63 citations · 63 across the 8 of their papers we have counts for
8 papers
X-SiT: Inherently Interpretable Surface Vision Transformers for Dementia Diagnosis
Fabian Bongratz, Tom Nuno Wolf, Jaume Gual Ramon +1
Interpretable models are crucial for supporting clinical decision-making, driving advances in their development and application for medical images. However, the nature of 3D volume…
DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation
Emre Kavak, Tom Nuno Wolf, Christian Wachinger
Dataset bias often leads deep learning models to exploit spurious correlations instead of task-relevant signals. We introduce the Standard Anti-Causal Model (SAM), a unifying causa…
SIC: Similarity-Based Interpretable Image Classification with Neural Networks
Tom Nuno Wolf, Emre Kavak, Fabian Bongratz +1
The deployment of deep learning models in critical domains necessitates a balance between high accuracy and interpretability. We introduce SIC, an inherently interpretable neural n…
From Barlow Twins to Triplet Training: Differentiating Dementia with Limited Data
Yitong Li, Tom Nuno Wolf, Sebastian Pölsterl +3
Differential diagnosis of dementia is challenging due to overlapping symptoms, with structural magnetic resonance imaging (MRI) being the primary method for diagnosis. Despite the…
Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning
Tom Nuno Wolf, Fabian Bongratz, Anne-Marie Rickmann +2
Explaining predictions of black-box neural networks is crucial when applied to decision-critical tasks. Thus, attribution maps are commonly used to identify important image regions…
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…
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…