Alexander Mühlberg
Alexander Mühlberg
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Multiparametric MRI for prostate cancer characterization: Combined use of radiomics model with PI-RADS and clinical parameters
P Woźnicki, N Westhoff, T Huber, P Riffel, MF Froelich, E Gresser, ...
Cancers 12 (7), 1767, 2020
General purpose radiomics for multi-modal clinical research
MG Wels, F Lades, A Muehlberg, M Suehling
Medical imaging 2019: Computer-aided diagnosis 10950, 1047-1054, 2019
The relevance of CT-based geometric and radiomics analysis of whole liver tumor burden to predict survival of patients with metastatic colorectal cancer
A Mühlberg, JW Holch, V Heinemann, T Huber, J Moltz, S Maurus, ...
European Radiology 31, 834-846, 2021
Three-dimensional distribution of muscle and adipose tissue of the thigh at CT: Association with acute hip fracture
A Muehlberg, O Museyko, V Bousson, P Pottecher, JD Laredo, K Engelke
Radiology 290 (2), 426-434, 2019
The Technome - A Predictive Internal Calibration Approach for Quantitative imaging Biomarker Research
A Mühlberg, A Katzmann, V Heinemann, R Kärgel, M Wels, O Taubmann, ...
Scientific Reports 10 (1), 1-15, 2020
A reproducible semi-automatic method to quantify the muscle-lipid distribution in clinical 3D CT images of the thigh
A Muehlberg, O Museyko, JD Laredo, K Engelke
PloS one 12 (4), e0175174, 2017
Explaining clinical decision support systems in medical imaging using cycle-consistent activation maximization
A Katzmann, O Taubmann, S Ahmad, A Mühlberg, M Sühling, HM Groß
Neurocomputing 458, 141-156, 2021
Predicting lesion growth and patient survival in colorectal cancer patients using deep neural networks
A Katzmann, A Muehlberg, M Sühling, D Noerenberg, JW Holch, ...
Medical Imaging with Deep Learning, 2018
Radiomics features of the spleen as surrogates for ct-based lymphoma diagnosis and subtype differentiation
JS Enke, JH Moltz, M D'Anastasi, WG Kunz, C Schmidt, S Maurus, ...
Cancers 14 (3), 713, 2022
Methods for generating synthetic training data and for training deep learning algorithms for tumor lesion characterization, method and system for tumor lesion characterization …
A Katzmann, L Kratzke, A Muehlberg, M Suehling
US Patent 11,138,731, 2021
Quantitative imaging biomarkers of the whole liver tumor burden improve survival prediction in metastatic pancreatic cancer
L Gebauer, JH Moltz, A Mühlberg, JW Holch, T Huber, J Enke, N Jäger, ...
Cancers 13 (22), 5732, 2021
Deep random forests for small sample size prediction with medical imaging data
A Katzmann, A Muehlberg, M Suehling, D Nörenberg, JW Holch, ...
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1543-1547, 2020
Unraveling the interplay of image formation, data representation and learning in CT‐based COPD phenotyping automation: The need for a meta‐strategy
A Mühlberg, R Kärgel, A Katzmann, F Durlak, PE Allard, JB Faivre, ...
Medical Physics 48 (9), 5179-5191, 2021
Computed Tomography Image-Based Deep Survival Regression for Metastatic Colorectal Cancer Using a Non-proportional Hazards Model
A Katzmann, A Muehlberg, M Suehling, D Noerenberg, S Maurus, ...
International Workshop on PRedictive Intelligence In MEdicine, 73-80, 2019
Muskelbildgebung bei Sarkopenie
K Engelke, A Grimm, A Mühlberg, A Friedberger, O Chaudry, O Museyko
Osteologie 26 (01), 18-24, 2017
How scan parameter choice affects deep learning-based coronary artery disease assessment from computed tomography
F Denzinger, M Wels, K Breininger, O Taubmann, A Mühlberg, ...
Scientific Reports 13 (1), 2563, 2023
Myofibrillar Lattice Remodeling Is a Structural Cytoskeletal Predictor of Diaphragm Muscle Weakness in a Fibrotic mdx (mdx Cmah−/−) Model
P Ritter, S Nübler, A Buttgereit, LR Smith, A Mühlberg, J Bauer, M Michael, ...
International journal of molecular sciences 23 (18), 10841, 2022
DeepTechnome: Mitigating Unknown Bias in Deep Learning Based Assessment of CT Images
S Langer, O Taubmann, F Denzinger, A Maier, A Mühlberg
arXiv preprint arXiv:2205.13297, 2022
Providing a classification explanation and a generative function
A Katzmann, S Ahmad, M Suehling, A Muehlberg
US Patent App. 17/476,630, 2022
Hybrid Rotation Invariant Networks for small sample size Deep Learning
A Katzmann, MS Seibel, A Muehlberg, M Suehling, D Noerenberg, ...
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