to make the most of unlabeled and quickly obtained labeled data in histology
In: 2nd International Conference on Medical Imaging with Deep Learning (MIDL)

2019

Michael Gadermayr, Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor and Dorit Merhof
Unsupervisedly Training GANs for Segmenting Digital Pathology with Automatically Generated Annotations
In: 2nd International Conference on Medical Imaging with Deep Learning (MIDL)

2018

Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof and Michael Gadermayr
Stain Independent Segmentation of Whole Slide Images: A Case Study in Renal Histology
In: IEEE International Symposium on Biomedical Imaging (ISBI)