1.3k citations · 2.3k across the 41 of their papers we have counts for
45 papers
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…
HALOS: Hallucination-free Organ Segmentation after Organ Resection Surgery
Anne-Marie Rickmann, Murong Xu, Tom Nuno Wolf +2
The wide range of research in deep learning-based medical image segmentation pushed the boundaries in a multitude of applications. A clinically relevant problem that received less…
Don't PANIC: Prototypical Additive Neural Network for Interpretable Classification of Alzheimer's Disease
Tom Nuno Wolf, Sebastian Pölsterl, Christian Wachinger
Alzheimer's disease (AD) has a complex and multifactorial etiology, which requires integrating information about neuroanatomy, genetics, and cerebrospinal fluid biomarkers for accu…
Joint Reconstruction and Parcellation of Cortical Surfaces
Anne-Marie Rickmann, Fabian Bongratz, Sebastian Pölsterl +2
The reconstruction of cerebral cortex surfaces from brain MRI scans is instrumental for the analysis of brain morphology and the detection of cortical thinning in neurodegenerative…
Is a PET all you need? A multi-modal study for Alzheimer's disease using 3D CNNs
Marla Narazani, Ignacio Sarasua, Sebastian Pölsterl +3
Alzheimer's Disease (AD) is the most common form of dementia and often difficult to diagnose due to the multifactorial etiology of dementia. Recent works on neuroimaging-based comp…
CASHformer: Cognition Aware SHape Transformer for Longitudinal Analysis
Ignacio Sarasua, Sebastian Pölsterl, Christian Wachinger
Modeling temporal changes in subcortical structures is crucial for a better understanding of the progression of Alzheimer's disease (AD). Given their flexibility to adapt to hetero…