| CT image segmentation methods for bone used in medical additive manufacturing M Van Eijnatten, R van Dijk, J Dobbe, G Streekstra, J Koivisto, J Wolff Medical engineering & physics 51, 6-16, 2018 | 206 | 2018 |
| Using 3D printing techniques to create an anthropomorphic thorax phantom for medical imaging purposes C Hazelaar, M van Eijnatten, M Dahele, J Wolff, T Forouzanfar, B Slotman, ... Medical physics 45 (1), 92-100, 2018 | 152 | 2018 |
| CT image segmentation of bone for medical additive manufacturing using a convolutional neural network J Minnema, M van Eijnatten, W Kouw, F Diblen, A Mendrik, J Wolff Computers in biology and medicine 103, 130-139, 2018 | 140 | 2018 |
| The impact of manual threshold selection in medical additive manufacturing M Van Eijnatten, J Koivisto, K Karhu, T Forouzanfar, J Wolff International journal of computer assisted radiology and surgery 12, 607-615, 2017 | 84 | 2017 |
| Segmentation of dental cone‐beam CT scans affected by metal artifacts using a mixed‐scale dense convolutional neural network J Minnema, M van Eijnatten, AA Hendriksen, N Liberton, DM Pelt, ... Medical physics 46 (11), 5027-5035, 2019 | 80 | 2019 |
| Virtual forensic anthropology: the accuracy of osteometric analysis of 3D bone models derived from clinical computed tomography (CT) scans KL Colman, HH De Boer, JGG Dobbe, NPTJ Liberton, KE Stull, ... Forensic science international 304, 109963, 2019 | 65 | 2019 |
| Effective radiation dose in the wrist resulting from a radiographic device, two CBCT devices and one MSCT device: a comparative study J Koivisto, M Van Eijnatten, T Kiljunen, XQ Shi, J Wolff Radiation protection dosimetry 179 (1), 58-68, 2018 | 62 | 2018 |
| A novel method of orbital floor reconstruction using virtual planning, 3-dimensional printing, and autologous bone M Vehmeijer, M van Eijnatten, N Liberton, J Wolff Journal of Oral and Maxillofacial Surgery 74 (8), 1608-1612, 2016 | 59 | 2016 |
| A cone-beam X-ray computed tomography data collection designed for machine learning H Der Sarkissian, F Lucka, M van Eijnatten, G Colacicco, SB Coban, ... Scientific data 6 (1), 215, 2019 | 54 | 2019 |
| Quantitative comparison of deep learning-based image reconstruction methods for low-dose and sparse-angle CT applications J Leuschner, M Schmidt, PS Ganguly, V Andriiashen, SB Coban, ... Journal of Imaging 7 (3), 44, 2021 | 49 | 2021 |
| Accuracy of MDCT and CBCT in three-dimensional evaluation of the oropharynx morphology H Chen, M Van Eijnatten, G Aarab, T Forouzanfar, J De Lange, ... European journal of orthodontics 40 (1), 58-64, 2018 | 41 | 2018 |
| Influence of CT parameters on STL model accuracy M Van Eijnatten, FH Berger, P De Graaf, J Koivisto, T Forouzanfar, J Wolff Rapid Prototyping Journal 23 (4), 678-685, 2017 | 38 | 2017 |
| Reliability and accuracy of three imaging software packages used for 3D analysis of the upper airway on cone beam computed tomography images H Chen, M Van Eijnatten, J Wolff, J De Lange, PF Van Der Stelt, ... Dentomaxillofacial radiology 46 (6), 20170043, 2017 | 36 | 2017 |
| Comparison of cardiac time intervals between echocardiography and impedance cardiography at various heart rates MAJM Van Eijnatten, MJ Van Rijssel, RJA Peters, RM Verdaasdonk, ... Journal of electrical bioimpedance 5 (1), 2-8, 2014 | 34 | 2014 |
| A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery J Minnema, A Ernst, M van Eijnatten, R Pauwels, T Forouzanfar, ... Dentomaxillofacial Radiology 51 (7), 20210437, 2022 | 32 | 2022 |
| MRI and additive manufacturing of nasal alar constructs for patient-specific reconstruction DO Visscher, M Van Eijnatten, NPTJ Liberton, J Wolff, MBM Hofman, ... Scientific reports 7 (1), 10021, 2017 | 26 | 2017 |
| The accuracy of ultrashort echo time MRI sequences for medical additive manufacturing M van Eijnatten, EJ Rijkhorst, M Hofman, T Forouzanfar, J Wolff Dentomaxillofacial Radiology 45 (5), 20150424, 2016 | 26 | 2016 |
| Comparison of convolutional neural network training strategies for cone-beam CT image segmentation J Minnema, J Wolff, J Koivisto, F Lucka, KJ Batenburg, T Forouzanfar, ... Computer Methods and Programs in Biomedicine 207, 106192, 2021 | 25 | 2021 |
| 3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning M van Eijnatten, L Rundo, KJ Batenburg, F Lucka, E Beddowes, C Caldas, ... Computer Methods and Programs in Biomedicine 208, 106261, 2021 | 17 | 2021 |
| Sophia Bethany Coban, and Kees Joost Batenburg H Der Sarkissian, F Lucka, M van Eijnatten, G Colacicco A conebeam x-ray computed tomography data collection designed for machine …, 2019 | 16 | 2019 |
