Evaluating Structural Connectomics in Relation to Different Q-space Sampling Techniques

  • Paulo Rodrigues
  • Alberto Prats-Galino
  • David Gallardo-Pujol
  • Pablo Villoslada
  • Carles Falcon
  • Vesna Prčkovska
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8149)


Brain networks are becoming forefront research in neuroscience. Network-based analysis on the functional and structural connectomes can lead to powerful imaging markers for brain diseases. However, constructing the structural connectome can be based upon different acquisition and reconstruction techniques whose information content and mutual differences has not yet been properly studied in a unified framework. The variations of the structural connectome if not properly understood can lead to dangerous conclusions when performing these type of studies. In this work we present evaluation of the structural connectome by analysing and comparing graph-based measures on real data acquired by the three most important Diffusion Weighted Imaging techniques: DTI, HARDI and DSI. We thus come to several important conclusions demonstrating that even though the different techniques demonstrate differences in the anatomy of the reconstructed fibers the respective connectomes show variations of 20%.


Acquisition Scheme Superior Longitudinal Fasciculus High Angular Resolution Characteristic Path Length Connectivity Matrice 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Paulo Rodrigues
    • 1
    • 2
  • Alberto Prats-Galino
    • 3
  • David Gallardo-Pujol
    • 2
  • Pablo Villoslada
    • 4
  • Carles Falcon
    • 5
  • Vesna Prčkovska
    • 4
  1. 1.Mint Labs S.L.BarcelonaSpain
  2. 2.Dept. of Personality, Faculty of PsychologyUBBarcelonaSpain
  3. 3.LSNA, Facultat de MedicinaUBBarcelonaSpain
  4. 4.Center for Neuroimmunology, Department of NeurosciencesIDIBAPS, Hospital ClinicBarcelonaSpain
  5. 5.Medical Imaging PlatformIDIBAPSBarcelonaSpain

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