Automatic registration of imaging mass spectrometry data to the Allen Brain Atlas transcriptome

Walid M. Abdelmoula; Ricardo J. Carreira; Reinald Shyti; Benjamin Balluff; Else Tolner; Arn M. J. M. van den Maagdenberg; B. P. F. Lelieveldt; Liam McDonnell; Jouke Dijkstra

doi:10.1117/12.2043653

21 March 2014 Automatic registration of imaging mass spectrometry data to the Allen Brain Atlas transcriptome

Walid M. Abdelmoula, Ricardo J. Carreira, Reinald Shyti, Benjamin Balluff, Else Tolner, Arn M. J. M. van den Maagdenberg, B. P. F. Lelieveldt, Liam McDonnell, Jouke Dijkstra

Author Affiliations +

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 90343M (2014) https://doi.org/10.1117/12.2043653
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Imaging Mass Spectrometry (IMS) is an emerging molecular imaging technology that provides spatially resolved information on biomolecular structures; each image pixel effectively represents a molecular mass spectrum. By combining the histological images and IMS-images, neuroanatomical structures can be distinguished based on their biomolecular features as opposed to morphological features. The combination of IMS data with spatially resolved gene expression maps of the mouse brain, as provided by the Allen Mouse Brain atlas, would enable comparative studies of spatial metabolic and gene expression patterns in life-sciences research and biomarker discovery. As such, it would be highly desirable to spatially register IMS slices to the Allen Brain Atlas (ABA). In this paper, we propose a multi-step automatic registration pipeline to register ABA histology to IMS- images. Key novelty of the method is the selection of the best reference section from the ABA, based on pre-processed histology sections. First, we extracted a hippocampus-specific geometrical feature from the given experimental histological section to initially localize it among the ABA sections. Then, feature-based linear registration is applied to the initially localized section and its two neighbors in the ABA to select the most similar reference section. A non-rigid registration yields a one-to-one mapping of the experimental IMS slice to the ABA. The pipeline was applied on 6 coronal sections from two mouse brains, showing high anatomical correspondence, demonstrating the feasibility of complementing biomolecule distributions from individual mice with the genome-wide ABA transcriptome.

Citation Download Citation

Walid M. Abdelmoula, Ricardo J. Carreira, Reinald Shyti, Benjamin Balluff, Else Tolner, Arn M. J. M. van den Maagdenberg, B. P. F. Lelieveldt, Liam McDonnell, and Jouke Dijkstra "Automatic registration of imaging mass spectrometry data to the Allen Brain Atlas transcriptome", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90343M (21 March 2014); https://doi.org/10.1117/12.2043653

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available