| Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative F Ambellan, A Tack, M Ehlke, S Zachow Medical image analysis 52, 109-118, 2019 | 340 | 2019 |
| VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images A Sekuboyina, ME Husseini, A Bayat, M Löffler, H Liebl, H Li, G Tetteh, ... Medical image analysis 73, 102166, 2021 | 244* | 2021 |
| Knee menisci segmentation using convolutional neural networks: data from the osteoarthritis initiative A Tack, A Mukhopadhyay, S Zachow Osteoarthritis and cartilage 26 (5), 680-688, 2018 | 119 | 2018 |
| Shape-aware surface reconstruction from sparse 3D point-clouds F Bernard, L Salamanca, J Thunberg, A Tack, D Jentsch, H Lamecker, ... Medical image analysis 38, 77-89, 2017 | 54 | 2017 |
| Fully automated assessment of knee alignment from full-leg x-rays employing a “yolov4 and resnet landmark regression algorithm”(yarla): Data from the osteoarthritis initiative A Tack, B Preim, S Zachow Computer Methods and Programs in Biomedicine 205, 106080, 2021 | 40 | 2021 |
| Accurate automated volumetry of cartilage of the knee using convolutional neural networks: data from the osteoarthritis initiative A Tack, S Zachow 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 40-43, 2019 | 22 | 2019 |
| A multi-task deep learning method for detection of meniscal tears in MRI data from the osteoarthritis initiative database A Tack, A Shestakov, D Lüdke, S Zachow Frontiers in Bioengineering and Biotechnology 9, 747217, 2021 | 14 | 2021 |
| Towards novel osteoarthritis biomarkers: Multi-criteria evaluation of 46,996 segmented knee MRI data from the Osteoarthritis Initiative A Tack, F Ambellan, S Zachow PloS one 16 (10), e0258855, 2021 | 10 | 2021 |
| Validation of three-dimensional models of the distal femur created from surgical navigation point cloud data for intraoperative and postoperative analysis of total knee … DAJ Wilson, C Anglin, F Ambellan, CM Grewe, A Tack, H Lamecker, ... International Journal of Computer Assisted Radiology and Surgery 12, 2097-2105, 2017 | 8 | 2017 |
| LE Court, Z. Huang, C. He, L A Sekuboyina, ME Husseini, A Bayat, M Löffler, H Liebl, H Li, G Tetteh, ... W. Wang, SH Ling, LD Huynh, N. Boutry, R. Jakubicek, J. Chmelik, S. Mulay, M …, 2020 | 5 | 2020 |
| Unsupervised detection of disturbances in 2D radiographs L Estacio, M Ehlke, A Tack, E Castro, H Lamecker, R Mora, S Zachow 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 367-370, 2021 | 1 | 2021 |
| Integrating Radiomics and Neural Networks for Knee Osteoarthritis Incidence Prediction S Li, P Cao, J Li, T Chen, P Luo, G Ruan, Y Zhang, X Wang, W Han, Z Zhu, ... Arthritis & Rheumatology, 2024 | | 2024 |
| Machine learning-based assessment of multiple anatomical structures in medical image data for diagnosis and prediction of knee osteoarthritis A Tack | | 2024 |
| Temperature regime influences accessions and effectiveness of germination promoters in the high-Andean crop maca E Castro, M Ehlke, L Estacio, H Lamecker, R Mora, A Tack, S Zachow John Wiley and Sons Inc, 2021 | | 2021 |
| Unsupervised detection of disturbances in 2D radiographs RN Camacho Chávez IEEE Computer Society, 2021 | | 2021 |
| Learning Appearance From Few Examples for Model-Based Segmentation T Amiranashvili, A Tack, H Lamecker, B Menze, S Zachow | | 2020 |
| Knee Menisci Segmentation using Convolutional Neural Networks: Data from the Osteoarthritis Initiative (Supplementary Material) A Tack, A Mukhopadhyay, S Zachow | | 2018 |
| Evaluating two methods for Geometry Reconstruction from Sparse Surgical Navigation Data F Ambellan, A Tack, D Wilson, C Anglin, H Lamecker, S Zachow | | 2017 |
| Field of Movement Estimation in artifacts affected 4D-CT-Image Data: Comparison of pair-and group-wise Registration A Tack, Y Kobayashi, T Gauer, A Schlaefer, R Werner STRAHLENTHERAPIE UND ONKOLOGIE 191, S65-S65, 2015 | | 2015 |
| Groupwise Registration for Robust Motion Field Estimation in Artifact-Affected 4D CT Images A Tack, Y Kobayashi, T Gauer, A Schlaefer, R Werner ICART: Imaging and Computer Assistance in Radiation Therapy: A workshop held …, 2015 | | 2015 |
Stefan ZachowZuse Institute Berlin (ZIB)在 zib.de 的电子邮件经过验证
Stefan ZachowZuse Institute Berlin (ZIB)在 zib.de 的电子邮件经过验证
Felix AmbellanZuse Institute Berlin | FU Berlin在 zib.de 的电子邮件经过验证
Hans Lamecker1000shapes GmbH在 1000shapes.com 的电子邮件经过验证