Publikationen in Zusammenarbeit mit Forschern von Florida State University (10)

2017

  1. A 3D convolutional neural network approach for the diagnosis of Parkinson’s disease

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. A heavy tailed expectation maximization hidden markov random field model with applications to segmentation of MRI

    Frontiers in Neuroinformatics, Vol. 11

  3. Automatic separation of parkinsonian patients and control subjects based on the striatal morphology

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  4. Case-Based Statistical Learning: A Non-Parametric Implementation with a Conditional-Error Rate SVM

    IEEE Access, Vol. 5, pp. 11468-11478

  5. Case-based statistical learning: A non parametric implementation applied to SPECT images

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  6. Evaluating Alzheimer’s disease diagnosis using texture analysis

    Communications in Computer and Information Science

  7. Functional brain imaging synthesis based on image decomposition and kernel modeling: Application to neurodegenerative diseases

    Frontiers in Neuroinformatics, Vol. 11

  8. On a heavy-tailed intensity normalization of the parkinson’s progression markers initiative brain database

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  9. Tree-based ensemble learning techniques in the analysis of parkinsonian syndromes

    Communications in Computer and Information Science

2016

  1. MRI brain segmentation using hidden Markov random fields with alpha-stable distributions

    2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016