Katherine Jane Hewitt

According to our database, Katherine Jane Hewitt authored at least 5 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance.

Jan Moritz Niehues, Gustav Müller-Franzes, Yoni Schirris, Sophia J. Wagner, Michael Jendrusch, Matthias Kloor, Alexander T. Pearson, Hannah Sophie Muti, Katherine Jane Hewitt, Gregory Patrick Veldhuizen, Laura Zigutyte, Daniel Truhn, Jakob Nikolas Kather

Comput. Biol. Medicine, 2024

2023

From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology.

Omar S. M. El Nahhas, Marko van Treeck, Georg Wölflein, Michaela Unger, Marta Ligero, Tim Lenz, Sophia J. Wagner, Katherine Jane Hewitt, Firas Khader, Sebastian Foersch, Daniel Truhn, Jakob Nikolas Kather

CoRR, 2023

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides.

Omar S. M. El Nahhas, Chiara Maria Lavinia Loeffler, Zunamys I. Carrero, Marko van Treeck, Fiona R. Kolbinger, Katherine Jane Hewitt, Hannah Sophie Muti, Mara Graziani, Qinghe Zeng, Julien Calderaro, Nadina Ortiz-Brüchle, Tanwei Yuan, Michael Hoffmeister, Hermann Brenner, Alexander Brobeil, Jorge S. Reis-Filho, Jakob Nikolas Kather

CoRR, 2023

2022

Test Time Transform Prediction for Open Set Histopathological Image Recognition.

Adrian Galdran, Katherine Jane Hewitt, Narmin Ghaffari Laleh, Jakob Nikolas Kather, Gustavo Carneiro, Miguel Ángel González Ballester

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Deep Learning for interpretable end-to-end survival (E-ESurv) prediction in gastrointestinal cancer histopathology.

Narmin Ghaffari Laleh, Amelie Echle, Hannah Sophie Muti, Katherine Jane Hewitt, Volkmar Schulz, Jakob Nikolas Kather

Proceedings of the MICCAI Workshop on Computational Pathology, 2021