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On a Heavy-Tailed Intensity Normalization of the Parkinson’s Progression Markers Initiative Brain Database

  • Diego Castillo-Barnes
  • Carlos Arenas
  • Fermín Segovia
  • Francisco J. Martínez-Murcia
  • Ignacio A. Illán
  • Juan M. Górriz
  • Javier Ramírez
  • Diego Salas-GonzalezEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10337)

Abstract

In this work, we normalize the intensity of 40 FP-CIT SPECT images from the Parkinson’s Progression Markers Initiative assuming that the histogram of intensity values follows an \(\alpha \)-stable distribution. Then, we study the normalized images. The interclass separation of the Parkinson’s disease (PD) brain images and the healthy control (HC) are calculated by means of the Mann-Whitney-Wilcoxon U-test. The intensity transformed images present higher inter-class separation according to the estimation of the U-test.

Keywords

Parkinson Disease Single Photon Emission Computerize Tomography Essential Tremor Stable Distribution Parkinson Disease Subject 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work was supported by MINECO/FEDER under the TEC2015-64718-R project and Junta de Andalucía under the P11-TIC-7103 Excellence Project.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Diego Castillo-Barnes
    • 1
  • Carlos Arenas
    • 1
  • Fermín Segovia
    • 1
  • Francisco J. Martínez-Murcia
    • 1
  • Ignacio A. Illán
    • 2
  • Juan M. Górriz
    • 1
  • Javier Ramírez
    • 1
  • Diego Salas-Gonzalez
    • 1
    Email author
  1. 1.Department of Signal Theory, Networking and CommunicationsETSIIT-UGR, University of GranadaGranadaSpain
  2. 2.Department of Scientific ComputingThe Florida State UniversityTallahasseeUSA

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