630 citations · 660 across the 8 of their papers we have counts for
8 papers
GLOWin: A Flow-based Invertible Generative Framework for Learning Disentangled Feature Representations in Medical Images
Aadhithya Sankar, Matthias Keicher, Rami Eisawy +4
Disentangled representations can be useful in many downstream tasks, help to make deep learning models more interpretable, and allow for control over features of synthetically gene…
Self-Supervised Out-of-Distribution Detection in Brain CT Scans
Abinav Ravi Venkatakrishnan, Seong Tae Kim, Rami Eisawy +2
Medical imaging data suffers from the limited availability of annotation because annotating 3D medical data is a time-consuming and expensive task. Moreover, even if the annotation…
Train, Learn, Expand, Repeat
Abhijeet Parida, Aadhithya Sankar, Rami Eisawy +4
High-quality labeled data is essential to successfully train supervised machine learning models. Although a large amount of unlabeled data is present in the medical domain, labelin…
Granular Motor State Monitoring of Free Living Parkinson's Disease Patients via Deep Learning
Kamer A. Yuksel, Jann Goschenhofer, Hridya V. Varma +2
Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide and affects around 1% of the (60+ years old) elderly population in industrial nations. More t…
Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning
Jann Goschenhofer, Franz MJ Pfister, Kamer Ali Yuksel +3
One major challenge in the medication of Parkinson's disease is that the severity of the disease, reflected in the patients' motor state, cannot be measured using accessible biomar…
A Multi-layer Gaussian Process for Motor Symptom Estimation in People with Parkinson's Disease
Muriel Lang, Franz M. J. Pfister, Jakob Fröhner +7
The assessment of Parkinson's disease (PD) poses a significant challenge as it is influenced by various factors which lead to a complex and fluctuating symptom manifestation. Thus,…
Parkinson's Disease Assessment from a Wrist-Worn Wearable Sensor in Free-Living Conditions: Deep Ensemble Learning and Visualization
Terry Taewoong Um, Franz Michael Josef Pfister, Daniel Christian Pichler +5
Parkinson's Disease (PD) is characterized by disorders in motor function such as freezing of gait, rest tremor, rigidity, and slowed and hyposcaled movements. Medication with dopam…
Data Augmentation of Wearable Sensor Data for Parkinson's Disease Monitoring using Convolutional Neural Networks
Terry Taewoong Um, Franz Michael Josef Pfister, Daniel Pichler +5
While convolutional neural networks (CNNs) have been successfully applied to many challenging classification applications, they typically require large datasets for training. When…