P Padilla

Summary

Publications

  1. ncbi NMF-SVM based CAD tool applied to functional brain images for the diagnosis of Alzheimer's disease
    P Padilla
    Department of Signal Theory, Telematics and Communications, University of Granada, 18071 Granada, Spain
    IEEE Trans Med Imaging 31:207-16. 2012
  2. ncbi Analysis of SPECT brain images for the diagnosis of Alzheimer's disease based on NMF for feature extraction
    P Padilla
    Department of Signal Theory, Networking and Communications, University of Granada, Fuentenueva s n, Granada, Spain
    Neurosci Lett 479:192-6. 2010
  3. ncbi Classification of functional brain images using a GMM-based multi-variate approach
    F Segovia
    Department of Signal Theory, Networking and Communications, University of Granada, Fuentenueva s n, Granada, Spain
    Neurosci Lett 474:58-62. 2010
  4. ncbi Feature selection using factor analysis for Alzheimer's diagnosis using 18F-FDG PET images
    D Salas-Gonzalez
    Department of Signal Theory, Networking and Communications, ETSIIT 18071, University of Granada, Granada, Spain
    Med Phys 37:6084-95. 2010
  5. ncbi Computer aided diagnosis system for the Alzheimer's disease based on partial least squares and random forest SPECT image classification
    J Ramirez
    Dept of Signal Theory, Networking and Communications, University of Granada, Periodista Daniel Saucedo Aranda S N, 18071 Granada, Spain
    Neurosci Lett 472:99-103. 2010

Collaborators

Detail Information

Publications5

  1. ncbi NMF-SVM based CAD tool applied to functional brain images for the diagnosis of Alzheimer's disease
    P Padilla
    Department of Signal Theory, Telematics and Communications, University of Granada, 18071 Granada, Spain
    IEEE Trans Med Imaging 31:207-16. 2012
    ..The proposed NMF-SVM method yields up to 91% classification accuracy with high sensitivity and specificity rates (upper than 90%). This NMF-SVM CAD tool becomes an accurate method for SPECT and PET AD image classification...
  2. ncbi Analysis of SPECT brain images for the diagnosis of Alzheimer's disease based on NMF for feature extraction
    P Padilla
    Department of Signal Theory, Networking and Communications, University of Granada, Fuentenueva s n, Granada, Spain
    Neurosci Lett 479:192-6. 2010
    ....
  3. ncbi Classification of functional brain images using a GMM-based multi-variate approach
    F Segovia
    Department of Signal Theory, Networking and Communications, University of Granada, Fuentenueva s n, Granada, Spain
    Neurosci Lett 474:58-62. 2010
    ..The leave-one-out cross-validation technique is used to validate the results obtained by the supervised learning-based computer aided diagnosis (CAD) system over databases of SPECT and PET images yielding an accuracy rate up to 96.67%...
  4. ncbi Feature selection using factor analysis for Alzheimer's diagnosis using 18F-FDG PET images
    D Salas-Gonzalez
    Department of Signal Theory, Networking and Communications, ETSIIT 18071, University of Granada, Granada, Spain
    Med Phys 37:6084-95. 2010
    ..Two hundred and ten 18F-FDG PET images from the ADNI initiative [52 normal controls (NC), 114 mild cognitive impairment (MCI), and 53 AD subjects] are studied...
  5. ncbi Computer aided diagnosis system for the Alzheimer's disease based on partial least squares and random forest SPECT image classification
    J Ramirez
    Dept of Signal Theory, Networking and Communications, University of Granada, Periodista Daniel Saucedo Aranda S N, 18071 Granada, Spain
    Neurosci Lett 472:99-103. 2010
    ..7%, and 96.9%, respectively. Moreover, the proposed CAD system outperformed several other recently developed AD CAD systems...