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Claes Lundström

Adjunct Professor

Presentation

Claes Lundström's primary research focus is to develop methods that enable new levels of accuracy and efficiency within medical imaging. The efforts are concentrated at the crossroads of machine learning, visualization and human-computer interaction in demanding clinical settings.

Lundström's research is carried out within the Center for Medical Image Science and Visualization (CMIV) at Linköping University. He received his PhD degree in 2007 and Docent degree in 2014. Particular recognition has been shown for his contributions to uncertainty visualization and Transfer Function design within volume rendering.

He has since 2012 led the technical side of the digital pathology research at CMIV, being the PI for large national-scale grants. Lundström also leads sizeable efforts in image-based precision orthopedics. From 2017 he is the Arena Director for the Analytic Imaging Diagnostics Arena (AIDA), a national center for research and innovation in Artificial Intelligence based at CMIV.

In parallel with his university efforts, Lundström since 2010 holds the position as Research Director at Sectra AB, where he has worked continuously since 1997 in several leading positions. Many of his academic contributions has segued into commercial products and concrete benefits to society.

Publications

2024

Emilia Ståhlbom, Jesper Molin, Anders Ynnerman, Claes Lundström (2024) Should I make it round? Suitability of circular and linear layouts for comparative tasks with matrix and connective data Computer graphics forum (Print), Vol. 43, Article e15102 (Article in journal) Continue to DOI
Milda Poceviciute, Gabriel Eilertsen, Claes Lundström (2024) Benefits of spatial uncertainty aggregation for segmentation in digital pathology Journal of Medical Imaging, Vol. 11 (Article in journal) Continue to DOI

2023

Fernando Cossío, Haiko Schurz, Mathias Engström, Carl Barck-Holst, Apostolia Tsirikoglou, Claes Lundström, Håkan Gustafsson, Kevin Smith, Sophia Zackrisson, Fredrik Strand (2023) VAI-B: a multicenter platform for the external validation of artificial intelligence algorithms in breast imaging Journal of Medical Imaging, Vol. 10 (Article in journal) Continue to DOI
Emilia Ståhlbom, Jesper Molin, Anders Ynnerman, Claes Lundström (2023) The thorny complexities of visualization research for clinical settings: A case study from genomics FRONTIERS IN BIOINFORMATICS, Vol. 3, Article 1112649 (Article in journal) Continue to DOI
Milda Poceviciute, Gabriel Eilertsen, Claes Lundström (2023) Spatial uncertainty aggregation for false negatives detection in breast cancer metastases segmentation MEDICAL IMAGING 2023, Article 124710W (Conference paper) Continue to DOI

News

Publications

2024

Emilia Ståhlbom, Jesper Molin, Anders Ynnerman, Claes Lundström (2024) Should I make it round? Suitability of circular and linear layouts for comparative tasks with matrix and connective data Computer graphics forum (Print), Vol. 43, Article e15102 (Article in journal) Continue to DOI
Milda Poceviciute, Gabriel Eilertsen, Claes Lundström (2024) Benefits of spatial uncertainty aggregation for segmentation in digital pathology Journal of Medical Imaging, Vol. 11 (Article in journal) Continue to DOI

2023

Fernando Cossío, Haiko Schurz, Mathias Engström, Carl Barck-Holst, Apostolia Tsirikoglou, Claes Lundström, Håkan Gustafsson, Kevin Smith, Sophia Zackrisson, Fredrik Strand (2023) VAI-B: a multicenter platform for the external validation of artificial intelligence algorithms in breast imaging Journal of Medical Imaging, Vol. 10 (Article in journal) Continue to DOI
Emilia Ståhlbom, Jesper Molin, Anders Ynnerman, Claes Lundström (2023) The thorny complexities of visualization research for clinical settings: A case study from genomics FRONTIERS IN BIOINFORMATICS, Vol. 3, Article 1112649 (Article in journal) Continue to DOI
Milda Poceviciute, Gabriel Eilertsen, Claes Lundström (2023) Spatial uncertainty aggregation for false negatives detection in breast cancer metastases segmentation MEDICAL IMAGING 2023, Article 124710W (Conference paper) Continue to DOI