140 citations · 174 across the 14 of their papers we have counts for
7 papers · 1 filter
Towards Automated COVID-19 Presence and Severity Classification
Dominik Müller, Niklas Schröter, Silvan Mertes +6
COVID-19 presence classification and severity prediction via (3D) thorax computed tomography scans have become important tasks in recent times. Especially for capacity planning of…
Standardized Medical Image Classification across Medical Disciplines
Simone Mayer, Dominik Müller, Frank Kramer
AUCMEDI is a Python-based framework for medical image classification. In this paper, we evaluate the capabilities of AUCMEDI, by applying it to multiple datasets. Datasets were spe…
Towards a Guideline for Evaluation Metrics in Medical Image Segmentation
Dominik Müller, Iñaki Soto-Rey, Frank Kramer
In the last decade, research on artificial intelligence has seen rapid growth with deep learning models, especially in the field of medical image segmentation. Various studies demo…
Assessing the Role of Random Forests in Medical Image Segmentation
Dennis Hartmann, Dominik Müller, Iñaki Soto-Rey +1
Neural networks represent a field of research that can quickly achieve very good results in the field of medical image segmentation using a GPU. A possible way to achieve good resu…
Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models
Dominik Müller, Iñaki Soto-Rey, Frank Kramer
Preventable or undiagnosed visual impairment and blindness affect billion of people worldwide. Automated multi-disease detection models offer great potential to address this proble…
Automated Chest CT Image Segmentation of COVID-19 Lung Infection based on 3D U-Net
Dominik Müller, Iñaki Soto Rey, Frank Kramer
The coronavirus disease 2019 (COVID-19) affects billions of lives around the world and has a significant impact on public healthcare. Due to rising skepticism towards the sensitivi…
MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning
Dominik Müller, Frank Kramer
The increased availability and usage of modern medical imaging induced a strong need for automatic medical image segmentation. Still, current image segmentation platforms do not pr…