Using Hierarchically Connected Nodes and Multiple GNN Message Passing Steps to Increase the Contextual Information in Cell-Graph Classification. - Joe Sims; Heike Irmgard Grabsch; Derek R. Magee (ISGIE/GRAIL@MICCAI, 2022)

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. - Narmin Ghaffari Laleh; Hannah Sophie Muti; Chiara Maria Lavinia Loeffler; Amelie Echle; Oliver Lester Saldanha; Faisal Mahmood 001; Ming Y. Lu; Christian Trautwein; Rupert Langer; Bastian Dislich; Roman David Bülow; Heike Irmgard Grabsch; et al. (Medical Image Anal., 2022)

Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474. - Narmin Ghaffari Laleh; Hannah Sophie Muti; Chiara Maria Lavinia Loeffler; Amelie Echle; Oliver Lester Saldanha; Faisal Mahmood 001; Ming Y. Lu; Christian Trautwein; Rupert Langer; Bastian Dislich; Roman David Bülow; Heike Irmgard Grabsch; et al. (Medical Image Anal., 2022)

Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study. - Sophia J. Wagner; Daniel Reisenbüchler; Nicholas P. West; Jan Moritz Niehues; Gregory Patrick Veldhuizen; Philip Quirke; Heike Irmgard Grabsch; Piet A. van den Brandt; Gordon G. A. Hutchins; Susan D. Richman; Tanwei Yuan; Rupert Langer; et al. (CoRR, 2023)

A Hybrid Transformer-Graph Model for Multi-Class Lymph Node Segmentation in Histopathology. - Elzbieta Budginaite; Derek R. Magee; Maximilian Kloft; Matthew Nankivell; Ruth E. Langley; David Cunningham; William H. Allum; Gayatri Raghuram; Takaki Yoshikawa; Takashi Oshima; Henry C. Woodruff; Heike Irmgard Grabsch (MIUA (3), 2025)