24 citations · 68 across the 25 of their papers we have counts for
9 papers · 1 filter
TomoGraphView: 3D Medical Image Classification with Omnidirectional Slice Representations and Graph Neural Networks
Johannes Kiechle, Stefan M. Fischer, Daniel M. Lang +5
The sharp rise in medical tomography examinations has created a demand for automated systems that can reliably extract informative features for downstream tasks such as tumor chara…
Progressive Growing of Patch Size: Curriculum Learning for Accelerated and Improved Medical Image Segmentation
Stefan M. Fischer, Johannes Kiechle, Laura Daza +6
In this work, we introduce Progressive Growing of Patch Size, an automatic curriculum learning approach for 3D medical image segmentation. Our approach progressively increases the…
MultiMAE for Brain MRIs: Robustness to Missing Inputs Using Multi-Modal Masked Autoencoder
Ayhan Can Erdur, Christian Beischl, Daniel Scholz +4
Missing input sequences are common in medical imaging data, posing a challenge for deep learning models reliant on complete input data. In this work, inspired by MultiMAE [2], we d…
MM-DINOv2: Adapting Foundation Models for Multi-Modal Medical Image Analysis
Daniel Scholz, Ayhan Can Erdur, Viktoria Ehm +4
Vision foundation models like DINOv2 demonstrate remarkable potential in medical imaging despite their origin in natural image domains. However, their design inherently works best…
Contrastive Anatomy-Contrast Disentanglement: A Domain-General MRI Harmonization Method
Daniel Scholz, Ayhan Can Erdur, Robbie Holland +4
Magnetic resonance imaging (MRI) is an invaluable tool for clinical and research applications. Yet, variations in scanners and acquisition parameters cause inconsistencies in image…
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Murong Xu, Tamaz Amiranashvili, Fernando Navarro +30
Accurate delineation of anatomical structures in volumetric CT scans is crucial for diagnosis and treatment planning. While AI has advanced automated segmentation, current approach…
BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis
Florian Kofler, Marcel Rosier, Mehdi Astaraki +26
BrainLesion Suite is a versatile toolkit for building modular brain lesion image analysis pipelines in Python. Following Pythonic principles, BrainLesion Suite is designed to provi…
Enhancing efficiency in paediatric brain tumour segmentation using a pathologically diverse single-center clinical dataset
A. Piffer, J. A. Buchner, A. G. Gennari +11
Background Brain tumours are the most common solid malignancies in children, encompassing diverse histological, molecular subtypes and imaging features and outcomes. Paediatric bra…
Improving Reliability and Explainability of Medical Question Answering through Atomic Fact Checking in Retrieval-Augmented LLMs
Juraj Vladika, Annika Domres, Mai Nguyen +10
Large language models (LLMs) exhibit extensive medical knowledge but are prone to hallucinations and inaccurate citations, which pose a challenge to their clinical adoption and reg…