Raf Van de Plas (Presenter)
Delft University of Technology
Bio: Raf Van de Plas is assistant professor at the Delft University of Technology (TU Delft) in the Netherlands. At the Delft Center for Systems and Control, he works on computational analysis of molecular imaging modalities such as imaging mass spectrometry and microscopy. He holds an adjunct assistant professor position in biochemistry at Vanderbilt University School of Medicine in Nashville, TN. He holds a PhD in Engineering (KU Leuven, 2010), an MSc in Industrial Engineering (Group T, 2002), and an MSc in Artificial Intelligence (KU Leuven, 2003). Before his appointment at TU Delft, he held a research faculty position at the Mass Spectrometry Research Center at Vanderbilt University with Dr. Richard Caprioli. His research focuses on the interface between (i) mathematical engineering and machine learning; (ii) analytical chemistry and instrumentation; and (iii) life sciences and medicine.
Authorship: Raf Van de Plas (1,2), Jeffrey Spraggins (2), Junhai Yang (2), and Richard M. Caprioli (2)
(1) Delft Center for Systems and Control, Delft University of Technology, Delft, Netherlands, (2) Mass Spectrometry Research Center and the Department of Biochemistry, Vanderbilt University, Nashville
| Short Abstract Medical studies increasingly employ a multitude of different imaging technologies to answer a specific biological question. A growing number of such multi-modal imaging studies include Imaging Mass Spectrometry (IMS) as one of these modalities. Although different modalities are routinely registered and overlaid to generate a single display, true integration of data across technologies is largely left to human interpretation, resulting in a significant underutilization of the potential of multi-modal measurements. This talk gives an overview of our recent work on the integration or ‘fusion’ of IMS with measurements from other imaging modalities, and demonstrates the potential of data-driven image fusion for IMS through several predictive applications. |
Long Abstract
Medical studies increasingly employ a multitude of different imaging technologies to answer a specific biological question. A growing number of such multi-modal imaging studies include Imaging Mass Spectrometry (IMS) as one of these modalities. Although different modalities are routinely registered and overlaid to generate a single display, true integration of data across technologies is largely left to human interpretation, resulting in a significant underutilization of the potential of multi-modal measurements. This talk gives an overview of our recent work on the integration or ‘fusion’ of IMS with measurements from other imaging modalities, and demonstrates the potential of data-driven image fusion for IMS through several predictive applications.
References & Acknowledgements:
Van de Plas, R., Yang, J., Spraggins, J., & Caprioli, R. M. Image fusion of mass spectrometry and microscopy: a multimodality paradigm for molecular tissue mapping. Nature Methods 12, no. 4 (2015): 366-372.
This work was supported by the US National Institutes of Health grants NIH/NIGMS R01 GM058008-15 and NIH/NIGMS P41 GM103391-04.
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