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ORCIDDominik Müller
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2020 – today
- 2025
[j9]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, Asaanth Sivajohan, Saerom Youn, Kevin Lane, Jin Chun, Xinliang Wang, Yunchao Gu, Sixu Lu, Young-tack Oh, Hyunjin Park, Chia-Yen Lee, Hung Yeh, Kai-Wen Cheng, Haoyu Wang, Jin Ye, Junjun He, Lixu Gu, Dominik Müller, Iñaki Soto Rey, Frank Kramer, Hidehisa Arai, Yuma Ochi, Takami Okada, Luca Giancardo, Gwenolé Quellec, Fabrice Mériaudeau:
RFMiD: Retinal Image Analysis for multi-Disease Detection challenge. Medical Image Anal. 99: 103365 (2025)- 2024
- [j8]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, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matías Nicolás Bossa, Abel Díaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran Razzak, Mohamed Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A. Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken, Marie-Pierre Revel:
The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data. Medical Image Anal. 97: 103230 (2024) - [c14]Katharina Ott, Santiago Cepeda, Dennis Hartmann, Frank Kramer, Dominik Müller:
Predicting Overall Survival of Glioblastoma Patients Using Deep Learning Classification Based on MRIs. GMDS 2024: 356-365 - [c13]Steffen Netzband, Dominik Müller, Stefanie Meyer, Jeton Iseni, Frank Kramer:
Towards a FHIR-Based Framework for Analyzing Nursing-Related Data in Smaller Sized Care Facilities. MIE 2024: 1029-1030 - [c12]Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz, Daniel Hieber, Jonas Bäcker, Samantha Cramer, Christoph Wengenmayr, Bruno Märkl, Ralf Huss, Frank Kramer, Iñaki Soto Rey, Johannes Raffler:
Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer. MIE 2024: 1110-1114 - [c11]Guelsuem Pehlivan, Carl Mathis Wild, Julia Baumgartl, Dennis Hartmann, Nina Ditsch, Frank Kramer, Dominik Müller:
Deep Learning Based Automatic Fibroglandular Tissue Segmentation in Breast Magnetic Resonance Imaging Screening. MIE 2024: 1115-1119 - [i17]Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz, Jonas Bäcker, Samantha Cramer, Christoph Wengenmayr, Bruno Märkl, Ralf Huss, Iñaki Soto Rey, Johannes Raffler:
DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks. CoRR abs/2403.16678 (2024) - [i16]Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz, Daniel Hieber, Jonas Bäcker, Samantha Cramer, Christoph Wengenmayr, Bruno Märkl, Ralf Huss, Frank Kramer, Iñaki Soto Rey, Johannes Raffler:
Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer. CoRR abs/2403.16695 (2024) - 2023
- [b1]Dominik Müller:
Frameworks in medical image analysis with deep neural networks. University of Augsburg, Germany, 2023 - [c10]Dominik Müller, Dennis Hartmann, Iñaki Soto Rey, Frank Kramer:
Abstract: AUCMEDI - Von der Insellösung zur einheitlichen und automatischen Klassifizierung von Medizinischen Bildern. Bildverarbeitung für die Medizin 2023: 253 - [c9]Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Bernhard Bauer, Wolfgang Reif, Elisabeth André, Frank Kramer:
Towards Automated COVID-19 Presence and Severity Classification. MIE 2023: 917-921 - [c8]Florian Auer, Nadja Bramkamp, Simone Mayer, Dominik Müller, Frank Kramer:
The RCX Extension Hub: A Resource for Implementations Extending the R Adaption of the Cytoscape Exchange Format. MIE 2023: 1075-1076 - [i15]Dominik Müller, Niklas Schröter, Silvan Mertes, Fabio Hellmann, Miriam Elia, Wolfgang Reif, Bernhard Bauer, Elisabeth André, Frank Kramer:
Towards Automated COVID-19 Presence and Severity Classification. CoRR abs/2305.08660 (2023) - [i14]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, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matías Nicolás Bossa, Abel Díaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran Razzak, Mohamed Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A. Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken, Marie-Pierre Revel Dubois:
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data. CoRR abs/2306.10484 (2023) - [i13]Sergio Garcia-Garcia, Santiago Cepeda, Dominik Müller, Alejandra Mosteiro, Ramon Torne, Silvia Agudo, Natalia de la Torre, Ignacio Arrese, Rosario Sarabia:
Enhanced Mortality Prediction In Patients With Subarachnoid Haemorrhage Using A Deep Learning Model Based On The Initial CT Scan. CoRR abs/2308.13373 (2023) - 2022
- [j7]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
An Analysis on Ensemble Learning Optimized Medical Image Classification With Deep Convolutional Neural Networks. IEEE Access 10: 66467-66480 (2022) - [c7]Florian Auer, Zhibek Abdykalykova, Dominik Müller, Frank Kramer:
Adaptation of HL7 FHIR for the Exchange of Patients' Gene Expression Profiles. ICIMTH 2022: 332-335 - [c6]Dominik Müller, Dennis Hartmann, Philip Meyer, Florian Auer, Iñaki Soto Rey, Frank Kramer:
MISeval: A Metric Library for Medical Image Segmentation Evaluation. MIE 2022: 33-37 - [c5]Florian Auer, Zhibek Abdykalykova, Dominik Müller, Frank Kramer:
Implementation of Gene Expression Profiles in the HL7 FHIR Standard. MIE 2022: 417-418 - [i12]Dominik Müller, Dennis Hartmann, Philip Meyer, Florian Auer, Iñaki Soto Rey, Frank Kramer:
MISeval: a Metric Library for Medical Image Segmentation Evaluation. CoRR abs/2201.09395 (2022) - [i11]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks. CoRR abs/2201.11440 (2022) - [i10]Florian Auer, Johann Frei, Dominik Müller, Frank Kramer:
Perspective on Code Submission and Automated Evaluation Platforms for University Teaching. CoRR abs/2201.13222 (2022) - [i9]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Towards a Guideline for Evaluation Metrics in Medical Image Segmentation. CoRR abs/2202.05273 (2022) - [i8]Simone Mayer, Dominik Müller, Frank Kramer:
Standardized Medical Image Classification across Medical Disciplines. CoRR abs/2210.11091 (2022) - [i7]Dennis Hartmann, Verena Schmid, Philip Meyer, Iñaki Soto Rey, Dominik Müller, Frank Kramer:
MISm: A Medical Image Segmentation Metric for Evaluation of weak labeled Data. CoRR abs/2210.13642 (2022) - 2021
- [j6]Dominik Müller, Frank Kramer:
MIScnn: a framework for medical image segmentation with convolutional neural networks and deep learning. BMC Medical Imaging 21(1): 12 (2021) - [j5]Michal Mazurek, Gloria Corti, Dominik Müller:
New Simulation Software Technologies at the LHCb Experiment at CERN. Comput. Informatics 40(4) (2021) - [c4]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Multi-Disease Detection in Retinal Imaging Based on Ensembling Heterogeneous Deep Learning Models. GMDS 2021: 23-31 - [c3]Florian Auer, Johann Frei, Dominik Müller, Frank Kramer:
Perspective on Code Submission and Automated Evaluation Platforms for University Teaching. MedInfo 2021: 912-916 - [c2]Philip Meyer, Dominik Müller, Iñaki Soto Rey, Frank Kramer:
COVID-19 Image Segmentation Based on Deep Learning and Ensemble Learning. MIE 2021: 518-519 - [i6]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models. CoRR abs/2103.14660 (2021) - [i5]Dennis Hartmann, Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Assessing the Role of Random Forests in Medical Image Segmentation. CoRR abs/2103.16492 (2021) - [i4]Pia Schneider, Dominik Müller, Frank Kramer:
Classification of Viral Pneumonia X-ray Images with the Aucmedi Framework. CoRR abs/2110.01017 (2021) - 2020
- [i3]Dominik Müller, Iñaki Soto Rey, Frank Kramer:
Automated Chest CT Image Segmentation of COVID-19 Lung Infection based on 3D U-Net. CoRR abs/2007.04774 (2020)
2010 – 2019
- 2019
- [j4]Dominik Müller, Claudia Czado:
Dependence modelling in ultra high dimensions with vine copulas and the Graphical Lasso. Comput. Stat. Data Anal. 137: 211-232 (2019) - [j3]Dominik Müller, Claudia Czado:
Selection of sparse vine copulas in high dimensions with the Lasso. Stat. Comput. 29(2): 269-287 (2019) - [i2]Dominik Müller, Frank Kramer:
MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning. CoRR abs/1910.09308 (2019) - 2016
- [j2]Gordon Elger, Dominik Müller, Alexander Hanß, Maximilian Schmid, E. Liu, Udo Karbowski, Robert Derix:
Transient thermal analysis for accelerated reliability testing of LEDs. Microelectron. Reliab. 64: 605-609 (2016) - 2015
- [j1]Akaki Mamageishvili, Matús Mihalák, Dominik Müller:
Tree Nash Equilibria in the Network Creation Game. Internet Math. 11(4-5): 472-486 (2015) - 2013
- [c1]Akaki Mamageishvili, Matús Mihalák, Dominik Müller:
Tree Nash Equilibria in the Network Creation Game. WAW 2013: 118-129 - [i1]Akaki Mamageishvili, Matús Mihalák, Dominik Müller:
Tree Nash Equilibria in the Network Creation Game. CoRR abs/1310.8245 (2013)
Coauthor Index
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last updated on 2024-10-23 21:23 CEST by the dblp team
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