Biomedical Imaging Group
Logo EPFL
    • Splines Tutorials
    • Splines Art Gallery
    • Wavelets Tutorials
    • Image denoising
    • ERC project: FUN-SP
    • Sparse Processes - Book Preview
    • ERC project: GlobalBioIm
    • The colored revolution of bioimaging
    • Deconvolution
    • SMLM
    • One-World Seminars: Representer theorems
    • A Unifying Representer Theorem
Follow us on Twitter.
Join our Github.
Masquer le formulaire de recherche
Menu
BIOMEDICAL IMAGING GROUP (BIG)
Laboratoire d'imagerie biomédicale (LIB)
  1. School of Engineering STI
  2. Institute IEM
  3.  LIB
  4.  Glomeruli Analysis
  • Laboratory
    • Laboratory
    • Laboratory
    • People
    • Jobs and Trainees
    • News
    • Events
    • Seminars
    • Resources (intranet)
    • Twitter
  • Research
    • Research
    • Researchs
    • Research Topics
    • Talks, Tutorials, and Reviews
  • Publications
    • Publications
    • Publications
    • Database of Publications
    • Talks, Tutorials, and Reviews
    • EPFL Infoscience
  • Code
    • Code
    • Code
    • Demos
    • Download Algorithms
    • Github
  • Teaching
    • Teaching
    • Teaching
    • Courses
    • Student projects
  • Splines
    • Teaching
    • Teaching
    • Splines Tutorials
    • Splines Art Gallery
    • Wavelets Tutorials
    • Image denoising
  • Sparsity
    • Teaching
    • Teaching
    • ERC project: FUN-SP
    • Sparse Processes - Book Preview
  • Imaging
    • Teaching
    • Teaching
    • ERC project: GlobalBioIm
    • The colored revolution of bioimaging
    • Deconvolution
    • SMLM
  • Machine Learning
    • Teaching
    • Teaching
    • One-World Seminars: Representer theorems
    • A Unifying Representer Theorem

Wavelet-Based Statistical Analysis for Optical Imaging in Mouse Olfactory Bulb

D. Van De Ville, B. Bathellier, A. Carleton, T. Blu, M. Unser

Proceedings of the Fourth IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'07), Arlington VA, USA, April 12-15, 2007, pp. 448-451.


Optical imaging is a powerful technique to map brain function in animals. In this study, we consider in vivo optical imaging of the murine olfactory bulb, using an intrinsic signal and a genetically expressed activity reporter fluorescent protein (synaptopHfluorin). The aim is to detect odor-evoked activations that occur in small spherical structures of the olfactory bulb called glomeruli. We propose a new way of analyzing this kind of data that combines a linear model (LM) fitting along the temporal dimension, together with a discrete wavelet transform (DWT) along the spatial dimensions. We show that relevant regressors for the LM are available for both types of optical signals. In addition, the spatial wavelet transform allows us to exploit spatial correlation at different scales, and in particular to extract activation patterns at the expected size of glomeruli. Our framework also provides a statistical significance for every pixel in the activation maps and it has strong type I error control.

@INPROCEEDINGS(http://bigwww.epfl.ch/publications/vandeville0702.html,
AUTHOR="Van De Ville, D. and Bathellier, B. and Carleton, A. and Blu, T.
	and Unser, M.",
TITLE="Wavelet-Based Statistical Analysis for Optical Imaging in Mouse
	Olfactory Bulb",
BOOKTITLE="Proceedings of the Fourth {IEEE} International Symposium on
	Biomedical Imaging: {F}rom Nano to Macro ({ISBI'07})",
YEAR="2007",
editor="",
volume="",
series="",
pages="448--451",
address="Arlington VA, USA",
month="April 12-15,",
organization="",
publisher="",
note="")

© 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
  • Laboratory
  • Research
  • Publications
    • Database of Publications
    • Talks, Tutorials, and Reviews
    • EPFL Infoscience
  • Code
  • Teaching
Logo EPFL, Ecole polytechnique fédérale de Lausanne
Emergencies: +41 21 693 3000 Services and resources Contact Map Webmaster email

Follow EPFL on social media

Follow us on Facebook. Follow us on Twitter. Follow us on Instagram. Follow us on Youtube. Follow us on LinkedIn.
Accessibility Disclaimer Privacy policy

© 2023 EPFL, all rights reserved