Követés
Claes Lundström
Claes Lundström
Center for Medical Image Science and Visualization, Linköping University
E-mail megerősítve itt: liu.se - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Measuring domain shift for deep learning in histopathology
K Stacke, G Eilertsen, J Unger, C Lundström
IEEE journal of biomedical and health informatics 25 (2), 325-336, 2020
2222020
Implementation of large-scale routine diagnostics using whole slide imaging in Sweden: Digital pathology experiences 2006-2013
S Thorstenson, J Molin, C Lundström
Journal of pathology informatics 5 (1), 14, 2014
1992014
Uncertainty visualization in medical volume rendering using probabilistic animation
C Lundström, P Ljung, A Persson, A Ynnerman
IEEE transactions on visualization and computer graphics 13 (6), 1648-1655, 2007
1992007
Local histograms for design of transfer functions in direct volume rendering
C Lundstrom, P Ljung, A Ynnerman
IEEE Transactions on visualization and computer graphics 12 (6), 1570-1579, 2006
1662006
Multi-touch table system for medical visualization: application to orthopedic surgery planning
C Lundstrom, T Rydell, C Forsell, A Persson, A Ynnerman
Visualization and Computer Graphics, IEEE Transactions on 17 (12), 1775-1784, 2011
1102011
Full body virtual autopsies using a state-of-the-art volume rendering pipeline
P Ljung, C Winskog, A Persson, C Lundström, A Ynnerman
Visualization and Computer Graphics, IEEE Transactions on 12 (5), 869-876, 2006
1032006
Deep learning nuclei detection: A simple approach can deliver state-of-the-art results
H Höfener, A Homeyer, N Weiss, J Molin, CF Lundström, HK Hahn
Computerized Medical Imaging and Graphics 70, 43-52, 2018
1002018
Transfer function based adaptive decompression for volume rendering of large medical data sets
P Ljung, C Lundstrom, A Ynnerman, K Museth
Volume Visualization and Graphics, 2004 IEEE Symposium on, 25-32, 2004
952004
Towards grading gleason score using generically trained deep convolutional neural networks
H Källén, J Molin, A Heyden, C Lundström, K Åström
Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on, 1163-1167, 2016
902016
Presenting artificial intelligence, deep learning, and machine learning studies to clinicians and healthcare stakeholders: an introductory reference with a guideline and a …
J Olczak, J Pavlopoulos, J Prijs, FFA Ijpma, JN Doornberg, C Lundström, ...
Acta orthopaedica 92 (5), 513-525, 2021
872021
A closer look at domain shift for deep learning in histopathology
K Stacke, G Eilertsen, J Unger, C Lundström
arXiv preprint arXiv:1909.11575, 2019
792019
Multiresolution interblock interpolation in direct volume rendering
P Ljung, C Lundström, A Ynnerman
Proceedings of the Eighth Joint Eurographics/IEEE VGTC conference on …, 2006
712006
Survey of XAI in digital pathology
M Pocevičiūtė, G Eilertsen, C Lundström
Artificial intelligence and machine learning for digital pathology: state-of …, 2020
682020
State‐of‐the‐art of visualization in post‐mortem imaging
C Lundström, A Persson, S Ross, P Ljung, S Lindholm, F Gyllensvärd, ...
Apmis 120 (4), 316-326, 2012
642012
Fully automatic measurements of axial vertebral rotation for assessment of spinal deformity in idiopathic scoliosis
D Forsberg, C Lundström, M Andersson, L Vavruch, H Tropp, H Knutsson
Physics in Medicine and Biology 58 (6), 1775, 2013
452013
Integrated Diagnostics: The Computational Revolution Catalyzing Cross-disciplinary Practices in Radiology, Pathology, and Genomics
CF Lundström, HL Gilmore, PR Ros
Radiology 285 (1), 12-15, 2017
422017
The a-histogram: Using Spatial Coherence to Enhance Histograms and Transfer Function Design
C Lundström, A Ynnerman, P Ljung, A Persson, H Knutsson
Proceedings of Eurographics/IEEE-VGTC Symposium on Visualization, 2006
42*2006
Annotations, ontologies, and whole slide images–Development of an annotated ontology-driven whole slide image library of normal and abnormal human tissue
K Lindman, JF Rose, M Lindvall, C Lundstrom, D Treanor
Journal of Pathology Informatics 10 (1), 22, 2019
342019
Extending and Simplifying Transfer Function Design in Medical Volume Rendering Using Local Histograms.
C Lundström, P Ljung, A Ynnerman
EuroVis, 263-270, 2005
342005
Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications
K Stacke, J Unger, C Lundström, G Eilertsen
arXiv preprint arXiv:2112.05760, 2021
302021
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Cikkek 1–20