Publications

Papers in international journals

  1. N. Lessmann, C. Sánchez, L. Beenen, L. Boulogne, M. Brink, E. Calli, J. Charbonnier, T. Dofferhoff, W. van Everdingen, P. Gerke, B. Geurts, H. Gietema, M. Groeneveld, L. van Harten, N. Hendrix, W. Hendrix, H. Huisman, I. Isgum, C. Jacobs, R. Kluge, M. Kok, J. Krdzalic, B. Lassen-Schmidt, K. van Leeuwen, J. Meakin, M. Overkamp, T. van Rees Vellinga, E. van Rikxoort, R. Samperna, C. Schaefer-Prokop, S. Schalekamp, E. Scholten, C. Sital, L. Stöger, J. Teuwen, K. Vaidhya Venkadesh, C. de Vente, M. Vermaat, W. Xie, B. de Wilde, M. Prokop and B. van Ginneken, "Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence", Radiology, 2021;298(1):E18-E28. Abstract DOI PMID Algorithm
  2. S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Stacked Bidirectional Convolutional LSTMs for Deriving 3D Non-contrast CT from Spatiotemporal 4D CT", IEEE Transactions on Medical Imaging, 2020;39(4):985-996. Abstract DOI PMID Cited by ~4
  3. M. Meijs, S. Pegge, M. Vos, A. Patel, S. van de Leemput, K. Koschmieder, M. Prokop, F. Meijer and R. Manniesing, "Cerebral Artery and Vein Segmentation in Fourdimensional CT Angiography Using Convolutional Neural Networks", Radiology: Artificial Intelligence, 2020;2(4):e190178. Abstract DOI
  4. S. van de Leemput, J. Teuwen, B. van Ginneken and R. Manniesing, "MemCNN: A Python/PyTorch package for creating memory-efficient invertible neural networks", JOSS, 2019;4(39):1576. Abstract DOI Cited by ~2 Code
  5. A. Patel, S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Image Level Training and Prediction: Intracranial Hemorrhage Identification in 3D Non-Contrast CT", IEEE Access, 2019;7(1):92355-92364. Abstract DOI Cited by ~3
  6. S. van de Leemput, M. Meijs, A. Patel, F. Meijer, B. van Ginneken and R. Manniesing, "Multiclass Brain Tissue Segmentation in 4D CT using Convolutional Neural Networks", IEEE Access, 2019;7(1):51557-51569. Abstract DOI Cited by ~1
  7. K. Chung, O. Mets, P. Gerke, C. Jacobs, A. den Harder, E. Scholten, M. Prokop, P. de Jong, B. van Ginneken and C. Schaefer-Prokop, "Brock malignancy risk calculator for pulmonary nodules: validation outside a lung cancer screening population", Thorax, 2018;73:857-863. Abstract DOI PMID Cited by ~18
  8. M. Meijs, A. Patel, S. van de Leemput, M. Prokop, E. van Dijk, F. de Leeuw, F. Meijer, B. van Ginneken and R. Manniesing, "Robust Segmentation of the Full Cerebral Vasculature in 4D CT Images of Suspected Stroke Patients", Nature Scientific Reports, 2017;7. Abstract DOI PMID
  9. F. Ciompi, K. Chung, S. van Riel, A. Setio, P. Gerke, C. Jacobs, E. Scholten, C. Schaefer-Prokop, M. Wille, A. Marchiano, U. Pastorino, M. Prokop and B. van Ginneken, "Towards automatic pulmonary nodule management in lung cancer screening with deep learning", Nature Scientific Reports, 2017(46479). Abstract DOI PMID Cited by ~171
  10. K. Chung, C. Jacobs, E. Scholten, J. Goo, H. Prosch, N. Sverzellati, F. Ciompi, O. Mets, P. Gerke, M. Prokop, B. van Ginneken and C. Schaefer-Prokop, "Lung-RADS Category 4X: Does It Improve Prediction of Malignancy in Subsolid Nodules?", Radiology, 2017;284(1):264-271. Abstract DOI PMID Cited by ~32
  11. A. Setio, F. Ciompi, G. Litjens, P. Gerke, C. Jacobs, S. van Riel, M. Wille, M. Naqibullah, C. Sánchez and B. van Ginneken, "Pulmonary nodule detection in CT images: false positive reduction using multi-view convolutional networks", IEEE Transactions on Medical Imaging, 2016;35(5):1160-1169. Abstract DOI PMID Cited by ~605
  12. R. Rudyanto, S. Kerkstra, E. van Rikxoort, C. Fetita, P. Brillet, C. Lefevre, W. Xue, X. Zhu, J. Liang, I. Öksüz, D. Ünay, K. Kadipasaoglu, R. Estépar, J. Ross, G. Washko, J. Prieto, M. Hoyos, M. Orkisz, H. Meine, M. Hüllebrand, C. Stöcker, F. Mir, V. Naranjo, E. Villanueva, M. Staring, C. Xiao, B. Stoel, A. Fabijanska, E. Smistad, A. Elster, F. Lindseth, A. Foruzan, R. Kiros, K. Popuri, D. Cobzas, D. Jimenez-Carretero, A. Santos, M. Ledesma-Carbayo, M. Helmberger, M. Urschler, M. Pienn, D. Bosboom, A. Campo, M. Prokop, P. de Jong, C. Ortiz-de-Solorzano, A. Muñoz-Barrutia and B. van Ginneken, "Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: The VESSEL12 study", Medical Image Analysis, 2014;18:1217-1232. Abstract DOI PMID Cited by ~104
  13. G. Litjens, R. Toth, W. van de Ven, C. Hoeks, S. Kerkstra, B. van Ginneken, G. Vincent, G. Guillard, N. Birbeck, J. Zhang, R. Strand, F. Malmberg, Y. Ou, C. Davatzikos, M. Kirschner, F. Jung, J. Yuan, W. Qiu, Q. Gao, P. Edwards, B. Maan, F. van der Heijden, S. Ghose, J. Mitra, J. Dowling, D. Barratt, H. Huisman and A. Madabhushi, "Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge", Medical Image Analysis, 2014;18(2):359-373. Abstract DOI PMID Cited by ~275
  14. B. Lassen, E. van Rikxoort, M. Schmidt, S. Kerkstra, B. van Ginneken and J. Kuhnigk, "Automatic segmentation of the pulmonary lobes from chest CT scans based on fissures, vessels, and bronchi", IEEE Transactions on Medical Imaging, 2013;32(2):210-222. Abstract DOI PMID Cited by ~105

Papers in conference proceedings

  1. S. van de Leemput, J. Teuwen and R. Manniesing, "MemCNN: a Framework for Developing Memory Efficient Deep Invertible Networks", International Conference on Learning Representations, 2018. Abstract Url Cited by ~5
  2. S. van de Leemput, A. Patel and R. Manniesing, "Full Volumetric Brain Tissue Segmentation in Non-contrast CT using Memory Efficient Convolutional LSTMs", Medical Imaging meets NeurIPS, 2018. Abstract Url Cited by ~1
  3. S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Stacked Bidirectional Convolutional LSTMs for 3D Non-contrast CT Reconstruction from Spatiotemporal 4D CT", Medical Imaging with Deep Learning, 2018. Abstract Url Cited by ~1
  4. A. Patel, S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Automatic Cerebrospinal Fluid Segmentation in Non-Contrast CT Images Using a 3D Convolutional Network", Medical Imaging, 2017;10134. Abstract DOI Cited by ~6
  5. S. van de Leemput, F. Dorssers and B. Ehteshami Bejnordi, "A novel spherical shell filter for reducing false positives in automatic detection of pulmonary nodules in thoracic CT scans", Medical Imaging, 2015;9414:94142P. Abstract DOI
  6. R. van den Boom, M. Oei, S. Lafebre, L. Oostveen, A. Meijer, S. Steens, M. Prokop, B. van Ginneken and R. Manniesing, "Brain Tissue Segmentation in 4D CT Images Using Voxel Classification", Medical Imaging, 2012;8314:83144B-83144B-6. Abstract DOI

Abstracts

  1. C. González-Gonzalo, B. Liefers, A. Vaidyanathan, H. van Zeeland, C. Klaver and C. Sánchez, "Opening the "black box"? of deep learning in automated screening of eye diseases", Association for Research in Vision and Ophthalmology, 2019. Abstract Url
  2. H. van Zeeland, J. Meakin, B. Liefers, C. González-Gonzalo, A. Vaidyanathan, B. van Ginneken, C. Klaver and C. Sánchez, "EyeNED workstation: Development of a multi-modal vendor-independent application for annotation, spatial alignment and analysis of retinal images", Association for Research in Vision and Ophthalmology, 2019. Abstract Cited by ~1
  3. B. Liefers, J. Colijn, C. González-Gonzalo, A. Vaidyanathan, H. van Zeeland, P. Mitchell, C. Klaver and C. Sánchez, "Prediction of areas at risk of developing geographic atrophy in color fundus images using deep learning", Association for Research in Vision and Ophthalmology, 2019. Abstract
  4. M. Meijs, A. Patel, S. van de Leemput, B. van Ginneken, M. Prokop and R. Manniesing, "Fast, Robust and Accurate Segmentation of the Complete Cerebral Vasculature in 4D-CTA using Deep Learning", Annual Meeting of the Radiological Society of North America, 2018. Abstract
  5. S. van de Leemput, F. Meijer, M. Prokop and R. Manniesing, "Cerebral white matter, gray matter and cerebrospinal fluid segmentation in CT using VCAST: a volumetric cluster annotation and segmentation tool", European Congress of Radiology, 2017. Abstract
  6. R. Manniesing, S. van de Leemput, M. Prokop and B. van Ginneken, "White Matter and Gray Matter Segmentation in 4D CT Images of Acute Ischemic Stroke Patients: a Feasibility Study", Annual Meeting of the Radiological Society of North America, 2016. Abstract
  7. F. Ciompi, K. Chung, A. Setio, S. van Riel, E. Scholten, P. Gerke, C. Jacobs, U. Pastorino, A. Marchiano, M. Wille, M. Prokop and B. van Ginneken, "Pulmonary nodule type classification with convolutional networks", Medical Image Computing and Computer-Assisted Intervention, 2016. Abstract
  8. B. van Ginneken, E. van Rikxoort, S. Lafebre, C. Jacobs, M. Schmidt, J. Kuhnigk, M. Prokop, C. Schaefer-Prokop, J. Charbonnier, L. Hogeweg, P. Maduskar, L. Gallardo-Estrella, R. Philipsen and B. Lassen, "CIRRUS Lung: an optimized workflow for quantitative image analysis of thoracic computed tomography and chest radiography for major pulmonary diseases: chronic obstructive pulmonary disease, lung cancer and tuberculosis", Annual Meeting of the Radiological Society of North America, 2013. Abstract
  9. R. van den Boom, M. Oei, L. Oostveen, S. Lafebre, B. van Ginneken, R. Manniesing and M. Prokop, "Effect of radiation exposure on quantitative evaluation of cerebral CT perfusion maps: results from a hybrid digital phantom", European Congress of Radiology, 2012. Abstract
  10. M. Oei, R. van den Boom, L. Oostveen, S. Lafebre, E. Smit, B. van Ginneken, R. Manniesing and M. Prokop, "Hybrid digital phantom for optimizing data acquisition strategies in CT perfusion", European Congress of Radiology, 2012. Abstract

PhD theses

  1. S. Lafebre, "From cosmic particle to radio pulse", 2008. Abstract Url