Tree Nash Equilibria in the Network Creation Game. - Akaki Mamageishvili; Matús Mihalák; Dominik Müller (Internet Math., 2015)

Transient thermal analysis for accelerated reliability testing of LEDs. - Gordon Elger; Dominik Müller; Alexander Hanß; Maximilian Schmid; E. Liu; Udo Karbowski; Robert Derix (Microelectron. Reliab., 2016)

Dependence modelling in ultra high dimensions with vine copulas and the Graphical Lasso. - Dominik Müller; Claudia Czado (Comput. Stat. Data Anal., 2019)

Selection of sparse vine copulas in high dimensions with the Lasso. - Dominik Müller; Claudia Czado (Stat. Comput., 2019)

Automated Chest CT Image Segmentation of COVID-19 Lung Infection based on 3D U-Net. - Dominik Müller; Iñaki Soto Rey; Frank Kramer 001 (CoRR, 2020)

Multi-Disease Detection in Retinal Imaging Based on Ensembling Heterogeneous Deep Learning Models. - Dominik Müller; Iñaki Soto Rey; Frank Kramer 001 (GMDS, 2021)

Perspective on Code Submission and Automated Evaluation Platforms for University Teaching. - Florian Auer; Johann Frei; Dominik Müller; Frank Kramer 001 (MedInfo, 2021)

COVID-19 Image Segmentation Based on Deep Learning and Ensemble Learning. - Philip Meyer; Dominik Müller; Iñaki Soto Rey; Frank Kramer 001 (MIE, 2021)

MIScnn: a framework for medical image segmentation with convolutional neural networks and deep learning. - Dominik Müller; Frank Kramer 001 (BMC Medical Imaging, 2021)

New Simulation Software Technologies at the LHCb Experiment at CERN. - Michal Mazurek; Gloria Corti; Dominik Müller (Comput. Informatics, 2021)

Assessing the Role of Random Forests in Medical Image Segmentation. - Dennis Hartmann; Dominik Müller; Iñaki Soto Rey; Frank Kramer 001 (CoRR, 2021)

Classification of Viral Pneumonia X-ray Images with the Aucmedi Framework. - Pia Schneider; Dominik Müller; Frank Kramer 001 (CoRR, 2021)

Adaptation of HL7 FHIR for the Exchange of Patients' Gene Expression Profiles. - Florian Auer; Zhibek Abdykalykova; Dominik Müller; Frank Kramer 001 (ICIMTH, 2022)

Implementation of Gene Expression Profiles in the HL7 FHIR Standard. - Florian Auer; Zhibek Abdykalykova; Dominik Müller; Frank Kramer 001 (MIE, 2022)

MISeval: A Metric Library for Medical Image Segmentation Evaluation. - Dominik Müller; Dennis Hartmann; Philip Meyer; Florian Auer; Iñaki Soto Rey; Frank Kramer 001 (MIE, 2022)

An Analysis on Ensemble Learning Optimized Medical Image Classification With Deep Convolutional Neural Networks. - Dominik Müller; Iñaki Soto Rey; Frank Kramer 001 (IEEE Access, 2022)

Towards a Guideline for Evaluation Metrics in Medical Image Segmentation. - Dominik Müller; Iñaki Soto Rey; Frank Kramer 001 (CoRR, 2022)

Standardized Medical Image Classification across Medical Disciplines. - Simone Mayer; Dominik Müller; Frank Kramer 001 (CoRR, 2022)

MISm: A Medical Image Segmentation Metric for Evaluation of weak labeled Data. - Dennis Hartmann; Verena Schmid; Philip Meyer; Iñaki Soto Rey; Dominik Müller; Frank Kramer 001 (CoRR, 2022)

Abstract: AUCMEDI - Von der Insellösung zur einheitlichen und automatischen Klassifizierung von Medizinischen Bildern. - Dominik Müller; Dennis Hartmann; Iñaki Soto Rey; Frank Kramer 001 (Bildverarbeitung für die Medizin, 2023)

The RCX Extension Hub: A Resource for Implementations Extending the R Adaption of the Cytoscape Exchange Format. - Florian Auer; Nadja Bramkamp; Simone Mayer; Dominik Müller; Frank Kramer 001 (MIE, 2023)

Towards Automated COVID-19 Presence and Severity Classification. - Dominik Müller; Silvan Mertes; Niklas Schröter; Fabio Hellmann; Miriam Elia; Bernhard Bauer 001; Wolfgang Reif; Elisabeth André; Frank Kramer 001 (MIE, 2023)

Enhanced Mortality Prediction In Patients With Subarachnoid Haemorrhage Using A Deep Learning Model Based On The Initial CT Scan. - Sergio Garcia-Garcia; Santiago Cepeda; Dominik Müller; Alejandra Mosteiro; Ramon Torne; Silvia Agudo; Natalia de la Torre; Ignacio Arrese; Rosario Sarabia (CoRR, 2023)

Frameworks in medical image analysis with deep neural networks - Dominik Müller (2023)

Predicting Overall Survival of Glioblastoma Patients Using Deep Learning Classification Based on MRIs. - Katharina Ott; Santiago Cepeda; Dennis Hartmann; Frank Kramer 001; Dominik Müller (GMDS, 2024)

Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer. - Dominik Müller; Philip Meyer; Lukas Rentschler; Robin Manz; Daniel Hieber; Jonas Bäcker; Samantha Cramer; Christoph Wengenmayr; Bruno Märkl; Ralf Huss; Frank Kramer 001; Iñaki Soto Rey; et al. (MIE, 2024)

Towards a FHIR-Based Framework for Analyzing Nursing-Related Data in Smaller Sized Care Facilities. - Steffen Netzband; Dominik Müller; Stefanie Meyer; Jeton Iseni; Frank Kramer 001 (MIE, 2024)

Deep Learning Based Automatic Fibroglandular Tissue Segmentation in Breast Magnetic Resonance Imaging Screening. - Guelsuem Pehlivan; Carl Mathis Wild; Julia Baumgartl; Dennis Hartmann; Nina Ditsch; Frank Kramer 001; Dominik Müller (MIE, 2024)

DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks. - Dominik Müller; Philip Meyer; Lukas Rentschler; Robin Manz; Jonas Bäcker; Samantha Cramer; Christoph Wengenmayr; Bruno Märkl; Ralf Huss; Iñaki Soto Rey; Johannes Raffler (CoRR, 2024)

The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data. - Luuk H. Boulogne; Julian Lorenz; Daniel Kienzle; Robin Schön; Katja Ludwig; Rainer Lienhart; Simon Jégou; Guang Li; Cong Chen; Qi Wang; Derik Shi; Mayug Maniparambil; et al. (Medical Image Anal., 2024)

RFMiD: Retinal Image Analysis for multi-Disease Detection challenge. - Samiksha Pachade; Prasanna Porwal; Manesh Kokare; Girish Deshmukh; Vivek Sahasrabuddhe; Zhengbo Luo; Feng Han; Zitang Sun; Li Qihan; Sei-ichiro Kamata; Edward Ho; Edward Wang; et al. (Medical Image Anal., 2025)