Alexander Katzmann
Alexander Katzmann
Research Scientist @ Siemens Healthineers
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Zitiert von
Zitiert von
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
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), 1103, 2020
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
Mobile assessment tools
K Henke, K Debes, HD Wuttke, A Katzmann
International Journal of Recent Contributions from Engineering, Science & IT …, 2014
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 Mühlberg, M Sühling, D Nörenberg, S Maurus, JW Holch, ...
Predictive Intelligence in Medicine: Second International Workshop, PRIME …, 2019
Providing a classification explanation and a generative function
A Katzmann, S Ahmad, M Suehling, A Muehlberg
US Patent App. 17/476,630, 2022
TumorEncode-Deep Convolutional Autoencoder for Computed Tomography Tumor Treatment Assessment
A Katzmann, A Mühlberg, M Sühling, D Nörenberg, JW Holch, HM Groß
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
Hybrid Rotation Invariant Networks for small sample size Deep Learning
A Katzmann, MS Seibel, A Mühlberg, M Sühling, D Nörenberg, S Maurus, ...
Method and data processing system for providing a prediction of a medical target variable
A Muehlberg, A Katzmann, F Durlak, M Suehling
US Patent 11,626,203, 2023
Method for obtaining at least one feature of interest
A Muehlberg, R Kaergel, A Katzmann, M Suehling
US Patent 11,341,632, 2022
Method and data processing system for providing radiomics-related information
A Muehlberg, O Taubmann, A Katzmann, F Durlak, M Wels, F Lades, ...
US Patent App. 17/462,140, 2022
Computer-implemented method for parametrizing a function for evaluating a medical image dataset
A Muehlberg, O Taubmann, A Katzmann, F Denzinger, F Lades, ...
US Patent App. 17/382,588, 2022
Deep learning for clinical decision support in oncology
A Katzmann
Method for obtaining disease-related clinical information
A Muehlberg, O Taubmann, A Katzmann, M Suehling
US Patent App. 17/109,332, 2021
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