| A survey on deep learning in medical image analysis G Litjens, T Kooi, BE Bejnordi, AAA Setio, F Ciompi, M Ghafoorian, ... Medical image analysis 42, 60-88, 2017 | 17530 | 2017 |
| Pulmonary nodule detection in CT images: false positive reduction using multi-view convolutional networks AAA Setio, F Ciompi, G Litjens, P Gerke, C Jacobs, SJ Van Riel, ... IEEE transactions on medical imaging 35 (5), 1160-1169, 2016 | 1537 | 2016 |
| Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis G Litjens, CI Sánchez, N Timofeeva, M Hermsen, I Nagtegaal, I Kovacs, ... Scientific reports 6 (1), 26286, 2016 | 1323 | 2016 |
| Large scale deep learning for computer aided detection of mammographic lesions T Kooi, G Litjens, B Van Ginneken, A Gubern-Mérida, CI Sánchez, ... Medical image analysis 35, 303-312, 2017 | 1230 | 2017 |
| Retinopathy online challenge: automatic detection of microaneurysms in digital color fundus photographs M Niemeijer, B Van Ginneken, MJ Cree, A Mizutani, G Quellec, ... IEEE transactions on medical imaging 29 (1), 185-195, 2009 | 701 | 2009 |
| Metrics reloaded: recommendations for image analysis validation L Maier-Hein, A Reinke, P Godau, MD Tizabi, F Buettner, E Christodoulou, ... Nature methods 21 (2), 195-212, 2024 | 607* | 2024 |
| Fast convolutional neural network training using selective data sampling: Application to hemorrhage detection in color fundus images MJJP Van Grinsven, B van Ginneken, CB Hoyng, T Theelen, CI Sánchez IEEE transactions on medical imaging 35 (5), 1273-1284, 2016 | 567 | 2016 |
| Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy D Abásolo, R Hornero, P Espino, J Poza, CI Sánchez, R de la Rosa Clinical neurophysiology 116 (8), 1826-1834, 2005 | 336 | 2005 |
| Location sensitive deep convolutional neural networks for segmentation of white matter hyperintensities M Ghafoorian, N Karssemeijer, T Heskes, IWM van Uden, CI Sanchez, ... Scientific Reports 7 (1), 5110, 2017 | 324 | 2017 |
| RETOUCH: The retinal OCT fluid detection and segmentation benchmark and challenge H Bogunović, F Venhuizen, S Klimscha, S Apostolopoulos, ... IEEE transactions on medical imaging 38 (8), 1858-1874, 2019 | 311 | 2019 |
| Automatic glaucoma classification using color fundus images based on convolutional neural networks and transfer learning JJ Gómez-Valverde, A Antón, G Fatti, B Liefers, A Herranz, A Santos, ... Biomedical optics express 10 (2), 892-913, 2019 | 291 | 2019 |
| Common limitations of image processing metrics: A picture story A Reinke, MD Tizabi, CH Sudre, M Eisenmann, T Rädsch, M Baumgartner, ... arXiv preprint arXiv:2104.05642, 2021 | 263 | 2021 |
| Retinal image analysis based on mixture models to detect hard exudates CI Sánchez, M García, A Mayo, MI López, R Hornero Medical Image Analysis 13 (4), 650-658, 2009 | 254 | 2009 |
| Neural network based detection of hard exudates in retinal images M García, CI Sánchez, MI López, D Abásolo, R Hornero Computer Methods and programs in biomedicine 93 (1), 9-19, 2009 | 246 | 2009 |
| Observer variability for classification of pulmonary nodules on low-dose CT images and its effect on nodule management SJ Van Riel, CI Sánchez, AA Bankier, DP Naidich, J Verschakelen, ... Radiology 277 (3), 863-871, 2015 | 230 | 2015 |
| A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis CI Sanchez, R Hornero, MI Lopez, M Aboy, J Poza, D Abasolo Medical engineering & physics 30 (3), 350-357, 2008 | 220 | 2008 |
| Understanding metric-related pitfalls in image analysis validation A Reinke, MD Tizabi, M Baumgartner, M Eisenmann, D Heckmann-Nötzel, ... Nature methods 21 (2), 182-194, 2024 | 196 | 2024 |
| An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information J Melendez, CI Sánchez, RHHM Philipsen, P Maduskar, R Dawson, ... Scientific reports 6 (1), 25265, 2016 | 171 | 2016 |
| Deep learning approach for the detection and quantification of intraretinal cystoid fluid in multivendor optical coherence tomography FG Venhuizen, B Van Ginneken, B Liefers, F Van Asten, V Schreur, ... Biomedical optics express 9 (4), 1545-1569, 2018 | 170 | 2018 |
| Adversarial attack vulnerability of medical image analysis systems: Unexplored factors G Bortsova, C González-Gonzalo, SC Wetstein, F Dubost, I Katramados, ... Medical Image Analysis 73, 102141, 2021 | 164 | 2021 |
Bram van GinnekenProfessor of Medical Image Analysis, Radboud UniversityVerified email at radboudumc.nl
