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Alexander Tack
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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
3142019
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
214*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
1152018
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
512017
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
352021
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
212019
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
132021
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
82021
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
82017
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
42020
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
12021
Machine learning-based assessment of multiple anatomical structures in medical image data for diagnosis and prediction of knee osteoarthritis
A Tack
2024
Unsupervised detection of disturbances in 2D radiographs
E Moritz, L Estacio, H Lamecker, R Mora, A Tack, E Castro, S Zachow
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
Gruppenweise Registrierung zur robusten Bewegungsfeldschätzung in artefaktbehafteten 4D-CT-Bilddaten
A Tack
2015
Bewegungsfeldschätzung in artefaktbehafteten 4D-CT-Bilddaten: Vergleich von paar-und gruppenweiser Registrierung
A Tack, Y Kobayashi, T Gauer, A Schlaefer, R Werner
Springer, 2015
2015
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