141 citations
- University of TurkuFI10 papers
- Aalto UniversityFI5 papers
- Turku University HospitalFI5 papers
- TU WienAT3 papers
- Åbo Akademi UniversityFI2 papers
- University of JyväskyläFI2 papers
- Aarhus UniversityDK1 paper
- Ecole des Hautes Etudes Commerciales du NordFR1 paper
- Finnish Meteorological InstituteFI1 paper
- Institute of Space TechnologyPK1 paper
- Nanyang Technological UniversitySG1 paper
- Petro-CanadaCA1 paper
11 papers
Quantitative evaluation of unsupervised clustering algorithms for dynamic total-body PET image analysis
Oona Rainio, Maria K. Jaakkola, Riku Klén
Background. Recently, dynamic total-body positron emission tomography (PET) imaging has become possible due to new scanner devices. While clustering algorithms have been proposed f…
AI for the prediction of early stages of Alzheimer's disease from neuroimaging biomarkers -- A narrative review of a growing field
Thorsten Rudroff, Oona Rainio, Riku Klén
Objectives: The objectives of this narrative review are to summarize the current state of AI applications in neuroimaging for early Alzheimer's disease (AD) prediction and to highl…
Stationary subspace analysis based on second-order statistics
Lea Flumian, Markus Matilainen, Klaus Nordhausen +1
In stationary subspace analysis (SSA) one assumes that the observable p-variate time series is a linear mixture of a k-variate nonstationary time series and a (p-k)-variate station…
Aalto-1, multi-payload CubeSat: In-orbit results and lessons learned
M. R. Mughal, J. Praks, R. Vainio +17
The in-orbit results and lessons learned of the first Finnish satellite Aalto-1 are briefly presented in this paper. Aalto-1, a three-unit CubeSat which was launched in June 2017,…
Extracting conditionally heteroscedastic components using ICA
Jari Miettinen, Markus Matilainen, Klaus Nordhausen +1
In the independent component model, the multivariate data is assumed to be a mixture of mutually independent latent components, and in independent component analysis (ICA) the aim…
Sliced Average Variance Estimation for Multivariate Time Series
Markus Matilainen, Christophe Croux, Klaus Nordhausen +1
Supervised dimension reduction for time series is challenging as there may be temporal dependence between the response and the predictors . Recently a time serie…