Fusion of Domain-Adapted Vision and Language Models for Medical Visual Question Answering

no code implementations • 24 Apr 2024 • Cuong Nhat Ha, Shima Asaadi, Sanjeev Kumar Karn, Oladimeji Farri, Tobias Heimann, Thomas Runkler

Vision-language models, while effective in general domains and showing strong performance in diverse multi-modal applications like visual question-answering (VQA), struggle to maintain the same level of effectiveness in more specialized domains, e. g., medical.

Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation

1 code implementation • 14 Jul 2023 • Jingna Qiu, Frauke Wilm, Mathias Öttl, Maja Schlereth, Chang Liu, Tobias Heimann, Marc Aubreville, Katharina Breininger

We find that the efficiency of this method highly depends on the choice of AL step size (i. e., the combination of region size and the number of selected regions per WSI), and a suboptimal AL step size can result in redundant annotation requests or inflated computation costs.

Active Learning Informativeness +2

End-to-end Learning for Image-based Detection of Molecular Alterations in Digital Pathology

no code implementations • 30 Jun 2022 • Marvin Teichmann, Andre Aichert, Hanibal Bohnenberger, Philipp Ströbel, Tobias Heimann

We propose a novel learning pipeline for WSI classification that is trainable end-to-end and does not require any auxiliary annotations.

whole slide images