207 citations · 279 across the 7 of their papers we have counts for
12 papers
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…
Alzheimer's Disease Diagnosis via Deep Factorization Machine Models
Raphael Ronge, Kwangsik Nho, Christian Wachinger +1
The current state-of-the-art deep neural networks (DNNs) for Alzheimer's Disease diagnosis use different biomarker combinations to classify patients, but do not allow extracting kn…
Combining 3D Image and Tabular Data via the Dynamic Affine Feature Map Transform
Sebastian Pölsterl, Tom Nuno Wolf, Christian Wachinger
Prior work on diagnosing Alzheimer's disease from magnetic resonance images of the brain established that convolutional neural networks (CNNs) can leverage the high-dimensional ima…
Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data
Sebastian Pölsterl, Christina Aigner, Christian Wachinger
Deep Neural Networks (DNNs) have an enormous potential to learn from complex biomedical data. In particular, DNNs have been used to seamlessly fuse heterogeneous information from n…
Recalibration of Neural Networks for Point Cloud Analysis
Ignacio Sarasua, Sebastian Poelsterl, Christian Wachinger
Spatial and channel re-calibration have become powerful concepts in computer vision. Their ability to capture long-range dependencies is especially useful for those networks that e…
Semi-Structured Deep Piecewise Exponential Models
Philipp Kopper, Sebastian Pölsterl, Christian Wachinger +3
We propose a versatile framework for survival analysis that combines advanced concepts from statistics with deep learning. The presented framework is based on piecewise exponential…