| 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 | 98 | 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 | 57 | 2019 |
| 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 | 37 | 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 Muehlberg, JW Holch, V Heinemann, T Huber, J Moltz, S Maurus, ... European radiology 31, 834-846, 2021 | 36 | 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), 1-15, 2020 | 23 | 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 | 22 | 2021 |
| 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 | 19 | 2022 |
| 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 | 19 | 2017 |
| 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 | 15 | 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 | 15 | 2018 |
| Digital staining in optical microscopy using deep learning-a review L Kreiss, S Jiang, X Li, S Xu, KC Zhou, KC Lee, A Mühlberg, K Kim, ... PhotoniX 4 (1), 34, 2023 | 11 | 2023 |
| 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 | 9 | 2021 |
| 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 | 8 | 2022 |
| 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 | 7 | 2020 |
| 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 | 6 | 2023 |
| Label‐free analysis of inflammatory tissue remodeling in murine lung tissue based on multiphoton microscopy, Raman spectroscopy and machine learning L Kreiss, I Ganzleben, A Mühlberg, P Ritter, D Schneidereit, C Becker, ... Journal of Biophotonics 15 (9), e202200073, 2022 | 4 | 2022 |
| Method for determining at least one object feature of an object A Muehlberg, R Kaergel, M Wels, M Suehling US Patent 10,922,813, 2021 | 4 | 2021 |
| 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 | 3 | 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 | 3 | 2019 |
| Muskelbildgebung bei Sarkopenie K Engelke, A Grimm, A Mühlberg, A Friedberger, O Chaudry, O Museyko Osteologie 26 (01), 18-24, 2017 | 3 | 2017 |
Alexander KatzmannResearch Scientist @ Siemens Healthineers在 siemens-healthineers.com 的电子邮件经过验证
