Hongwei Bran Li
Hongwei Bran Li
Dept. of Computer Science, Techinical University of Munich / University of Zurich
Verified email at - Homepage
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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
The liver tumor segmentation benchmark (lits)
P Bilic, PF Christ, H Li, E Vorontsov, G Chlebus, H Chen, Q Dou, CW Fu, ...
arXiv preprint arXiv:1901.04056, 2019
Fully convolutional network ensembles for white matter hyperintensities segmentation in MR images
H Li, G Jiang, J Zhang, R Wang, Z Wang, WS Zheng, B Menze
NeuroImage 183, 650-665, 2018
Standardized assessment of automatic segmentation of white matter hyperintensities and results of the WMH segmentation challenge
HJ Kuijf, JM Biesbroek, J De Bresser, R Heinen, S Andermatt, M Bento, ...
IEEE transactions on medical imaging 38 (11), 2556-2568, 2019
Knowledge-aided convolutional neural network for small organ segmentation
Y Zhao, H Li, S Wan, A Sekuboyina, X Hu, G Tetteh, M Piraud, B Menze
IEEE journal of biomedical and health informatics 23 (4), 1363-1373, 2019
Automated whole-body bone lesion detection for multiple myeloma on 68Ga-pentixafor PET/CT imaging using deep learning methods
L Xu, G Tetteh, J Lipkova, Y Zhao, H Li, P Christ, M Piraud, A Buck, K Shi, ...
Contrast media & molecular imaging 2018, 2018
Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge
VM Campello, P Gkontra, C Izquierdo, C Martín-Isla, A Sojoudi, PM Full, ...
IEEE Transactions on Medical Imaging 40 (12), 3543-3554, 2021
DiamondGAN: Unified Multi-modal Generative Adversarial Networks for MRI Sequences Synthesis
H Li, JC Paetzold, A Sekuboyina, F Kofler, J Zhang, JS Kirschke, ...
MICCAI 2019, 795-803, 2019
VerSe: a vertebrae labelling and segmentation benchmark for multi-detector CT images
A Sekuboyina, ME Husseini, A Bayat, M Löffler, H Liebl, H Li, G Tetteh, ...
Medical image analysis 73, 102166, 2021
Deep learning-enabled multi-organ segmentation in whole-body mouse scans
O Schoppe, C Pan, J Coronel, H Mai, Z Rong, MI Todorov, A Müskes, ...
Nature communications 11 (1), 1-14, 2020
Deep-Learning Generated Synthetic Double Inversion Recovery Images Improve Multiple Sclerosis Lesion Detection
T Finck*, H Li*, L Grundl, P Eichinger, M Bussas, M Mühlau, B Menze, ...
Investigative Radiology 55 (5), 318-323, 2020
Cardiac segmentation on late gadolinium enhancement MRI: a benchmark study from multi-sequence cardiac MR segmentation challenge
X Zhuang, J Xu, X Luo, C Chen, C Ouyang, D Rueckert, VM Campello, ...
arXiv preprint arXiv:2006.12434, 2020
Differential diagnosis for pancreatic cysts in ct scans using densely-connected convolutional networks
H Li, M Reichert, K Lin, N Tselousov, R Braren, D Fu, R Schmid, J Li, ...
EMBC 2019, 2095-2098, 2019
Automatic brain structures segmentation using deep residual dilated u-net
H Li, A Zhygallo, B Menze
MICCAI Brainlesion Workshop, 385-393, 2018
Hierarchical multi-class segmentation of glioma images using networks with multi-level activation function
X Hu, H Li, Y Zhao, C Dong, BH Menze, M Piraud
MICCAI Brainlesion Workshop, 116-127, 2018
HEp-2 specimen classification via deep CNNs and pattern histogram
H Li, H Huang, WS Zheng, X Xie, J Zhang
ICPR 2016, 2145-2149, 2016
Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective
AB Qasim, I Ezhov, S Shit, O Schoppe, JC Paetzold, A Sekuboyina, ...
MIDL 2020, 2020
Cross-view Relation Networks for Mammogram Mass Detection
J Ma, S Liang, X Li, H Li, BH Menze, R Zhang, WS Zheng
ICPR 2020, 2019
Coarse-to-fine adversarial networks and zone-based uncertainty analysis for NK/T-cell lymphoma segmentation in CT/PET images
X Hu, R Guo, J Chen, H Li, D Waldmannstetter, Y Zhao, B Li, K Shi, ...
IEEE journal of biomedical and health informatics 24 (9), 2599-2608, 2020
Multi-scale convolutional-stack aggregation for robust white matter hyperintensities segmentation
H Li, J Zhang, M Muehlau, J Kirschke, B Menze
MICCAI Brainlesion Workshop 2018, 199-207, 2018
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