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ORCIDClaes Lundström
Person information
- affiliation: Linköping University, Center for Medical Image Science and Visualization, Sweden
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Books and Theses
- 2007
[b1]Claes Lundström:
Efficient Medical Volume Visualization : An Approach Based on Domain Knowledge. Linköping University, Sweden, 2007
Journal Articles
- 2024
- [j16]Emilia Ståhlbom
, Jesper Molin, Anders Ynnerman, Claes Lundström:
Should I make it round? Suitability of circular and linear layouts for comparative tasks with matrix and connective data. Comput. Graph. Forum 43(3) (2024) - 2023
- [j15]Emilia Ståhlbom, Jesper Molin, Anders Ynnerman, Claes Lundström:
The thorny complexities of visualization research for clinical settings: A case study from genomics. Frontiers Bioinform. 3 (2023) - [j14]Claes Lundström, Martin Lindvall:
Mapping the Landscape of Care Providers' Quality Assurance Approaches for AI in Diagnostic Imaging. J. Digit. Imaging 36(2): 379-387 (2023) - 2021
- [j13]Caroline Bivik Stadler, Martin Lindvall, Claes Lundström, Anna Bodén, Karin Lindman, Jeronimo Rose, Darren Treanor, Johan Blomma, Karin Stacke, Nicolas Pinchaud, Martin Hedlund, Filip Landgren, Mischa Woisetschläger, Daniel Forsberg:
Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training. J. Digit. Imaging 34(1): 105-115 (2021) - [j12]Karin Stacke, Gabriel Eilertsen, Jonas Unger, Claes Lundström:
Measuring Domain Shift for Deep Learning in Histopathology. IEEE J. Biomed. Health Informatics 25(2): 325-336 (2021) - 2019
- [j11]Martin Falk, Anders Ynnerman, Darren Treanor, Claes Lundström:
Interactive Visualization of 3D Histopathology in Native Resolution. IEEE Trans. Vis. Comput. Graph. 25(1): 1008-1017 (2019) - 2018
- [j10]Henning Höfener, André Homeyer, Nick Weiss, Jesper Molin, Claes F. Lundström, Horst K. Hahn:
Deep learning nuclei detection: A simple approach can deliver state-of-the-art results. Comput. Medical Imaging Graph. 70: 43-52 (2018) - 2016
- [j9]Chunliang Wang, Claes Lundström:
CT scan range estimation using multiple body parts detection: let PACS learn the CT image content. Int. J. Comput. Assist. Radiol. Surg. 11(2): 317-325 (2016) - 2014
- [j8]Daniel Forsberg, Claes Lundström, Hans Knutsson:
Eigenspine: Computing the correlation between measures describing vertebral pose for patients with adolescent idiopathic scoliosis. Comput. Medical Imaging Graph. 38(7): 549-557 (2014) - 2013
- [j7]Claes Lundström:
vPSNR: a visualization-aware image fidelity metric tailored for diagnostic imaging. Int. J. Comput. Assist. Radiol. Surg. 8(3): 437-450 (2013) - 2011
- [j6]Claes Lundström, Thomas Rydell, Camilla Forsell, Anders Persson, Anders Ynnerman:
Multi-Touch Table System for Medical Visualization: Application to Orthopedic Surgery Planning. IEEE Trans. Vis. Comput. Graph. 17(12): 1775-1784 (2011) - 2010
- [j5]Stefan Lindholm, Patric Ljung, Claes Lundström, Anders Persson, Anders Ynnerman:
Spatial Conditioning of Transfer Functions Using Local Material Distributions. IEEE Trans. Vis. Comput. Graph. 16(6): 1301-1310 (2010) - 2007
- [j4]Patric Ljung, Calle Winskog, Anders Persson, Claes Lundström, Anders Ynnerman:
Forensic Virtual Autopsies by Direct Volume Rendering [DSP Applications]. IEEE Signal Process. Mag. 24(6): 112-116 (2007) - [j3]Claes Lundström, Patric Ljung, Anders Persson, Anders Ynnerman:
Uncertainty Visualization in Medical Volume Rendering Using Probabilistic Animation. IEEE Trans. Vis. Comput. Graph. 13(6): 1648-1655 (2007) - 2006
- [j2]Patric Ljung, Calle Winskog, Anders Persson, Claes Lundström, Anders Ynnerman:
Full Body Virtual Autopsies using a State-of-the-art Volume Rendering Pipeline. IEEE Trans. Vis. Comput. Graph. 12(5): 869-876 (2006) - [j1]Claes Lundström, Patric Ljung, Anders Ynnerman:
Local Histograms for Design of Transfer Functions in Direct Volume Rendering. IEEE Trans. Vis. Comput. Graph. 12(6): 1570-1579 (2006)
Conference and Workshop Papers
- 2023
- [c22]Milda Poceviciute, Gabriel Eilertsen, Stina Garvin, Claes Lundström:
Detecting Domain Shift in Multiple Instance Learning for Digital Pathology Using Fréchet Domain Distance. MICCAI (5) 2023: 157-167 - 2022
- [c21]Emilia Ståhlbom, Jesper Molin, Claes Lundström, Anders Ynnerman:
Visualization Challenges of Variant Interpretation in Multiscale NGS Data. EuroVis (Posters) 2022: 107-109 - 2021
- [c20]Milda Poceviciute, Gabriel Eilertsen, Claes Lundström:
Unsupervised Anomaly Detection In Digital Pathology Using GANs. ISBI 2021: 1878-1882 - [c19]Martin Lindvall, Claes Lundström, Jonas Löwgren:
Rapid Assisted Visual Search: Supporting Digital Pathologists with Imperfect AI. IUI 2021: 504-513 - 2020
- [c18]Karin Stacke, Claes Lundström, Gabriel Eilertsen:
Evaluation of Contrastive Predictive Coding for Histopathology Applications. ML4H@NeurIPS 2020: 328-340 - [c17]Martin Falk, Patric Ljung, Claes Lundström, Anders Ynnerman, Ingrid Hotz:
Feature Exploration using Local Frequency Distributions in Computed Tomography Data. VCBM 2020: 13-24 - 2017
- [c16]Martin Falk, Ingrid Hotz, Patric Ljung, Darren Treanor, Anders Ynnerman, Claes Lundström:
Transfer Function design toolbox for full-color volume datasets. PacificVis 2017: 171-179 - 2016
- [c15]Hanna Källén, Jesper Molin, Anders Heyden, Claes Lundström, Kalle Åström:
Towards grading gleason score using generically trained deep convolutional neural networks. ISBI 2016: 1163-1167 - [c14]Jesper Molin, Pawel W. Wozniak, Claes Lundström, Darren Treanor, Morten Fjeld:
Understanding Design for Automated Image Analysis in Digital Pathology. NordiCHI 2016: 58 - 2015
- [c13]Anders Ynnerman, Thomas Rydell, Anders Persson, Aron Ernvik, Camilla Forsell, Patric Ljung, Claes Lundström:
Multi-Touch Table System for Medical Visualization. Eurographics (Dirk Bartz Prize) 2015: 9-12 - 2014
- [c12]Jesper Molin, Kavitha Shaga Devan, Karin Wårdell, Claes Lundström:
Feature-enhancing zoom to facilitate Ki-67 hot spot detection. Medical Imaging: Digital Pathology 2014: 90410W - [c11]Stefan Lindholm, Daniel Forsberg, Anders Ynnerman, Hans Knutsson, Mats T. Andersson, Claes Lundström:
Towards Clinical Deployment of Automated Anatomical Regions-Of-Interest. VCBM 2014: 137-143 - 2013
- [c10]Freddie Åström, Michael Felsberg, George Baravdish, Claes Lundström:
Targeted Iterative Filtering. SSVM 2013: 1-11 - 2011
- [c9]Claes Lundström, Anders Persson:
Characterizing Visual Analytics in Diagnostic Imaging. EuroVA@EuroVis 2011 - [c8]Daniel Forsberg, Claes Lundström, Mats T. Andersson, Hans Knutsson:
Model-Based Transfer Functions for Efficient Visualization of Medical Image Volumes. SCIA 2011: 592-603 - 2010
- [c7]Isabella Scandurra, Camilla Forsell, Anders Ynnerman, Patric Ljung, Claes Lundström, Anders Persson:
Advancing the State-of-the-Art for Virtual Autopsies - Initial Forensic Workflow Study. MedInfo 2010: 639-643 - 2006
- [c6]Claes Lundström, Patric Ljung, Anders Ynnerman:
Multi-Dimensional Transfer Function Design Using Sorted Histograms. VG@SIGGRAPH 2006: 1-8 - [c5]Karljohan Lundin, Claes Lundström, Matthew Cooper, Anders Ynnerman:
Enabling Haptic Interaction with Volumetric MRI Data Through Knowledge-based Tissue Separation. VG@SIGGRAPH 2006: 75-78 - [c4]Claes Lundström, Anders Ynnerman, Patric Ljung, Anders Persson, Hans Knutsson:
The alpha -histogram: Using Spatial Coherence to Enhance Histograms and Transfer Function Design. EuroVis 2006: 227-234 - [c3]Patric Ljung, Claes Lundström, Anders Ynnerman:
Multiresolution Interblock Interpolation in Direct Volume Rendering. EuroVis 2006: 259-266 - 2005
- [c2]Claes Lundström, Patric Ljung, Anders Ynnerman:
Extending and Simplifying Transfer Function Design in Medical Volume Rendering Using Local Histograms. EuroVis 2005: 263-270 - 2004
- [c1]Patric Ljung, Claes Lundström, Anders Ynnerman, Ken Museth:
Transfer Function Based Adaptive Decompression for Volume Rendering of Large Medical Data Sets. VolVis 2004: 25-32
Parts in Books or Collections
- 2020
- [p1]Milda Poceviciute, Gabriel Eilertsen, Claes Lundström:
Survey of XAI in Digital Pathology. AI and ML for Digital Pathology 2020: 56-88
Editorship
- 2023
- [e1]Claes Lundström, Daniel Jönsson, Ingrid Hotz, Martin Falk:
VCBM 2023: Eurographics Workshop on Visual Computing for Biology and Medicine, Norrköping, Sweden, September 20-22, 2023. Eurographics Association 2023, ISBN 978-3-03868-216-5 [contents]
Informal and Other Publications
- 2024
- [i8]Milda Poceviciute, Gabriel Eilertsen, Stina Garvin, Claes Lundström:
Detecting Domain Shift in Multiple Instance Learning for Digital Pathology Using Fréchet Domain Distance. CoRR abs/2405.09934 (2024) - 2021
- [i7]Milda Poceviciute, Gabriel Eilertsen, Claes Lundström:
Unsupervised anomaly detection in digital pathology using GANs. CoRR abs/2103.08945 (2021) - [i6]Gabriel Eilertsen, Apostolia Tsirikoglou, Claes Lundström, Jonas Unger:
Ensembles of GANs for synthetic training data generation. CoRR abs/2104.11797 (2021) - [i5]Karin Stacke, Jonas Unger, Claes Lundström, Gabriel Eilertsen:
Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications. CoRR abs/2112.05760 (2021) - [i4]Milda Poceviciute, Gabriel Eilertsen, Sofia Jarkman, Claes Lundström:
Can uncertainty boost the reliability of AI-based diagnostic methods in digital pathology? CoRR abs/2112.09693 (2021) - 2020
- [i3]Milda Poceviciute, Gabriel Eilertsen, Claes Lundström:
Survey of XAI in digital pathology. CoRR abs/2008.06353 (2020) - 2019
- [i2]Karin Stacke, Gabriel Eilertsen, Jonas Unger, Claes Lundström:
A Closer Look at Domain Shift for Deep Learning in Histopathology. CoRR abs/1909.11575 (2019) - 2016
- [i1]Jesper Molin, Anna Bodén, Darren Treanor, Morten Fjeld, Claes Lundström:
Scale Stain: Multi-Resolution Feature Enhancement in Pathology Visualization. CoRR abs/1610.04141 (2016)
Coauthor Index
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