Statistical Parametric Models and Inference for Biomedical Signal Processing
Subtitle: Applications in Speech and Magnetic Resonance Imaging
Contributors: Wolfe, Patrick J.; Hu, Evelyn; Khaneja, Navin; Lu, Yue M.
Published: 2012
Language: eng
Description: In this thesis, we develop statistical methods for extracting significant information from biomedical signals. Biomedical signals are not only generated from a complex system but also affected by various random factors during their measurement. The biomedical signals may then be studied in two aspects: observational noise that biomedical signals experience and intrinsic nature that noise-free signals possess. We study Magnetic Resonance (MR) images and speech signals as applications in the one- and two-dimensional signal representation.
Notes: Thesis Ph.D. Harvard University 2012