MUSE--a new tool for interactive image analysis and segmentation based on multivariate statistics

E Bengtsson; B Nordin; F Pedersen

doi:10.1016/0169-2607(94)90128-7

MUSE--a new tool for interactive image analysis and segmentation based on multivariate statistics

Comput Methods Programs Biomed. 1994 Mar;42(3):181-200. doi: 10.1016/0169-2607(94)90128-7.

Authors

E Bengtsson¹, B Nordin, F Pedersen

Affiliation

¹ Centre for Image Analysis, Uppsala University, Sweden.

PMID: 8062550
DOI: 10.1016/0169-2607(94)90128-7

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).

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Diagnostic Imaging
Discriminant Analysis
Image Processing, Computer-Assisted*
Multivariate Analysis*
Regression Analysis
Software*
User-Computer Interface