Jens Kleesiek
Jens Kleesiek
Computational Radiology, German Cancer Research Center (DKFZ)
Verified email at dkfz.de
TitleCited byYear
IKK mediates ischemia-induced neuronal death
O Herrmann, B Baumann, R De Lorenzi, S Muhammad, W Zhang, ...
Nature medicine 11 (12), 1322-1329, 2005
2622005
Deep MRI brain extraction: a 3D convolutional neural network for skull stripping
J Kleesiek, G Urban, A Hubert, D Schwarz, K Maier-Hein, M Bendszus, ...
NeuroImage 129, 460-469, 2016
1892016
Multi-modal Brain Tumor Segmentation using Deep Convolutional Neural Networks
G Urban, M Bendszus, FA Hamprecht, J Kleesiek
MICCAI Brain Tumor Segmentation Challenge (BraTS) Workshop, 31-35, 2014
1102014
DALSA: Domain Adaptation for Supervised Learning from Sparsely Annotated MR Images.
M Goetz, C Weber, F Binczyk, J Polanska, R Tarnawski, ...
IEEE transactions on medical imaging, 2015
362015
Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression
A Biller, S Badde, A Nagel, JO Neumann, W Wick, A Hertenstein, ...
American Journal of Neuroradiology 37 (1), 66-73, 2016
342016
ilastik for Multi-modal Brain Tumor Segmentation
J Kleesiek, A Biller, G Urban, U Köthe, M Bendszus, FA Hamprecht
MICCAI Brain Tumor Segmentation Challenge (BraTS) Workshop, 12-17, 2014
322014
Single-drop optimization of protein crystallization
A Meyer, K Dierks, D Hilterhaus, T Klupsch, P Mühlig, J Kleesiek, ...
Acta Crystallographica Section F: Structural Biology and Crystallization …, 2012
202012
A Transgenic Approach to Identify Thyroxine Transporter‐Expressing Structures in Brain Development
MF Lang, S Salinin, DA Ridder, J Kleesiek, J Hroudova, S Berger, ...
Journal of neuroendocrinology 23 (12), 1194-1203, 2011
182011
Sodium MRI in multiple sclerosis is compatible with intracellular sodium accumulation and inflammation-induced hyper-cellularity of acute brain lesions
A Biller, I Pflugmann, S Badde, R Diem, B Wildemann, AM Nagel, ...
Scientific reports 6, 31269, 2016
112016
Virtual raters for reproducible and objective assessments in radiology
J Kleesiek, J Petersen, M Döring, K Maier-Hein, U Köthe, W Wick, ...
Scientific reports 6, 25007, 2016
92016
Action-driven perception for a humanoid
J Kleesiek, S Badde, S Wermter, AK Engel
International Conference on Agents and Artificial Intelligence, 83-99, 2012
62012
What do Objects Feel Like?-Active Perception for a Humanoid Robot.
J Kleesiek, S Badde, S Wermter, AK Engel
ICAART (1), 64-73, 2012
32012
Intuitive Interaction: Tapping into body skills to find rich and intuitive interaction methods for Virtual Reality
S Beckhaus, J Kleesiek
CHI ’11 Workshop 27 – Embodied Interaction: Theory and Practice in HCI, 128-132, 2011
32011
Can Virtual Contrast Enhancement in Brain MRI Replace Gadolinium?: A Feasibility Study
J Kleesiek, JN Morshuis, F Isensee, K Deike-Hofmann, D Paech, ...
Investigative radiology 54 (10), 653-660, 2019
22019
Wie funktioniert maschinelles Lernen?
J Kleesiek, JM Murray, C Strack, G Kaissis, R Braren
Der Radiologe, 1-8, 2019
12019
Wie funktioniert Radiomics?
JM Murray, G Kaissis, R Braren, J Kleesiek
Der Radiologe, 1-9, 2019
12019
Reward-driven learning of sensorimotor laws and visual features
J Kleesiek, AK Engel, C Weber, S Wermter
2011 IEEE International Conference on Development and Learning (ICDL) 2, 1-6, 2011
12011
RNA secondary structure prediction using a self‐consistent mean field approach
J Kleesiek, AE Torda
Journal of computational chemistry 31 (6), 1135-1142, 2010
12010
Künstliche Intelligenz und maschinelles Lernen in der onkologischen Bildgebung
J Kleesiek, JM Murray, G Kaissis, R Braren
Der Onkologe, 1-6, 0
1
A primer on radiomics
JM Murray, G Kaissis, R Braren, J Kleesiek
Der Radiologe, 2019
2019
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Articles 1–20