title: A fast T1 algorithm.
abstract: Multispectral tissue classification using magnetic resonance T1, T2, and rho images may be useful in diagnosing and locating certain pathology. Techniques for generating the T1 images necessary for this classification scheme often require longer data collection and post processing times than are practical. As a consequence, further development of this classification scheme may be limited. This paper addresses an improvement in the post processing time required to generate T1 images. A nonlinear least-squares algorithm is described for rapidly generating spin-lattice relaxation time images from variable repetition time magnetic resonance images. The algorithm generates a 256 x 256 pixel T1 image from nine variable repetition time images in approximately 60 sec on a VAX-6510 computer.
authors.affiliation: Center for Imaging Science, Rochester Institute of Technology, NY 14623.
authors.forename: J
authors.initials: J
authors.lastname: Gong
authors.forename: J P
authors.initials: JP
authors.lastname: Hornak
mesh_terms: D000465:Algorithms; D006801:Humans; D008279:Magnetic Resonance Imaging; D013997:Time Factors