| Accuracy of magnetic resonance imaging for local staging of prostate cancer: a diagnostic meta-analysis M de Rooij, EHJ Hamoen, JA Witjes, JO Barentsz, MM Rovers European urology 70 (2), 233-245, 2016 | 655 | 2016 |
| Prospective study of diagnostic accuracy comparing prostate cancer detection by transrectal ultrasound–guided biopsy versus magnetic resonance (MR) imaging with subsequent MR … MR Pokorny, M De Rooij, E Duncan, FH Schröder, R Parkinson, ... European urology 66 (1), 22-29, 2014 | 645 | 2014 |
| Accuracy of multiparametric MRI for prostate cancer detection: a meta-analysis M De Rooij, EHJ Hamoen, JJ Fütterer, JO Barentsz, MM Rovers American Journal of Roentgenology 202 (2), 343-351, 2014 | 564 | 2014 |
| Use of the prostate imaging reporting and data system (PI-RADS) for prostate cancer detection with multiparametric magnetic resonance imaging: a diagnostic meta-analysis EHJ Hamoen, M de Rooij, JA Witjes, JO Barentsz, MM Rovers European urology 67 (6), 1112-1121, 2015 | 393 | 2015 |
| Artificial intelligence in radiology: 100 commercially available products and their scientific evidence KG van Leeuwen, S Schalekamp, MJCM Rutten, B van Ginneken, ... European radiology 31, 3797-3804, 2021 | 240 | 2021 |
| Cost-effectiveness of magnetic resonance (MR) imaging and MR-guided targeted biopsy versus systematic transrectal ultrasound–guided biopsy in diagnosing prostate cancer: a … M De Rooij, S Crienen, JA Witjes, JO Barentsz, MM Rovers, JPC Grutters European urology 66 (3), 430-436, 2014 | 232 | 2014 |
| ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation … M de Rooij, B Israël, M Tummers, HU Ahmed, T Barrett, F Giganti, ... European radiology 30, 5404-5416, 2020 | 206 | 2020 |
| Prostate cancer aggressiveness: in vivo assessment of MR spectroscopy and diffusion-weighted imaging at 3 T T Kobus, PC Vos, T Hambrock, M De Rooij, CA Hulsbergen—Van de Kaa, ... Radiology 265 (2), 457-467, 2012 | 164 | 2012 |
| How does artificial intelligence in radiology improve efficiency and health outcomes? KG Van Leeuwen, M de Rooij, S Schalekamp, B van Ginneken, ... Pediatric Radiology, 1-7, 2022 | 115 | 2022 |
| Measuring health-related quality of life in men with prostate cancer: A systematic review of the most used questionnaires and their validity EHJ Hamoen, M De Rooij, JA Witjes, JO Barentsz, MM Rovers Urologic Oncology: Seminars and Original Investigations 33 (2), 69. e19-69. e28, 2015 | 90 | 2015 |
| Cost-effectiveness comparison of imaging-guided prostate biopsy techniques: systematic transrectal ultrasound, direct in-bore MRI, and image fusion W Venderink, TM Govers, M de Rooij, JJ Fütterer, JPM Sedelaar American Journal of Roentgenology 208 (5), 1058-1063, 2017 | 80 | 2017 |
| Deep learning–assisted prostate cancer detection on bi-parametric MRI: minimum training data size requirements and effect of prior knowledge M Hosseinzadeh, A Saha, P Brand, I Slootweg, M de Rooij, H Huisman European Radiology, 1-11, 2022 | 65 | 2022 |
| Elastic versus rigid image registration in magnetic resonance imaging–transrectal ultrasound fusion prostate biopsy: a systematic review and meta-analysis W Venderink, M de Rooij, JPM Sedelaar, HJ Huisman, JJ Fütterer European urology focus 4 (2), 219-227, 2018 | 64 | 2018 |
| Artificial intelligence based algorithms for prostate cancer classification and detection on magnetic resonance imaging: a narrative review JJ Twilt, KG van Leeuwen, HJ Huisman, JJ Fütterer, M de Rooij Diagnostics 11 (6), 959, 2021 | 63 | 2021 |
| Molecular and functional imaging for detection of lymph node metastases in prostate cancer A Fortuin, M De Rooij, P Zamecnik, U Haberkorn, J Barentsz International journal of molecular sciences 14 (7), 13842-13857, 2013 | 48 | 2013 |
| Molecular and functional imaging for detection of lymph node metastases in prostate cancer A Fortuin, M De Rooij, P Zamecnik, U Haberkorn, J Barentsz International journal of molecular sciences 14 (7), 13842-13857, 2013 | 48 | 2013 |
| Artificial intelligence and radiologists at prostate cancer detection in mri—the pi-cai challenge A Saha, J Bosma, J Twilt, B van Ginneken, D Yakar, M Elschot, J Veltman, ... Medical Imaging with Deep Learning, short paper track, 2023 | 45 | 2023 |
| Focus on the quality of prostate multiparametric magnetic resonance imaging: synopsis of the ESUR/ESUI recommendations on quality assessment and interpretation of images and … M de Rooij, B Israël, T Barrett, F Giganti, AR Padhani, V Panebianco, ... European Urology 78 (4), 483-485, 2020 | 33 | 2020 |
| Cost-effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke: an early health technology assessment KG van Leeuwen, FJA Meijer, S Schalekamp, MJCM Rutten, EJ van Dijk, ... Insights into Imaging 12, 1-9, 2021 | 29 | 2021 |
| Development and validation of a convolutional neural network for automated detection of scaphoid fractures on conventional radiographs N Hendrix, E Scholten, B Vernhout, S Bruijnen, B Maresch, M de Jong, ... Radiology: Artificial Intelligence 3 (4), e200260, 2021 | 28 | 2021 |
