Academic Career and Research Areas

Tobias Lasser (*1979) works in the area of computational imaging with applications in medicine and biology. His research focuses on the areas of solving inverse problems of novel tomographic imaging modalities, such as anisotropic X-ray darkfield tomography or light field microscopy, as well as clinical decision support on the basis of multi-modal data.

Tobias Lasser studied Informatics (2006) and Mathematics (2008) at TUM. He achieved his PhD in Informatics at TUM in 2011, and completed his habilitation in Informatics at TUM in 2017. In 2024, he was appointed to außerplanmässiger Professer at TUM.

Awards

  • Outstanding editorial board member award by the IEEE Signal Processing Society (2023)
  • Best poster award at the Fully3D Conference (2021)
  • CeDoSIA supervisory award for the best supervision of PhD candidates at TUM Informatics (2021)
  • TeachInf teaching award for best mandatory course at TUM Informatics (2021)
  • Best paper award at the Digital Heritage Conference (2015)

T. Cheslerean-Boghiu, F. Hofmann, M. Schultheiß, F. Pfeiffer, D. Pfeiffer, T. Lasser. WNet: A Data-driven Dual-domain Denoising Model for Sparse-view Computed Tomography with a Trainable Reconstruction Layer. IEEE Transactions on Computational Imaging 9, 2023.

Abstract

P. Tang, X. Yan, Y. Nan, S. Xiang, S. Krammer, T. Lasser. FusionM4Net: A multi-stage multi-modal learning algorithm for multi-label skin lesion classification. Medical Image Analysis 76, 2022.

Abstract

A. Stefanoiu, J. Page, P. Symvoulidis, G. Westmeyer, T. Lasser. Artifact-free deconvolution in light field microscopy. Optics Express 27, 2019.

Abstract

M. Wieczorek, F. Schaff, F. Pfeiffer, T. Lasser. Anisotropic X-ray Dark-Field Tomography: A Continuous Model and its Discretization. Physical Review Letters 117, 2016.

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J. Vogel, F. Schaff, A. Fehringer, C. Jud, M. Wieczorek, F. Pfeiffer, T. Lasser. Constrained X-ray tensor tomography reconstruction. Optics Express 23, 2015.

Abstract

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