DATA_ANALYSIS

Medical images and signals are often acquired in digital format. This allows for the development of signal and image analysis algorithms to process this data to gain useful information about the image or signal's content. Image and signal analysis techniques give way to objective quantification of structures, objects, relationships of events and other properties in an image or signal.

• Data Analysis Techniques for Medical Signals and Images
  • Disease quantification (localization, volume measurements, etc.)
  • Automated analysis of therapy effects and pathology progression
  • Detection of pathology and anatomy
  • Data mining or classification
  • Statistical modelling of pathology and other phenomena
  • Image filtering (edge-detection, enhancement, etc.)
  • Sonification and audification
  • Analysis of registration deformation maps

• High-Level Data Analysis Techniques for Medical Signals and Images
  • Pattern recognition techniques (LDA, PCA, etc.)
  • Feature extraction
  • Time-frequency transformations (wavelet, Gabor, Wigner-Ville, etc.)
  • Texture analysis (multiresolutional-, spatial- or frequency-based)
  • Histogram analysis (statistics)