Sequence-independent segmentation of magnetic resonance images

DMCA

Sequence-independent segmentation of magnetic resonance images (2004)

Cached

Download Links

by Bruce Fischl , David H. Salat , A Nikos Makris , Florent Ségonne , B Brian T. Quinn , Anders M. Dale A

Venue:	Neuroimage
Citations:	112 - 20 self

BibTeX

@ARTICLE{Fischl04sequence-independentsegmentation,
    author = {Bruce Fischl and David H. Salat and A Nikos Makris and Florent Ségonne and B Brian T. Quinn and Anders M. Dale A},
    title = {Sequence-independent segmentation of magnetic resonance images},
    journal = {Neuroimage},
    year = {2004},
    pages = {69--84}
}

OpenURL

Abstract

We present a set of techniques for embedding the physics of the imaging process that generates a class of magnetic resonance images (MRIs) into a segmentation or registration algorithm. This results in substantial invariance to acquisition parameters, as the effect of these parameters on the contrast properties of various brain structures is explicitly modeled in the segmentation. In addition, the integration of image acquisition with tissue classification allows the derivation of sequences that are optimal for segmentation purposes. Another benefit of these procedures is the generation of probabilistic models of the intrinsic tissue parameters that cause MR contrast (e.g., T1, proton density, T2*), allowing access to these physiologically relevant parameters that may change with disease or demographic, resulting in nonmorphometric alterations in MR images that are otherwise difficult to detect. Finally, we also present a high band width multiecho FLASH pulse sequence that results in high signal-to-noise ratio with minimal image distortion due to B0 effects. This sequence has the added benefit of allowing the explicit estimation of T2 * and of reducing test–retest intensity variability.

Keyphrases

magnetic resonance image sequence-independent segmentation minimal image distortion substantial invariance added benefit mr image segmentation purpose nonmorphometric alteration explicit estimation contrast property mr contrast test retest intensity variability acquisition parameter image acquisition b0 effect tissue classification imaging process relevant parameter high signal-to-noise ratio probabilistic model intrinsic tissue parameter proton density various brain structure

DMCA