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1,260 results on '"Leeuw, Frank‐Erik"'

4. Cognitive impairment in young adults following cerebellar stroke: Prevalence and longitudinal course

Author

van Alebeek, Mayte E., Norden, Anouk van, Brouwers, Paul J.A.M., Arntz, Renate M., van Dijk, Gert W., Gons, Rob A.R., van Uden, Inge W.M., Heijer, Tom den, de Kort, Paul L.M., de Laat, Karlijn F., Vermeer, Sarah E., van Zagten, Marian S.G., Wermer, Marieke J.H., Nederkoorn, Paul J., van Rooij, Frank G., van den Wijngaard, Ido R., Reumers, Stacha F.I., Schellekens, Mijntje M.I., Lugtmeijer, Selma, Maas, Roderick P.P.W.M., Verhoeven, Jamie I., Boot, Esther M., Ekker, Merel S., Tuladhar, Anil M., van de Warrenburg, Bart P.C., Schutter, Dennis J.L.G., Kessels, Roy P.C., and de Leeuw, Frank-Erik

Published
2024
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7. Stroke

Author

Hilkens, Nina A, Casolla, Barbara, Leung, Thomas W, and de Leeuw, Frank-Erik

Published
2024
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10. Neuroimaging standards for research into small vessel disease—advances since 2013

Author

Duering, Marco, Biessels, Geert Jan, Brodtmann, Amy, Chen, Christopher, Cordonnier, Charlotte, de Leeuw, Frank-Erik, Debette, Stéphanie, Frayne, Richard, Jouvent, Eric, Rost, Natalia S, ter Telgte, Annemieke, Al-Shahi Salman, Rustam, Backes, Walter H, Bae, Hee-Joon, Brown, Rosalind, Chabriat, Hugues, De Luca, Alberto, deCarli, Charles, Dewenter, Anna, Doubal, Fergus N, Ewers, Michael, Field, Thalia S, Ganesh, Aravind, Greenberg, Steven, Helmer, Karl G, Hilal, Saima, Jochems, Angela C C, Jokinen, Hanna, Kuijf, Hugo, Lam, Bonnie Y K, Lebenberg, Jessica, MacIntosh, Bradley J, Maillard, Pauline, Mok, Vincent C T, Pantoni, Leonardo, Rudilosso, Salvatore, Satizabal, Claudia L, Schirmer, Markus D, Schmidt, Reinhold, Smith, Colin, Staals, Julie, Thrippleton, Michael J, van Veluw, Susanne J, Vemuri, Prashanthi, Wang, Yilong, Werring, David, Zedde, Marialuisa, Akinyemi, Rufus O, Del Brutto, Oscar H, Markus, Hugh S, Zhu, Yi-Cheng, Smith, Eric E, Dichgans, Martin, and Wardlaw, Joanna M

Published
2023
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12. Stroke genetics informs drug discovery and risk prediction across ancestries

Author

Mishra, Aniket, Malik, Rainer, Hachiya, Tsuyoshi, Jürgenson, Tuuli, Namba, Shinichi, Posner, Daniel C., Kamanu, Frederick K., Koido, Masaru, Le Grand, Quentin, Shi, Mingyang, He, Yunye, Georgakis, Marios K., Caro, Ilana, Krebs, Kristi, Liaw, Yi-Ching, Vaura, Felix C., Lin, Kuang, Winsvold, Bendik Slagsvold, Srinivasasainagendra, Vinodh, Parodi, Livia, Bae, Hee-Joon, Chauhan, Ganesh, Chong, Michael R., Tomppo, Liisa, Akinyemi, Rufus, Roshchupkin, Gennady V., Habib, Naomi, Jee, Yon Ho, Thomassen, Jesper Qvist, Abedi, Vida, Cárcel-Márquez, Jara, Nygaard, Marianne, Leonard, Hampton L., Yang, Chaojie, Yonova-Doing, Ekaterina, Knol, Maria J., Lewis, Adam J., Judy, Renae L., Ago, Tetsuro, Amouyel, Philippe, Armstrong, Nicole D., Bakker, Mark K., Bartz, Traci M., Bennett, David A., Bis, Joshua C., Bordes, Constance, Børte, Sigrid, Cain, Anael, Ridker, Paul M., Cho, Kelly, Chen, Zhengming, Cruchaga, Carlos, Cole, John W., de Jager, Phil L., de Cid, Rafael, Endres, Matthias, Ferreira, Leslie E., Geerlings, Mirjam I., Gasca, Natalie C., Gudnason, Vilmundur, Hata, Jun, He, Jing, Heath, Alicia K., Ho, Yuk-Lam, Havulinna, Aki S., Hopewell, Jemma C., Hyacinth, Hyacinth I., Inouye, Michael, Jacob, Mina A., Jeon, Christina E., Jern, Christina, Kamouchi, Masahiro, Keene, Keith L., Kitazono, Takanari, Kittner, Steven J., Konuma, Takahiro, Kumar, Amit, Lacaze, Paul, Launer, Lenore J., Lee, Keon-Joo, Lepik, Kaido, Li, Jiang, Li, Liming, Manichaikul, Ani, Markus, Hugh S., Marston, Nicholas A., Meitinger, Thomas, Mitchell, Braxton D., Montellano, Felipe A., Morisaki, Takayuki, Mosley, Thomas H., Nalls, Mike A., Nordestgaard, Børge G., O’Donnell, Martin J., Okada, Yukinori, Onland-Moret, N. Charlotte, Ovbiagele, Bruce, Peters, Annette, Psaty, Bruce M., Rich, Stephen S., Rosand, Jonathan, Sabatine, Marc S., Sacco, Ralph L., Saleheen, Danish, Sandset, Else Charlotte, Salomaa, Veikko, Sargurupremraj, Muralidharan, Sasaki, Makoto, Satizabal, Claudia L., Schmidt, Carsten O., Shimizu, Atsushi, Smith, Nicholas L., Sloane, Kelly L., Sutoh, Yoichi, Sun, Yan V., Tanno, Kozo, Tiedt, Steffen, Tatlisumak, Turgut, Torres-Aguila, Nuria P., Tiwari, Hemant K., Trégouët, David-Alexandre, Trompet, Stella, Tuladhar, Anil Man, Tybjærg-Hansen, Anne, van Vugt, Marion, Vibo, Riina, Verma, Shefali S., Wiggins, Kerri L., Wennberg, Patrik, Woo, Daniel, Wilson, Peter W. F., Xu, Huichun, Yang, Qiong, Yoon, Kyungheon, Millwood, Iona Y., Gieger, Christian, Ninomiya, Toshiharu, Grabe, Hans J., Jukema, J. Wouter, Rissanen, Ina L., Strbian, Daniel, Kim, Young Jin, Chen, Pei-Hsin, Mayerhofer, Ernst, Howson, Joanna M. M., Irvin, Marguerite R., Adams, Hieab, Wassertheil-Smoller, Sylvia, Christensen, Kaare, Ikram, Mohammad A., Rundek, Tatjana, Worrall, Bradford B., Lathrop, G. Mark, Riaz, Moeen, Simonsick, Eleanor M., Kõrv, Janika, França, Paulo H. C., Zand, Ramin, Prasad, Kameshwar, Frikke-Schmidt, Ruth, de Leeuw, Frank-Erik, Liman, Thomas, Haeusler, Karl Georg, Ruigrok, Ynte M., Heuschmann, Peter Ulrich, Longstreth, W. T., Jung, Keum Ji, Bastarache, Lisa, Paré, Guillaume, Damrauer, Scott M., Chasman, Daniel I., Rotter, Jerome I., Anderson, Christopher D., Zwart, John-Anker, Niiranen, Teemu J., Fornage, Myriam, Liaw, Yung-Po, Seshadri, Sudha, Fernández-Cadenas, Israel, Walters, Robin G., Ruff, Christian T., Owolabi, Mayowa O., Huffman, Jennifer E., Milani, Lili, Kamatani, Yoichiro, Dichgans, Martin, and Debette, Stephanie

Published
2022
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13. Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration

Author

Smith, Eric E, Biessels, Geert Jan, De Guio, François, de Leeuw, Frank Erik, Duchesne, Simon, Düring, Marco, Frayne, Richard, Ikram, M Arfan, Jouvent, Eric, MacIntosh, Bradley J, Thrippleton, Michael J, Vernooij, Meike W, Adams, Hieab, Backes, Walter H, Ballerini, Lucia, Black, Sandra E, Chen, Christopher, Corriveau, Rod, DeCarli, Charles, Greenberg, Steven M, Gurol, M Edip, Ingrisch, Michael, Job, Dominic, Lam, Bonnie YK, Launer, Lenore J, Linn, Jennifer, McCreary, Cheryl R, Mok, Vincent CT, Pantoni, Leonardo, Pike, G Bruce, Ramirez, Joel, Reijmer, Yael D, Romero, Jose Rafael, Ropele, Stefan, Rost, Natalia S, Sachdev, Perminder S, Scott, Christopher JM, Seshadri, Sudha, Sharma, Mukul, Sourbron, Steven, Steketee, Rebecca ME, Swartz, Richard H, van Oostenbrugge, Robert, van Osch, Matthias, van Rooden, Sanneke, Viswanathan, Anand, Werring, David, Dichgans, Martin, and Wardlaw, Joanna M

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Neurodegenerative, Biomedical Imaging, Brain Disorders, Neurosciences, Neurological, Cerebrovascular disease, Stroke, Dementia, Magnetic resonance imaging, Radiology, Genetics, Biological psychology
Abstract

IntroductionMany consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease.MethodsSurveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis.ResultsA framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository.ConclusionsThe HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

Published
2019

18. Trigger factors in patients with a patent foramen ovale—associated stroke: A case-crossover study

Author

Immens, Maikel HM, primary, Ekker, Merel S, additional, Verburgt, Esmee, additional, Verhoeven, Jamie I, additional, Schellekens, Mijntje MI, additional, Hilkens, Nina A, additional, Boot, Esther M, additional, Van Alebeek, Mayte E, additional, Brouwers, Paul JAM, additional, Arntz, Renate M, additional, Van Dijk, Gert W, additional, Gons, Rob AR, additional, Van Uden, Inge WM, additional, den Heijer, Tom, additional, de Kort, Paul LM, additional, de Laat, KF, additional, Van Norden, Anouk GW, additional, Vermeer, Sarah E, additional, Van Zagten, Marian SG, additional, Van Oostenbrugge, Robert J, additional, Wermer, Marieke JH, additional, Nederkoorn, Paul J, additional, Kerkhoff, Henk, additional, Rooyer, FA, additional, Van Rooij, Frank G, additional, Van den Wijngaard, Ido R, additional, Klijn, Catharina JM, additional, Tuladhar, Anil M, additional, ten Cate, Tim JF, additional, and de Leeuw, Frank-Erik, additional

Published
2024
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19. Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR

Author

Ghafoorian, Mohsen, Teuwen, Jonas, Manniesing, Rashindra, de Leeuw, Frank-Erik, van Ginneken, Bram, Karssemeijer, Nico, and Platel, Bram

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Ventricular volume and its progression are known to be linked to several brain diseases such as dementia and schizophrenia. Therefore accurate measurement of ventricle volume is vital for longitudinal studies on these disorders, making automated ventricle segmentation algorithms desirable. In the past few years, deep neural networks have shown to outperform the classical models in many imaging domains. However, the success of deep networks is dependent on manually labeled data sets, which are expensive to acquire especially for higher dimensional data in the medical domain. In this work, we show that deep neural networks can be trained on much-cheaper-to-acquire pseudo-labels (e.g., generated by other automated less accurate methods) and still produce more accurate segmentations compared to the quality of the labels. To show this, we use noisy segmentation labels generated by a conventional region growing algorithm to train a deep network for lateral ventricle segmentation. Then on a large manually annotated test set, we show that the network significantly outperforms the conventional region growing algorithm which was used to produce the training labels for the network. Our experiments report a Dice Similarity Coefficient (DSC) of $0.874$ for the trained network compared to $0.754$ for the conventional region growing algorithm ($p < 0.001$)., Comment: 7 pages, 4 figures, SPIE Medical Imaging 2018 Conference paper

Published
2018
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20. Prehospital transdermal glyceryl trinitrate in patients with presumed acute stroke (MR ASAP): an ambulance-based, multicentre, randomised, open-label, blinded endpoint, phase 3 trial

Author

van Ahee, Ayla, Visseren, Frank, Halkes, Patricia, van Eijk, Ruben, Simons, Michelle, Pellikaan, Wilma, Van Wijngaarden, Wilma, Ponjee, Eva, Geijtenbeek, Petra, Arts, Ton, Zock, Elles, Oudshoorn, Wilma, Steenwinkel, Frans, Samim, Hamdia, van Zandwijk, Mark, Vrielink, Lisette, Mulder, Peter Jan, Gerritsen, Aico, Ijzermans, Jim, Kooijman, Marjan, Francissen, Oscar, van Nuland, Rick, van Zwam, Wim, Jacobi, Linda, van den Berg, Rene, Beenen, Ludo, van Es, Adriaan, van Doormaal, Pieter-Jan, Lycklama a Nijeholt, Geert, van den Wijngaard, Ido, Yoo, Albert, Yo, Lonneke, Martens, Jasper, Hammer, Bas, Roosendaal, Stefan, Meijer, Anton, Krietemeijer, Menno, Bokkers, Reinoud, van der Hoorn, Anouk, Gerrits, Dick, Coutinho, Jonathan, Jansen, Ben, Manschot, Sanne, Koudstaal, Peter, Keizer, Koos, Chalos, Vicky, Versteeg, Adriaan, Wolff, Lennard, van Voorst, Henk, van der Sluijs, Matthijs, Hoving, Arnolt-Jan, Treurniet, Kilian, LeCouffe, Natalie, van de Graaf, Rob, Goldhoorn, Robert-Jan, Hinseveld, Wouter, Pirson, Anne, Sondag, Lotte, Kappelhof, Manon, Tolhuisen, Manon, Brouwer, Josje, van der Steen, Wouter, Rinkel, Leon, Bruggeman, Agnetha, Sprengers, Rita, Sterrenberg, Martin, Verheesen, Sabrina, Heiligers, Leontien, Martens, Yvonne, El Ghannouti, Naziha, Slotboom, Miranda, van den Berg, Sophie A, Uniken Venema, Simone M, Reinink, Hendrik, Hofmeijer, Jeannette, Schonewille, Wouter J, Miedema, Irene, Fransen, Puck S S, O Pruissen, D Martijn, Raaijmakers, Theodora W M, van Dijk, Gert W, de Leeuw, Frank-Erik, van Vliet, Jorine A, Kwa, Vincent I H, Kerkhoff, Henk, van 't Net, Alex, Boomars, Rene, Siegers, Arjen, Lok, Tycho, Caminada, Klaartje, Esteve Cuevas, Laura M, Visser, Marieke C, Zwetsloot, Casper P, Boomsma, Jooske M F, Schipper, Mirjam H, van Eijkelenburg, Roeland P J, Berkhemer, Olvert A, Nieboer, Daan, Lingsma, Hester F, Emmer, Bart J, van Oostenbrugge, Robert J, van der Lugt, Aad, Roos, Yvo B W E M, Majoie, Charles B L M, Dippel, Diederik W J, Nederkoorn, Paul J, and van der Worp, H Bart

Published
2022
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22. Impact of the lockdown on acute stroke treatments during the first surge of the COVID-19 outbreak in the Netherlands

Author

Benali, Faysal, Stolze, Lotte J., Rozeman, Anouk D., Dinkelaar, Wouter, Coutinho, Jonathan M., Emmer, Bart J., Gons, Rob A. R., Yo, Lonneke F. S., van Tuijl, Julia H., Boukrab, Issam, van Dam-Nolen, Dianne H. K., van den Wijngaard, Ido R., Lycklama à Nijeholt, Geert J., de Laat, Karlijn F., van Dijk, Lukas C., den Hertog, Heleen M., Flach, H. Zwenneke, Wermer, Marieke J. H., van Walderveen, Marianne A. A., Brouwers, Paul J. A. M., Bulut, Tomas, Vermeer, Sarah E., Bernsen, Marie Louise E., Uyttenboogaart, Maarten, Bokkers, Reinoud P. H., Boogaarts, Jeroen D., de Leeuw, Frank-Erik, van der Worp, H. Bart, van der Schaaf, Irene C., Schonewille, Wouter J., Vos, Jan A., Remmers, Michel J. M., Imani, Farshad, Dippel, Diederik W. J., van Zwam, Wim H., Nederkoorn, Paul J., and van Oostenbrugge, Robert J.

Published
2022
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25. Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Author

Ghafoorian, Mohsen, Mehrtash, Alireza, Kapur, Tina, Karssemeijer, Nico, Marchiori, Elena, Pesteie, Mehran, Guttmann, Charles R. G., de Leeuw, Frank-Erik, Tempany, Clare M., van Ginneken, Bram, Fedorov, Andriy, Abolmaesumi, Purang, Platel, Bram, and Wells III, William M.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of normal and diseased tissue in the images. Convolutional neural networks (CNNs), which have shown to be successful in many medical image analysis tasks, are typically sensitive to the variations in imaging protocols. Therefore, in many cases, networks trained on data acquired with one MRI protocol, do not perform satisfactorily on data acquired with different protocols. This limits the use of models trained with large annotated legacy datasets on a new dataset with a different domain which is often a recurring situation in clinical settings. In this study, we aim to answer the following central questions regarding domain adaptation in medical image analysis: Given a fitted legacy model, 1) How much data from the new domain is required for a decent adaptation of the original network?; and, 2) What portion of the pre-trained model parameters should be retrained given a certain number of the new domain training samples? To address these questions, we conducted extensive experiments in white matter hyperintensity segmentation task. We trained a CNN on legacy MR images of brain and evaluated the performance of the domain-adapted network on the same task with images from a different domain. We then compared the performance of the model to the surrogate scenarios where either the same trained network is used or a new network is trained from scratch on the new dataset.The domain-adapted network tuned only by two training examples achieved a Dice score of 0.63 substantially outperforming a similar network trained on the same set of examples from scratch., Comment: 8 pages, 3 figures

Published
2017
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26. Cognitive impairment in young adults following cerebellar stroke: Prevalence and longitudinal course.

Author

Reumers, Stacha F.I., Schellekens, Mijntje M.I., Lugtmeijer, Selma, Maas, Roderick P.P.W.M., Verhoeven, Jamie I., Boot, Esther M., Ekker, Merel S., Tuladhar, Anil M., van de Warrenburg, Bart P.C., Schutter, Dennis J.L.G., Kessels, Roy P.C., and de Leeuw, Frank-Erik

Subjects
COGNITION disorders, STROKE treatment, DISEASE prevalence, NEUROPSYCHOLOGICAL tests, EXECUTIVE function
Published
2024
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27. White matter integrity in hospitalized COVID-19 patients is not associated with short- and long-term clinical outcomes.

Author

van Lith, Theresa J., Hao Li, van der Wijk, Marte W., Wijers, Naomi T., Sluis, Wouter M., Wermer, Marieke J. H., de Leeuw, Frank-Erik, Meijer, Frederick J. A., and Tuladhar, Anil M.

Subjects
POST-acute COVID-19 syndrome, COVID-19, DIFFUSION tensor imaging, PATIENT experience, VISUAL analog scale
Abstract

Objectives: SARS-CoV-2 infection is associated with a decline in functional outcomes; many patients experience persistent symptoms, while the underlying pathophysiology remains unclear. This study investigated white matter (WM) integrity on brain MRI in hospitalized COVID-19 patients and its associations with clinical outcomes, including long COVID. Materials and methods: We included hospitalized COVID-19 patients and controls from CORONavirus and Ischemic Stroke (CORONIS), an observational cohort study, who underwent MRI-DWI imaging at baseline shortly after discharge (<3 months after positive PCR) and 3 months after baseline scanning. We assessed WM integrity using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) and performed comparisons between groups and within patients. Clinical assessment was conducted at 3 and 12 months with functional outcomes such as modified Rankin Scale (mRS), Post-COVID-19 Functional Status scale (PCFS), Visual Analogue Scale (VAS), and long COVID, cognitive assessment was conducted by the Modified Telephone Interview for Cognitive Status (TICS-M), and the Hospital Anxiety and Depression Scale (HADS) was used to assess mood disorder. Associations between WM integrity and clinical outcomes were evaluated using logistic regression and linear regression. Results: A total of 49 patients (mean age 59.5 years) showed higher overall peak width of skeletonized mean diffusivity (PSMD) (p = 0.030) and lower neurite density index (NDI) in several WM regions compared with 25 controls at the baseline (p < 0.05; FWE-corrected) but did not remain statistically significant after adjusting for WM hyperintensities. Orientation dispersion index (ODI) increased after 3-month follow-up in several WM regions within patients (p < 0.05), which remained significant after correction for changes in WMH volume. Patients exhibited worse clinical outcomes compared with controls. Low NDI at baseline was associated with worse performance on the Post-COVID-19 Functional Status scale after 12 months (p = 0.018). Conclusion: After adjusting for WMH, hospitalized COVID-19 patients no longer exhibited lower WM integrity compared with controls. WM integrity was generally not associated with clinical assessments as measured shortly after discharge, suggesting that factors other than underlying WM integrity play a role in worse clinical outcomes or long COVID. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin

Author

Ghafoorian, Mohsen, Karssemeijer, Nico, Heskes, Tom, Bergkamp, Mayra, Wissink, Joost, Obels, Jiri, Keizer, Karlijn, de Leeuw, Frank-Erik, van Ginneken, Bram, Marchiori, Elena, and Platel, Bram

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Lacunes of presumed vascular origin (lacunes) are associated with an increased risk of stroke, gait impairment, and dementia and are a primary imaging feature of the small vessel disease. Quantification of lacunes may be of great importance to elucidate the mechanisms behind neuro-degenerative disorders and is recommended as part of study standards for small vessel disease research. However, due to the different appearance of lacunes in various brain regions and the existence of other similar-looking structures, such as perivascular spaces, manual annotation is a difficult, elaborative and subjective task, which can potentially be greatly improved by reliable and consistent computer-aided detection (CAD) routines. In this paper, we propose an automated two-stage method using deep convolutional neural networks (CNN). We show that this method has good performance and can considerably benefit readers. We first use a fully convolutional neural network to detect initial candidates. In the second step, we employ a 3D CNN as a false positive reduction tool. As the location information is important to the analysis of candidate structures, we further equip the network with contextual information using multi-scale analysis and integration of explicit location features. We trained, validated and tested our networks on a large dataset of 1075 cases obtained from two different studies. Subsequently, we conducted an observer study with four trained observers and compared our method with them using a free-response operating characteristic analysis. Shown on a test set of 111 cases, the resulting CAD system exhibits performance similar to the trained human observers and achieves a sensitivity of 0.974 with 0.13 false positives per slice. A feasibility study also showed that a trained human observer would considerably benefit once aided by the CAD system., Comment: 11 pages, 7 figures

Published
2016
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29. Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities

Author

Ghafoorian, Mohsen, Karssemeijer, Nico, Heskes, Tom, van Uden, Inge, Sanchez, Clara, Litjens, Geert, de Leeuw, Frank-Erik, van Ginneken, Bram, Marchiori, Elena, and Platel, Bram

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The anatomical location of imaging features is of crucial importance for accurate diagnosis in many medical tasks. Convolutional neural networks (CNN) have had huge successes in computer vision, but they lack the natural ability to incorporate the anatomical location in their decision making process, hindering success in some medical image analysis tasks. In this paper, to integrate the anatomical location information into the network, we propose several deep CNN architectures that consider multi-scale patches or take explicit location features while training. We apply and compare the proposed architectures for segmentation of white matter hyperintensities in brain MR images on a large dataset. As a result, we observe that the CNNs that incorporate location information substantially outperform a conventional segmentation method with hand-crafted features as well as CNNs that do not integrate location information. On a test set of 46 scans, the best configuration of our networks obtained a Dice score of 0.791, compared to 0.797 for an independent human observer. Performance levels of the machine and the independent human observer were not statistically significantly different (p-value=0.17)., Comment: 13 pages, 8 figures

Published
2016

30. Consensus statement on current and emerging methods for the diagnosis and evaluation of cerebrovascular disease

Author

Donahue, Manus J, Achten, Eric, Cogswell, Petrice M, De Leeuw, Frank-Erik, Derdeyn, Colin P, Dijkhuizen, Rick M, Fan, Audrey P, Ghaznawi, Rashid, Heit, Jeremy J, Ikram, M Arfan, Jezzard, Peter, Jordan, Lori C, Jouvent, Eric, Knutsson, Linda, Leigh, Richard, Liebeskind, David S, Lin, Weili, Okell, Thomas W, Qureshi, Adnan I, Stagg, Charlotte J, van Osch, Matthias JP, van Zijl, Peter CM, Watchmaker, Jennifer M, Wintermark, Max, Wu, Ona, Zaharchuk, Greg, Zhou, Jinyuan, and Hendrikse, Jeroen

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Stroke, Aging, Brain Disorders, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, Good Health and Well Being, Cerebrovascular Disorders, Humans, hemodynamics, metabolism, imaging, cerebrovascular disease, Cardiorespiratory Medicine and Haematology, Neurology & Neurosurgery, Clinical sciences
Abstract

Cerebrovascular disease (CVD) remains a leading cause of death and the leading cause of adult disability in most developed countries. This work summarizes state-of-the-art, and possible future, diagnostic and evaluation approaches in multiple stages of CVD, including (i) visualization of sub-clinical disease processes, (ii) acute stroke theranostics, and (iii) characterization of post-stroke recovery mechanisms. Underlying pathophysiology as it relates to large vessel steno-occlusive disease and the impact of this macrovascular disease on tissue-level viability, hemodynamics (cerebral blood flow, cerebral blood volume, and mean transit time), and metabolism (cerebral metabolic rate of oxygen consumption and pH) are also discussed in the context of emerging neuroimaging protocols with sensitivity to these factors. The overall purpose is to highlight advancements in stroke care and diagnostics and to provide a general overview of emerging research topics that have potential for reducing morbidity in multiple areas of CVD.

Published
2018

31. Contribution of Common Genetic Variants to Risk of Early Onset Ischemic Stroke

Author

Jaworek, Thomas, Xu, Huichun, Gaynor, Brady J, Cole, John W., Rannikmae, Kristiina, Stanne, Tara M, Tomppo, Liisa, Abedi, Vida, Amouyel, Philippe, Armstrong, Nicole D, Attia, John, Bell, Steven, Benavente, Oscar R, Boncoraglio, Giorgio B, Butterworth, Adam, Carcel-Marquez, Jara, Chen, Zhengming, Chong, Michael, Cruchaga, Carlos, Cushman, Mary, Danesh, John, Debette, Stephanie, Duggan, David J, Durda, Jon Peter, Engstrom, Gunnar, Enzinger, Chris, Faul, Jessica D, Fecteau, Natalie S, Fernandez-Cadenas, Israel, Gieger, Christian, Giese, Anne-Katrin, Grewal, Raji P, Grittner, Ulrike, Havulinna, Aki S, Heitsch, Laura, Hochberg, Marc C, Holliday, Elizabeth, Hu, Jie, Ilinca, Andreea, Irvin, Marguerite R, Jackson, Rebecca D, Jacob, Mina A., Janssen, Raquel Rabionet, Jimenez-Conde, Jordi, Johnson, Julie A, Kamatani, Yoichiro, Kardia, Sharon L, Koido, Masaru, Kubo, Michiaki, Lange, Leslie, Lee, Jin-Moo, Lemmens, Robin, Levi, Christopher R, Li, Jiang, Li, Liming, Lin, Kuang, Lopez, Haley, Luke, Sothear, Maguire, Jane, McArdle, Patrick F, McDonough, Caitrin W., Meschia, James F, Metso, Tiina, Muller-Nurasyid, Martina, OʼConnor, Timothy D, OʼDonnell, Martin, Peddareddygari, Leema R, Pera, Joanna, Perry, James A, Peters, Annette, Putaala, Jukka, Ray, Debashree, Rexrode, Kathryn, Ribases, Marta, Rosand, Jonathan, Rothwell, Peter M, Rundek, Tatjana, Ryan, Kathleen A, Sacco, Ralph L., Salomaa, Veikko, Sanchez-Mora, Cristina, Schmidt, Reinhold, Sharma, Pankaj, Slowik, Agnieszka, Smith, Jennifer A, Smith, Nicholas L, Wassertheil-Smoller, Sylvia, Soederholm, Martin, Stine, O. C, Strbian, Daniel, Sudlow, Cathie L, Tatlisumak, Turgut, Terao, Chikashi, Thijs, Vincent, Torres-Aguila, Nuria P, Tregouet, David-Alexandre, Tuladhar, Anil M., Veldink, Jan H, Walters, Robin G, Weir, David R, Woo, Daniel, Worrall, Bradford B, Hong, Charles C, Ross, Owen, Zand, Ramin, Leeuw, Frank-Erik de, Lindgren, Arne G, Pare, Guillaume, Anderson, Christopher D., Markus, Hugh S, Jern, Christina, Malik, Rainer, Dichgans, Martin, Mitchell, Braxton D, and Kittner, Steven J

Published
2022
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33. European stroke organisation (ESO) guideline on cerebral small vessel disease, part 2, lacunar ischaemic stroke

Author

Wardlaw, Joanna M, primary, Chabriat, Hugues, additional, de Leeuw, Frank-Erik, additional, Debette, Stéphanie, additional, Dichgans, Martin, additional, Doubal, Fergus, additional, Jokinen, Hanna, additional, Katsanos, Aristeidis H, additional, Ornello, Raffaele, additional, Pantoni, Leonardo, additional, Pasi, Marco, additional, Pavlovic, Aleksandra M, additional, Rudilosso, Salvatore, additional, Schmidt, Reinhold, additional, Staals, Julie, additional, Taylor-Rowan, Martin, additional, Hussain, Salman, additional, and Lindgren, Arne G, additional

Published
2024
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34. Immune regulation and blood–brain barrier permeability in cerebral small vessel disease: study protocol of the INflammation and Small Vessel Disease (INSVD) study – a multicentre prospective cohort study

Author

Low, Audrey, primary, van Winden, Sanne, additional, Cai, Lupei, additional, Kessels, Roy P C, additional, Maas, Marnix C, additional, Morris, Robin G, additional, Nus, Meritxell, additional, Tozer, Daniel J, additional, Tuladhar, Anil, additional, van der Kolk, Anja, additional, Wolters, Rowan, additional, Mallat, Ziad, additional, Riksen, Niels P, additional, Markus, Hugh, additional, and de Leeuw, Frank‐Erik, additional

Published
2024
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37. Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

Author

Harkness, Kirsty, Shaw, Louise, Sword, Jane, Mohd Nor, Azlisham, Sharma, Pankaj, Kelly, Deborah, Harrington, Frances, Randall, Marc, Smith, Matthew, Mahawish, Karim, Elmarim, Abduelbaset, Esisi, Bernard, Cullen, Claire, Nallasivam, Arumug, Price, Christopher, Barry, Adrian, Roffe, Christine, Coyle, John, Hassan, Ahamad, Birns, Jonathan, Cohen, David, Sekaran, Lakshmanan, Parry-Jones, Adrian, Parry, Anthea, Hargroves, David, Proschel, Harald, Datta, Prabel, Darawil, Khaled, Manoj, Aravindakshan, Burn, Mathew, Patterson, Chris, Giallombardo, Elio, Smyth, Nigel, Mansoor, Syed, Anwar, Ijaz, Marsh, Rachel, Ispoglou, Sissi, Chadha, Dinesh, Prabhakaran, Mathuri, Meenakishundaram, Sanjeevikumar, O'Connell, Janice, Scott, Jon, Krishnamurthy, Vinodh, Aghoram, Prasanna, McCormick, Michael, Sprigg, Nikola, O'Mahony, Paul, Cooper, Martin, Choy, Lillian, Wilkinson, Peter, Leach, Simon, Caine, Sarah, Burger, Ilse, Gunathilagan, Gunaratam, Guyler, Paul, Emsley, Hedley, Davis, Michelle, Manawadu, Dulka, Pasco, Kath, Mamun, Maam, Luder, Robert, Sajid, Mahmud, Okwera, James, Warburton, Elizabeth, Saastamoinen, Kari, England, Timothy, Putterill, Janet, Flossman, Enrico, Power, Michael, Dani, Krishna, Mangion, David, Suman, Appu, Corrigan, John, Lawrence, Enas, Vahidassr, Djamil, Shakeshaft, Clare, Brown, Martin, Charidimou, Andreas, Cohen, Hannah, Banerjee, Gargi, Houlden, Henry, White, Mark, Yousry, Tarek, Flossmann, Enrico, Muir, Keith, Gratz, Pascal, Mattle, Heinrich, Panos, Leonidas, Korczyn, Amos, Kliper, Efrat, Maeder, Philippe, Gass, Achim, Pachai, Chahin, Bracoub, Luc, Douste-Blazy, Marie-Yvonne, Fratacci, Marie Dominique, Vicaut, Eric, Sato, Shoichiro, Miwa, Kaori, Fujita, Kyohei, Ide, Toshihiro, Ma, Henry, Ly, John, Singhal, Shaloo, Chandra, Ronil, Slater, Lee-Anne, Soufan, Cathy, Moran, Christopher, Traenka, Christopher, Thilemann, Sebastian, Fladt, Joachim, Gensicke, Henrik, Bonati, Leo, Kim, Beom Joon, Han, Moon-Ku, Kang, Jihoon, Ko, Eunbin, Yang, Mi Hwa, Jang, Myung Suk, Murphy, Sean, Carty, Fiona, Akijian, Layan, Thornton, John, Schembri, Mark, Douven, Elles, Delgado-Mederos, Raquel, Marín, Rebeca, Camps-Renom, Pol, Guisado-Alonso, Daniel, Nuñez, Fidel, Medrano-Martorell, Santiago, Merino, Elisa, Iida, Kotaro, Ikeda, Syuhei, Irie, Hiroyuki, Demirelli, Derya Selcuk, Medanta, Jayesh Modi, Zerna, Charlotte, Hernández, Maria Valdés, Armitage, Paul, Heye, Anna, Muñoz-Maniega, Susana, Sakka, Eleni, Thrippleton, Michael, Dennis, Martin, Beigneux, Ysoline, Silva, Mauro, Venketasubramanian, Narayanaswamy, Ho, Shu Leung, Cheung, Raymond Tak Fai, Chan, Koon Ho, Teo, Kay Cheong, Hui, Edward, Kwan, Joseph Shiu Kwong, Chang, Richard, Tse, Man Yu, Hoi, Chu Peng, Chan, Chung Yan, Chan, Oi Ling, Cheung, Ryan Hoi Kit, Wong, Edmund Ka Ming, Leung, Kam Tat, Tsang, Suk Fung, Ip, Hing Lung, Ma, Sze Ho, Ma, Karen, Fong, Wing Chi, Li, Siu Hung, Li, Richard, Ng, Ping Wing, Wong, Kwok Kui, Liu, Wenyan, Wong, Lawrence, Ramos, Lino, De Schryver, Els, Jöbsis, Joost, van der Sande, Jaap, Brouwers, Paul, Roos, Yvo, Stam, Jan, Bakker, Stef, Verbiest, Henk, Schoonewille, Wouter, Linn, Cisca, Hertzberger, Leopold, van Gemert, Maarten, Berntsen, Paul, Van Dam-Nolen, Dianne, Kooi, M Eline, Van der Lugt, Aad, Koudstaal, Peter, Leff, Alexander, Ward, Nicholas, Nachev, Parashkev, Perry, Richard, Ozkan, Hatice, Mitchell, John, Best, Jonathan G, Ambler, Gareth, Wilson, Duncan, Lee, Keon-Joo, Lim, Jae-Sung, Shiozawa, Masayuki, Koga, Masatoshi, Li, Linxin, Lovelock, Caroline, Chabriat, Hugues, Hennerici, Michael, Wong, Yuen Kwun, Mak, Henry Ka Fung, Prats-Sanchez, Luis, Martínez-Domeño, Alejandro, Inamura, Shigeru, Yoshifuji, Kazuhisa, Arsava, Ethem Murat, Horstmann, Solveig, Purrucker, Jan, Lam, Bonnie Yin Ka, Wong, Adrian, Kim, Young Dae, Song, Tae-Jin, Lemmens, Robin, Eppinger, Sebastian, Gattringer, Thomas, Uysal, Ender, Tanriverdi, Zeynep, Bornstein, Natan M, Ben Assayag, Einor, Hallevi, Hen, Molad, Jeremy, Nishihara, Masashi, Tanaka, Jun, Coutts, Shelagh B, Polymeris, Alexandros, Wagner, Benjamin, Seiffge, David J, Lyrer, Philippe, Algra, Ale, Kappelle, L Jaap, Al-Shahi Salman, Rustam, Jäger, Hans R, Lip, Gregory Y H, Fischer, Urs, El-Koussy, Marwan, Mas, Jean-Louis, Legrand, Laurence, Karayiannis, Christopher, Phan, Thanh, Gunkel, Sarah, Christ, Nicolas, Abrigo, Jill, Leung, Thomas, Chu, Winnie, Chappell, Francesca, Makin, Stephen, Hayden, Derek, Williams, David J, Mess, Werner H, Nederkoorn, Paul J, Barbato, Carmen, Browning, Simone, Wiegertjes, Kim, Tuladhar, Anil M, Maaijwee, Noortje, Guevarra, Anne Cristine, Yatawara, Chathuri, Mendyk, Anne-Marie, Delmaire, Christine, Köhler, Sebastian, van Oostenbrugge, Robert, Zhou, Ying, Xu, Chao, Hilal, Saima, Gyanwali, Bibek, Chen, Christopher, Lou, Min, Staals, Julie, Bordet, Régis, Kandiah, Nagaendran, de Leeuw, Frank-Erik, Simister, Robert, Hendrikse, Jeroen, Kelly, Peter J, Wardlaw, Joanna, Soo, Yannie, Fluri, Felix, Srikanth, Velandai, Calvet, David, Jung, Simon, Kwa, Vincent I H, Engelter, Stefan T, Peters, Nils, Smith, Eric E, Hara, Hideo, Yakushiji, Yusuke, Orken, Dilek Necioglu, Fazekas, Franz, Thijs, Vincent, Heo, Ji Hoe, Mok, Vincent, Veltkamp, Roland, Ay, Hakan, Imaizumi, Toshio, Gomez-Anson, Beatriz, Lau, Kui Kai, Jouvent, Eric, Rothwell, Peter M, Toyoda, Kazunori, Bae, Hee-Joon, Marti-Fabregas, Joan, and Werring, David J

Published
2021
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41. Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries

Author

Mishra, Aniket, Malik, Rainer, Hachiya, Tsuyoshi, Jürgenson, Tuuli, Namba, Shinichi, Posner, Daniel C., Kamanu, Frederick K., Koido, Masaru, Le Grand, Quentin, Shi, Mingyang, He, Yunye, Georgakis, Marios K., Caro, Ilana, Krebs, Kristi, Liaw, Yi-Ching, Vaura, Felix C., Lin, Kuang, Winsvold, Bendik Slagsvold, Srinivasasainagendra, Vinodh, Parodi, Livia, Bae, Hee-Joon, Chauhan, Ganesh, Chong, Michael R., Tomppo, Liisa, Akinyemi, Rufus, Roshchupkin, Gennady V., Habib, Naomi, Jee, Yon Ho, Thomassen, Jesper Qvist, Abedi, Vida, Cárcel-Márquez, Jara, Nygaard, Marianne, Leonard, Hampton L., Yang, Chaojie, Yonova-Doing, Ekaterina, Knol, Maria J., Lewis, Adam J., Judy, Renae L., Ago, Tetsuro, Amouyel, Philippe, Armstrong, Nicole D., Bakker, Mark K., Bartz, Traci M., Bennett, David A., Bis, Joshua C., Bordes, Constance, Børte, Sigrid, Cain, Anael, Ridker, Paul M., Cho, Kelly, Chen, Zhengming, Cruchaga, Carlos, Cole, John W., de Jager, Phil L., de Cid, Rafael, Endres, Matthias, Ferreira, Leslie E., Geerlings, Mirjam I., Gasca, Natalie C., Gudnason, Vilmundur, Hata, Jun, He, Jing, Heath, Alicia K., Ho, Yuk-Lam, Havulinna, Aki S., Hopewell, Jemma C., Hyacinth, Hyacinth I., Inouye, Michael, Jacob, Mina A., Jeon, Christina E., Jern, Christina, Kamouchi, Masahiro, Keene, Keith L., Kitazono, Takanari, Kittner, Steven J., Konuma, Takahiro, Kumar, Amit, Lacaze, Paul, Launer, Lenore J., Lee, Keon-Joo, Lepik, Kaido, Li, Jiang, Li, Liming, Manichaikul, Ani, Markus, Hugh S., Marston, Nicholas A., Meitinger, Thomas, Mitchell, Braxton D., Montellano, Felipe A., Morisaki, Takayuki, Mosley, Thomas H., Nalls, Mike A., Nordestgaard, Børge G., O’Donnell, Martin J., Okada, Yukinori, Onland-Moret, N. Charlotte, Ovbiagele, Bruce, Peters, Annette, Psaty, Bruce M., Rich, Stephen S., Rosand, Jonathan, Sabatine, Marc S., Sacco, Ralph L., Saleheen, Danish, Sandset, Else Charlotte, Salomaa, Veikko, Sargurupremraj, Muralidharan, Sasaki, Makoto, Satizabal, Claudia L., Schmidt, Carsten O., Shimizu, Atsushi, Smith, Nicholas L., Sloane, Kelly L., Sutoh, Yoichi, Sun, Yan V., Tanno, Kozo, Tiedt, Steffen, Tatlisumak, Turgut, Torres-Aguila, Nuria P., Tiwari, Hemant K., Trégouët, David-Alexandre, Trompet, Stella, Tuladhar, Anil Man, Tybjærg-Hansen, Anne, van Vugt, Marion, Vibo, Riina, Verma, Shefali S., Wiggins, Kerri L., Wennberg, Patrik, Woo, Daniel, Wilson, Peter W. F., Xu, Huichun, Yang, Qiong, Yoon, Kyungheon, Millwood, Iona Y., Gieger, Christian, Ninomiya, Toshiharu, Grabe, Hans J., Jukema, J. Wouter, Rissanen, Ina L., Strbian, Daniel, Kim, Young Jin, Chen, Pei-Hsin, Mayerhofer, Ernst, Howson, Joanna M. M., Irvin, Marguerite R., Adams, Hieab, Wassertheil-Smoller, Sylvia, Christensen, Kaare, Ikram, Mohammad A., Rundek, Tatjana, Worrall, Bradford B., Lathrop, G. Mark, Riaz, Moeen, Simonsick, Eleanor M., Kõrv, Janika, França, Paulo H. C., Zand, Ramin, Prasad, Kameshwar, Frikke-Schmidt, Ruth, de Leeuw, Frank-Erik, Liman, Thomas, Haeusler, Karl Georg, Ruigrok, Ynte M., Heuschmann, Peter Ulrich, Longstreth, W. T., Jung, Keum Ji, Bastarache, Lisa, Paré, Guillaume, Damrauer, Scott M., Chasman, Daniel I., Rotter, Jerome I., Anderson, Christopher D., Zwart, John-Anker, Niiranen, Teemu J., Fornage, Myriam, Liaw, Yung-Po, Seshadri, Sudha, Fernández-Cadenas, Israel, Walters, Robin G., Ruff, Christian T., Owolabi, Mayowa O., Huffman, Jennifer E., Milani, Lili, Kamatani, Yoichiro, Dichgans, Martin, and Debette, Stephanie

Published
2022
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44. Cognitive trajectory in the first year after first-ever ischaemic stroke in young adults: the ODYSSEY study

Author

Schellekens, Mijntje M I, primary, Springer, Ravi C S, additional, Boot, Esther M, additional, Verhoeven, Jamie I, additional, Ekker, Merel S, additional, van Alebeek, Mayte E, additional, Brouwers, Paul J A M, additional, Arntz, Renate M, additional, van Dijk, Gert W, additional, Gons, Rob A R, additional, van Uden, Inge W M, additional, den Heijer, Tom, additional, van Tuijl, Julia H, additional, de Laat, Karlijn F, additional, van Norden, Anouk G W, additional, Vermeer, Sarah E, additional, van Zagten, Marian S G, additional, Van Oostenbrugge, Robert J, additional, Wermer, Marieke J H, additional, Nederkoorn, Paul J, additional, van Rooij, Frank G, additional, van den Wijngaard, Ido R, additional, de Kort, Paul L M, additional, De Leeuw, Frank-Erik, additional, Kessels, Roy P C, additional, and Tuladhar, Anil M, additional

Published
2023
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48. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

Author

Harkness, Kirsty, Shaw, Louise, Sword, Jane, Mohd Nor, Azlisham, Sharma, Pankaj, Kelly, Deborah, Harrington, Frances, Randall, Marc, Smith, Matthew, Mahawish, Karim, Elmarim, Abduelbaset, Esisi, Bernard, Cullen, Claire, Nallasivam, Arumug, Price, Christopher, Barry, Adrian, Roffe, Christine, Coyle, John, Hassan, Ahamad, Birns, Jonathan, Cohen, David, Sekaran, Lakshmanan, Parry-Jones, Adrian, Parry, Anthea, Hargroves, David, Proschel, Harald, Datta, Prabel, Darawil, Khaled, Manoj, Aravindakshan, Burn, Mathew, Patterson, Chris, Giallombardo, Elio, Smyth, Nigel, Mansoor, Syed, Anwar, Ijaz, Marsh, Rachel, Ispoglou, Sissi, Chadha, Dinesh, Prabhakaran, Mathuri, Meenakishundaram, Sanjeevikumar, O'Connell, Janice, Scott, Jon, Krishnamurthy, Vinodh, Aghoram, Prasanna, McCormick, Michael, Sprigg, Nikola, O'Mahony, Paul, Cooper, Martin, Choy, Lillian, Wilkinson, Peter, Leach, Simon, Caine, Sarah, Burger, Ilse, Gunathilagan, Gunaratam, Guyler, Paul, Emsley, Hedley, Davis, Michelle, Manawadu, Dulka, Pasco, Kath, Mamun, Maam, Luder, Robert, Sajid, Mahmud, Okwera, James, Warburton, Elizabeth, Saastamoinen, Kari, England, Timothy, Putterill, Janet, Flossman, Enrico, Power, Michael, Dani, Krishna, Mangion, David, Suman, Appu, Corrigan, John, Lawrence, Enas, Vahidassr, Djamil, Shakeshaft, Clare, Brown, Martin, Charidimou, Andreas, Cohen, Hannah, Banerjee, Gargi, Houlden, Henry, White, Mark, Yousry, Tarek, Flossmann, Enrico, Muir, Keith, El-Koussy, Marwan, Gratz, Pascal, Molad, Jeremy, Korczyn, Amos, Kliper, Efrat, Maeder, Philippe, Gass, Achim, Pachai, Chahin, Bracoub, Luc, Douste-Blazy, Marie-Yvonne, Fratacci, Marie Dominique, Vicaut, Eric, Sato, Shoichiro, Miwa, Kaori, Fujita, Kyohei, Ide, Toshihiro, Ma, Henry, Ly, John, Singhal, Shahoo, Chandra, Ronil, Slater, Lee-Anne, Soufan, Cathy, Moran, Christopher, Traenka, Christopher, Thilemann, Sebastian, Fladt, Joachim, Gensicke, Henrik, Bonati, Leo, Kim, Beom Joon, Han, Moon-Ku, Kang, Jihoon, Ko, Eunbin, Yang, Mi Hwa, Jang, Myung Suk, Murphy, Sean, Carty, Fiona, Akijian, Layan, Thornton, John, Schembri, Mark, Douven, Elles, Delgado-Mederos;, Raquel, Marín, Rebeca, Camps-Renom, Pol, Guisado-Alonso, Daniel, Nuñez, Fidel, Medrano-Martorell, Santiago, Merino, Elisa, Iida, Kotaro, Ikeda, Syuhei, Nishihara, Masashi, Irie, Hiroyuki, Demirelli, Derya Selcuk, Medanta, Jayesh Modi, Zerna, Charlotte, Hernández, Maria Valdés, Armitage, Paul, Heye, Anna, Muñoz-Maniega, Susana, Sakka, Eleni, Thrippleton, Michael, Dennis, Martin, Beigneux, Ysoline, Silva, Mauro, Venketasubramanian, Narayanaswamy, Ho, Shu Leung, Cheung, Raymond Tak Fai, Chan, Koon Ho, Teo, Kay Cheong, Hui, Edward, Kwan, Joseph Shiu Kwong, Chang, Richard, Tse, Man Yu, Hoi, Chu Peng, Chan, Chung Yan, Chan, Oi Ling, Cheung, Ryan Hoi Kit, Wong, Edmund Ka Ming, Leung, Kam Tat, Tsang, Suk Fung, Ip, Hing Lung, Ma, Sze Ho, Ma, Karen, Fong, Wing Chi, Li, Siu Hung, Li, Richard, Ng, Ping Wing, Wong, Kwok Kui, Liu, Wenyan, Wong, Lawrence, Ramos, Lino, De Schryver, Els, Jöbsis, Joost, van der Sande, Jaap, Brouwers, Paul, Roos, Yvo, Stam, Jan, Bakker, Stef, Verbiest, Henk, Schoonewille, Wouter, Linn, Cisca, Hertzberger, Leopold, van Gemert, Maarten, Berntsen, Paul, Hendrikse, Jeroen, Nederkoorn, Paul, Mess, Werner, Koudstaal, Peter, Leff, Alexander, Ward, Nicholas, Nachev, Parashkev, Perry, Richard, Ozkan, Hatice, Mitchell, John, Wilson, Duncan, Ambler, Gareth, Lee, Keon-Joo, Lim, Jae-Sung, Shiozawa, Masayuki, Koga, Masatoshi, Li, Linxin, Lovelock, Caroline, Chabriat, Hugues, Hennerici, Michael, Wong, Yuen Kwun, Mak, Henry Ka Fung, Prats-Sánchez, Luis, Martínez-Domeño, Alejandro, Inamura, Shigeru, Yoshifuji, Kazuhisa, Arsava, Ethem Murat, Horstmann, Solveig, Purrucker, Jan, Lam, Bonnie Yin Ka, Wong, Adrian, Kim, Young Dae, Song, Tae-Jin, Schrooten, Maarten, Lemmens, Robin, Eppinger, Sebastian, Gattringer, Thomas, Uysal, Ender, Tanriverdi, Zeynep, Bornstein, Natan M, Assayag, Einor Ben, Hallevi, Hen, Tanaka, Jun, Hara, Hideo, Coutts, Shelagh B, Hert, Lisa, Polymeris, Alexandros, Seiffge, David J, Lyrer, Philippe, Algra, Ale, Kappelle, Jaap, Al-Shahi Salman, Rustam, Jäger, Hans R, Lip, Gregory Y H, Mattle, Heinrich P, Panos, Leonidas D, Mas, Jean-Louis, Legrand, Laurence, Karayiannis, Christopher, Phan, Thanh, Gunkel, Sarah, Christ, Nicolas, Abrigo, Jill, Leung, Thomas, Chu, Winnie, Chappell, Francesca, Makin, Stephen, Hayden, Derek, Williams, David J, Kooi, M Eline, van Dam-Nolen, Dianne H K, Barbato, Carmen, Browning, Simone, Wiegertjes, Kim, Tuladhar, Anil M, Maaijwee, Noortje, Guevarra, Christine, Yatawara, Chathuri, Mendyk, Anne-Marie, Delmaire, Christine, Köhler, Sebastian, van Oostenbrugge, Robert, Zhou, Ying, Xu, Chao, Hilal, Saima, Gyanwali, Bibek, Chen, Christopher, Lou, Min, Staals, Julie, Bordet, Régis, Kandiah, Nagaendran, de Leeuw, Frank-Erik, Simister, Robert, van der Lugt, Aad, Kelly, Peter J, Wardlaw, Joanna M, Soo, Yannie, Fluri, Felix, Srikanth, Velandai, Calvet, David, Jung, Simon, Kwa, Vincent I H, Engelter, Stefan T, Peters, Nils, Smith, Eric E, Yakushiji, Yusuke, Orken, Dilek Necioglu, Fazekas, Franz, Thijs, Vincent, Heo, Ji Hoe, Mok, Vincent, Veltkamp, Roland, Ay, Hakan, Imaizumi, Toshio, Gomez-Anson, Beatriz, Lau, Kui Kai, Jouvent, Eric, Rothwell, Peter M, Toyoda, Kazunori, Bae, Hee-Joon, Marti-Fabregas, Joan, and Werring, David J

Published
2019
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