title: MUSE--a new tool for interactive image analysis and segmentation based on multivariate statistics.
abstract: MUSE--a new software tool for the interactive exploration of multivariate images and the development of image segmentation methods has been designed, implemented, and tested in a number of real application projects. The multivariate statistical classification and projection methods in MUSE can be used not only to analyze multispectral images but also, in special cases, multitemporal images and volume images. Additionally MUSE can be applied to normal greyscale images provided they are made multivariate through an initial processing step. This step may consist in the application of filters designed to enhance any existing texture differences between different regions in the images. MUSE has been successfully applied to medical images (color photographs, MR, PET, SPECT) as well as to satellite images (Landsat TM).
authors.affiliation: Centre for Image Analysis, Uppsala University, Sweden.
authors.forename: E
authors.initials: E
authors.lastname: Bengtsson
authors.forename: B
authors.initials: B
authors.lastname: Nordin
authors.forename: F
authors.initials: F
authors.lastname: Pedersen
mesh_terms: D003952:Diagnostic Imaging; D016002:Discriminant Analysis; D007091:Image Processing, Computer-Assisted; D015999:Multivariate Analysis; D012044:Regression Analysis; D012984:Software; D014584:User-Computer Interface