| Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteoarthritic knee pain J Kemnitz, CF Baumgartner, F Eckstein, A Chaudhari, A Ruhdorfer, ... Magnetic Resonance Materials in Physics, Biology and Medicine 33, 483-493, 2020 | 48 | 2020 |
| The role of thigh muscle and adipose tissue in knee osteoarthritis progression in women: data from the Osteoarthritis Initiative J Kemnitz, W Wirth, F Eckstein, AG Culvenor Osteoarthritis and cartilage 26 (9), 1190-1195, 2018 | 35 | 2018 |
| Industrial federated learning–requirements and system design T Hiessl, D Schall, J Kemnitz, S Schulte International Conference on Practical Applications of Agents and Multi-Agent …, 2020 | 34 | 2020 |
| Validation of an active shape model-based semi-automated segmentation algorithm for the analysis of thigh muscle and adipose tissue cross-sectional areas J Kemnitz, F Eckstein, AG Culvenor, A Ruhdorfer, T Dannhauer, ... Magnetic Resonance Materials in Physics, Biology and Medicine 30, 489-503, 2017 | 32 | 2017 |
| Moderate physical activity and prevention of cartilage loss in people with knee osteoarthritis: data from the osteoarthritis initiative A Bricca, W Wirth, CB Juhl, J Kemnitz, DJ Hunter, CK Kwoh, F Eckstein, ... Arthritis Care & Research 71 (2), 218-226, 2019 | 29 | 2019 |
| Longitudinal change in thigh muscle strength prior to and concurrent with symptomatic and radiographic knee osteoarthritis progression: data from the Osteoarthritis Initiative J Kemnitz, W Wirth, F Eckstein, A Ruhdorfer, AG Culvenor Osteoarthritis and Cartilage 25 (10), 1633-1640, 2017 | 27 | 2017 |
| Accuracy and longitudinal reproducibility of quantitative femorotibial cartilage measures derived from automated U-Net-based segmentation of two different MRI contrasts: data … W Wirth, F Eckstein, J Kemnitz, CF Baumgartner, E Konukoglu, D Fuerst, ... Magnetic Resonance Materials in Physics, Biology and Medicine 34, 337-354, 2021 | 25 | 2021 |
| Mesenchymal iron deposition is associated with adverse long‐term outcome in non‐alcoholic fatty liver disease SK Eder, A Feldman, G Strebinger, J Kemnitz, S Zandanell, D Niederseer, ... Liver International 40 (8), 1872-1882, 2020 | 24 | 2020 |
| Cohort-based Federated Learning Services for Industrial Collaboration on the Edge T Hiessl, SR Lakani, J Kemnitz, D Schall, S Stefan TechRxiv, 2021 | 23 | 2021 |
| Evaluation of hyperparameter-optimization approaches in an industrial federated learning system S Holly, T Hiessl, SR Lakani, D Schall, C Heitzinger, J Kemnitz Data Science–Analytics and Applications: Proceedings of the 4th …, 2022 | 16 | 2022 |
| Detection of Differences in Longitudinal Cartilage Thickness Loss Using a Deep‐Learning Automated Segmentation Algorithm: Data From the Foundation for the National Institutes … F Eckstein, AS Chaudhari, D Fuerst, M Gaisberger, J Kemnitz, ... Arthritis Care & Research 74 (6), 929-936, 2022 | 10 | 2022 |
| Validation of a 3D thigh muscle and adipose tissue segmentation method using statistical shape models J Kemnitz, F Eckstein, AG Culvenor, A Ruhdorfer, T Dannhauer, ... Osteoarthritis and Cartilage 26, S457-S458, 2018 | 9 | 2018 |
| Combining heterogeneously labeled datasets for training segmentation networks J Kemnitz, CF Baumgartner, W Wirth, F Eckstein, SK Eder, E Konukoglu Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018 …, 2018 | 8 | 2018 |
| A Deep Learning Automated Segmentation Algorithm Accurately Detects Differences in Longitudinal Cartilage Thickness Loss–Data from the FNIH Biomarkers Study of the … F Eckstein, AS Chaudhari, D Fuerst, M Gaisberger, J Kemnitz, ... Arthritis Care & Research, 2020 | 7 | 2020 |
| Towards robust and transferable iiot sensor based anomaly classification using artificial intelligence J Kemnitz, T Bierweiler, H Grieb, S von Dosky, D Schall Data Science–Analytics and Applications: Proceedings of the 4th …, 2022 | 5 | 2022 |
| Brief Report: Loss of Muscle Strength Prior to Knee Replacement: A Question of Anatomic Cross‐Sectional Area or Specific Strength? AG Culvenor, FC Hamler, J Kemnitz, W Wirth, F Eckstein Arthritis & Rheumatology 70 (2), 222-229, 2018 | 5 | 2018 |
| Minimal-Configuration Anomaly Detection for IIoT Sensors: A Systematic Analysis of Deep Learning Approaches C Heistracher, A Jalali, A Suendermann, S Meixner, D Schall, B Haslhofer, ... Data Science–Analytics and Applications: Proceedings of the 4th …, 2022 | 4 | 2022 |
| Muscle function tests as supportive outcome measures for performance-based and self-reported physical function in patients with knee osteoarthritis: exploratory analysis of … PM Holm, J Kemnitz, T Bandholm, M Wernbom, HM Schrøder, ST Skou The Journal of Strength & Conditioning Research, 2022 | 4 | 2022 |
| Local MRI-based measures of thigh adipose tissue derived from fully automated deep convolutional neural network-based segmentation show a comparable responsiveness to … J Kemnitz, E Steidle-Kloc, W Wirth, D Fuerst, A Wisser, SK Eder, ... Annals of Anatomy-Anatomischer Anzeiger 240, 151866, 2022 | 3 | 2022 |
| Transfer learning strategies for anomaly detection in iot vibration data C Heistracher, A Jalali, I Strobl, A Suendermann, S Meixner, S Holly, ... IECON 2021–47th Annual Conference of the IEEE Industrial Electronics Society …, 2021 | 3 | 2021 |
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