Shadi Albarqouni

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Citations	3767	3744
h-index	20	20
i10-index	38	38

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Nassir NavabProfessor of Computer Science, Technische Universität MünchenVerified email at cs.tum.edu
Christoph BaurDirector Software Imaging Products at Rohde & Schwarz GmbH & Co. KGVerified email at tum.de
Bene WiestlerDept. of Neuroradiology, TUMVerified email at tum.de
Slobodan IlicSenior Key Expert Research Scientist, Siemens AG and Adjunct Professor at TUMVerified email at in.tum.de
Vasileios BelagiannisUlm UniversityVerified email at uni-ulm.de
Nicola RiekeNVIDIAVerified email at nvidia.com
Irene EspositoProfessor of Pathology, University of Düsseldorf, GermanyVerified email at med.uni-duesseldorf.de
Fausto MilletarìJohnson&JohnsonVerified email at its.jnj.com
Andrew TraskDeepMind, University of Oxford, and OpenMinedVerified email at google.com
Ronald M. Summers, MD, PhDNational Institutes of Health Clinical CenterVerified email at nih.gov
Sebastien OurselinProfessor of Healthcare Engineering, King's College LondonVerified email at kcl.ac.uk
Bram van GinnekenProfessor of Medical Image Analysis, Radboud UniversityVerified email at radboudumc.nl
Andreas K. MaierUniversity of Erlangen-NurembergVerified email at fau.de
Lena Maier-HeinProfessor, German Cancer Research CenterVerified email at dkfz.de
Carsten MarrInstitute of Computational Biology, Helmholtz Zentrum MünchenVerified email at helmholtz-muenchen.de
Daniel RueckertTechnical University of Munich and Imperial College LondonVerified email at tum.de
Leonidas GuibasProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Ender KonukogluETH ZurichVerified email at vision.ee.ethz.ch
Danail StoyanovProfessor of Robot Vision, University College LondonVerified email at ucl.ac.uk
Guillaume LandryDepartment of Radiation Oncology, University Hospital, LMU MunichVerified email at med.uni-muenchen.de

Shadi Albarqouni

AI Group Leader at Helmholtz Zentrum München | TUM Junior Fellow | fmr. Imperial College and ETH

Verified email at helmholtz-muenchen.de - Homepage

Machine Learning Deep Learning Medical Imaging Medical Image Analysis Federated Learning


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Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer BE Bejnordi, M Veta, PJ Van Diest, B Van Ginneken, N Karssemeijer, ... Jama 318 (22), 2199-2210, 2017	1423	2017
Aggnet: deep learning from crowds for mitosis detection in breast cancer histology images S Albarqouni, C Baur, F Achilles, V Belagiannis, S Demirci, N Navab IEEE transactions on medical imaging 35 (5), 1313-1321, 2016	436	2016
Structure-preserving color normalization and sparse stain separation for histological images A Vahadane, T Peng, A Sethi, S Albarqouni, L Wang, M Baust, K Steiger, ... IEEE transactions on medical imaging 35 (8), 1962-1971, 2016	244	2016
Deep autoencoding models for unsupervised anomaly segmentation in brain MR images C Baur, B Wiestler, S Albarqouni, N Navab International MICCAI Brainlesion Workshop, 161-169, 2018	225	2018
The future of digital health with federated learning N Rieke, J Hancox, W Li, F Milletari, H Roth, S Albarqouni, S Bakas, ... npj Digital Medicine 3 (119), 2020	150	2020
GANs for medical image analysis S Kazeminia, C Baur, A Kuijper, B van Ginneken, N Navab, S Albarqouni, ... Artificial Intelligence in Medicine, 101938, 2020	143	2020
Staingan: Stain style transfer for digital histological images MT Shaban, C Baur, N Navab, S Albarqouni 2019 Ieee 16th international symposium on biomedical imaging (Isbi 2019 …, 2019	126	2019
Semi-supervised deep learning for fully convolutional networks C Baur, S Albarqouni, N Navab International Conference on Medical Image Computing and Computer-Assisted …, 2017	90	2017
Generating highly realistic images of skin lesions with GANs C Baur, S Albarqouni, N Navab OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy …, 2018	74*	2018
An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy S Ali, F Zhou, B Braden, A Bailey, S Yang, G Cheng, P Zhang, X Li, ... Scientific reports 10 (1), 1-15, 2020	62	2020
Capsule networks against medical imaging data challenges A Jiménez-Sánchez, S Albarqouni, D Mateus Intravascular Imaging and Computer Assisted Stenting and Large-Scale …, 2018	58	2018
Structure-preserved color normalization for histological images A Vahadane, T Peng, S Albarqouni, M Baust, K Steiger, AM Schlitter, ... 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 1012-1015, 2015	50	2015
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study C Baur, S Denner, B Wiestler, N Navab, S Albarqouni Medical Image Analysis 101952, 2021	48	2021
Inceptiongcn: receptive field aware graph convolutional network for disease prediction A Kazi, S Shekarforoush, SA Krishna, H Burwinkel, G Vivar, K Kortüm, ... International Conference on Information Processing in Medical Imaging, 73-85, 2019	37	2019
Deep learning and data labeling for medical applications G Carneiro, D Mateus, L Peter, A Bradley, JMRS Tavares, V Belagiannis, ...	36	2016
Image-to-images translation for multi-task organ segmentation and bone suppression in chest x-ray radiography M Eslami, S Tabarestani, S Albarqouni, E Adeli, N Navab, M Adjouadi IEEE transactions on medical imaging 39 (7), 2553-2565, 2020	30	2020
Domain and geometry agnostic CNNs for left atrium segmentation in 3D ultrasound MA Degel, N Navab, S Albarqouni International Conference on Medical Image Computing and Computer-Assisted …, 2018	28	2018
Parsing human skeletons in an operating room V Belagiannis, X Wang, HBB Shitrit, K Hashimoto, R Stauder, Y Aoki, ... Machine Vision and Applications 27 (7), 1035-1046, 2016	26	2016
Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer A Lahiani, N Navab, S Albarqouni, E Klaiman Medical Image Computing and Computer Assisted Intervention, 568-576, 2019	25*	2019
Fusing unsupervised and supervised deep learning for white matter lesion segmentation C Baur, B Wiestler, S Albarqouni, N Navab International Conference on Medical Imaging with Deep Learning, 63-72, 2019	21	2019

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