2 citations · 5 across the 6 of their papers we have counts for
6 papers
Neural Image Unfolding: Flattening Sparse Anatomical Structures using Neural Fields
Leonhard Rist, Pluvio Stephan, Noah Maul +6
Tomographic imaging reveals internal structures of 3D objects and is crucial for medical diagnoses. Visualizing the morphology and appearance of non-planar sparse anatomical struct…
Comparative Analysis of Radiomic Features and Gene Expression Profiles in Histopathology Data Using Graph Neural Networks
Luis Carlos Rivera Monroy, Leonhard Rist, Martin Eberhardt +5
This study leverages graph neural networks to integrate MELC data with Radiomic-extracted features for melanoma classification, focusing on cell-wise analysis. It assesses the effe…
Employing Graph Representations for Cell-level Characterization of Melanoma MELC Samples
Luis Carlos Rivera Monroy, Leonhard Rist, Martin Eberhardt +5
Histopathology imaging is crucial for the diagnosis and treatment of skin diseases. For this reason, computer-assisted approaches have gained popularity and shown promising results…
Building Brains: Subvolume Recombination for Data Augmentation in Large Vessel Occlusion Detection
Florian Thamm, Oliver Taubmann, Markus Jürgens +5
Ischemic strokes are often caused by large vessel occlusions (LVOs), which can be visualized and diagnosed with Computed Tomography Angiography scans. As time is brain, a fast, acc…
An Algorithm for the Labeling and Interactive Visualization of the Cerebrovascular System of Ischemic Strokes
Florian Thamm, Markus Jürgens, Oliver Taubmann +4
During the diagnosis of ischemic strokes, the Circle of Willis and its surrounding vessels are the arteries of interest. Their visualization in case of an acute stroke is often ena…
Segmentation of the Carotid Lumen and Vessel Wall using Deep Learning and Location Priors
Florian Thamm, Felix Denzinger, Leonhard Rist +3
In this report we want to present our method and results for the Carotid Artery Vessel Wall Segmentation Challenge. We propose an image-based pipeline utilizing the U-Net architect…