45 citations · 141 across the 20 of their papers we have counts for
8 papers · 1 filter
A Semi-automatic Cranial Implant Design Tool Based on Rigid ICP Template Alignment and Voxel Space Reconstruction
Michael Lackner, Behrus Puladi, Jens Kleesiek +2
In traumatic medical emergencies, the patients heavily depend on cranioplasty - the craft of neurocranial repair using cranial implants. Despite the improvements made in recent yea…
How we won BraTS 2023 Adult Glioma challenge? Just faking it! Enhanced Synthetic Data Augmentation and Model Ensemble for brain tumour segmentation
André Ferreira, Naida Solak, Jianning Li +4
Deep Learning is the state-of-the-art technology for segmenting brain tumours. However, this requires a lot of high-quality data, which is difficult to obtain, especially in the me…
Anatomy Completor: A Multi-class Completion Framework for 3D Anatomy Reconstruction
Jianning Li, Antonio Pepe, Gijs Luijten +3
In this paper, we introduce a completion framework to reconstruct the geometric shapes of various anatomies, including organs, vessels and muscles. Our work targets a scenario wher…
Open-Source Skull Reconstruction with MONAI
Jianning Li, André Ferreira, Behrus Puladi +7
We present a deep learning-based approach for skull reconstruction for MONAI, which has been pre-trained on the MUG500+ skull dataset. The implementation follows the MONAI contribu…
Automated cross-sectional view selection in CT angiography of aortic dissections with uncertainty awareness and retrospective clinical annotations
Antonio Pepe, Jan Egger, Marina Codari +7
Objective: Surveillance imaging of chronic aortic diseases, such as dissections, relies on obtaining and comparing cross-sectional diameter measurements at predefined aortic landma…
Learning to Rearrange Voxels in Binary Segmentation Masks for Smooth Manifold Triangulation
Jianning Li, Antonio Pepe, Christina Gsaxner +2
Medical images, especially volumetric images, are of high resolution and often exceed the capacity of standard desktop GPUs. As a result, most deep learning-based medical image ana…