Image biomarker standardisation initiative A Zwanenburg, S Leger, M Vallières, S Löck arXiv preprint arXiv:1612.07003, 2016 | 2816* | 2016 |
A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling S Leger, A Zwanenburg, K Pilz, F Lohaus, A Linge, K Zöphel, J Kotzerke, ... Scientific reports 7 (1), 13206, 2017 | 228 | 2017 |
Assessing robustness of radiomic features by image perturbation A Zwanenburg, S Leger, L Agolli, K Pilz, EGC Troost, C Richter, S Löck Scientific reports 9 (1), 614, 2019 | 202 | 2019 |
Image biomarker standardisation initiative-feature definitions A Zwanenburg, S Leger, M Vallières, S Löck arXiv preprint arXiv:1612.07003 10, 2016 | 125 | 2016 |
Spatial distribution of FMISO in head and neck squamous cell carcinomas during radio-chemotherapy and its correlation to pattern of failure S Zschaeck, R Haase, N Abolmaali, R Perrin, K Stützer, S Appold, ... Acta Oncologica 54 (9), 1355-1363, 2015 | 88* | 2015 |
2018 robotic scene segmentation challenge M Allan, S Kondo, S Bodenstedt, S Leger, R Kadkhodamohammadi, ... arXiv preprint arXiv:2001.11190, 2020 | 70 | 2020 |
Comparative validation of multi-instance instrument segmentation in endoscopy: results of the ROBUST-MIS 2019 challenge T Roß, A Reinke, PM Full, M Wagner, H Kenngott, M Apitz, H Hempe, ... Medical image analysis 70, 101920, 2021 | 65 | 2021 |
Development and validation of a gene signature for patients with head and neck carcinomas treated by postoperative radio (chemo) therapy S Schmidt, A Linge, A Zwanenburg, S Leger, F Lohaus, C Krenn, ... Clinical Cancer Research 24 (6), 1364-1374, 2018 | 54 | 2018 |
CT imaging during treatment improves radiomic models for patients with locally advanced head and neck cancer S Leger, A Zwanenburg, K Pilz, S Zschaeck, K Zöphel, J Kotzerke, ... Radiotherapy and Oncology 130, 10-17, 2019 | 52 | 2019 |
Image biomarker standardisation initiative. arXiv 2016 A Zwanenburg, S Leger, M Vallières, S Löck arXiv preprint arXiv:1612.07003, 0 | 51 | |
Non-rigid volume to surface registration using a data-driven biomechanical model M Pfeiffer, C Riediger, S Leger, JP Kühn, D Seppelt, RT Hoffmann, J Weitz, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 40 | 2020 |
2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma S Starke, S Leger, A Zwanenburg, K Leger, F Lohaus, A Linge, ... Scientific reports 10 (1), 15625, 2020 | 37 | 2020 |
Robust medical instrument segmentation challenge 2019 T Ross, A Reinke, PM Full, M Wagner, H Kenngott, M Apitz, H Hempe, ... arXiv preprint arXiv:2003.10299, 2020 | 33 | 2020 |
Comprehensive analysis of tumour sub-volumes for radiomic risk modelling in locally advanced HNSCC S Leger, A Zwanenburg, K Leger, F Lohaus, A Linge, A Schreiber, ... Cancers 12 (10), 3047, 2020 | 22 | 2020 |
Image biomarker standardisation initiative-feature definitions. arXiv 2016 A Zwanenburg, S Leger, M Vallières, S Löck arXiv preprint arXiv:1612.07003, 2016 | 16 | 2016 |
Radiomics-based tumor phenotype determination based on medical imaging and tumor microenvironment in a preclinical setting J Müller, S Leger, A Zwanenburg, T Suckert, A Lühr, E Beyreuther, ... Radiotherapy and Oncology 169, 96-104, 2022 | 15 | 2022 |
Artificial Intelligence for context-aware surgical guidance in complex robot-assisted oncological procedures: An exploratory feasibility study FR Kolbinger, S Bodenstedt, M Carstens, S Leger, S Krell, FM Rinner, ... European Journal of Surgical Oncology, 106996, 2023 | 14 | 2023 |
The image-based preoperative fistula risk score (preFRS) predicts postoperative pancreatic fistula in patients undergoing pancreatic head resection FR Kolbinger, J Lambrecht, S Leger, T Ittermann, S Speidel, J Weitz, ... Scientific Reports 12 (1), 4064, 2022 | 13 | 2022 |
FDG uptake in normal tissues assessed by PET during treatment has prognostic value for treatment results in head and neck squamous cell carcinomas undergoing radiochemotherapy S Zschaeck, S Löck, S Leger, R Haase, A Bandurska-Luque, S Appold, ... Radiotherapy and Oncology 122 (3), 437-444, 2017 | 13 | 2017 |
Physical correction model for automatic correction of intensity non-uniformity in magnetic resonance imaging S Leger, S Löck, V Hietschold, R Haase, HJ Böhme, N Abolmaali Physics and Imaging in Radiation Oncology 4, 32-38, 2017 | 12 | 2017 |