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Abstract Factor analysis (FA) has been pursued as a means to decompose dynamic cardiac PET images into different tissue types
 

Summary: Abstract Factor analysis (FA) has been pursued as a means to
decompose dynamic cardiac PET images into different tissue types
based on their unique physiology. Each tissue is represented by a
time-activity profile (factor) and an associated spatial distribution
(structure). Decomposition is based on non-negative constraints of
both the factors and structures; however, additional constraints are
required to achieve a unique solution. In this work we present a
novel method that combines physiological models of factor
relationships into the decomposition process. Preliminary results are
evaluated, suggesting that model-based FA decomposition results in
physiologically accurate factors and structures.
I. INTRODUCTION
actor analysis (FA) techniques have been explored as a means
to improve cardiac function quantification. An image series is
decomposed into a finite number of temporal factors and their
corresponding spatial distribution (structures) which, ideally,
should correspond to the physiology of the imaged tissue [1]. The
decomposition may be expressed in matrix form as
Y = FS+E,
Where Y is the dynamic image sequence (the pixels of each time

  

Source: Adler, Andy - Department of Systems and Computer Engineering, Carleton University

 

Collections: Computer Technologies and Information Sciences