title: Automated subject-specific, hexahedral mesh generation via image registration.
abstract: Generating subject-specific, all-hexahedral meshes for finite element analysis continues to be of significant interest in biomechanical research communities. To date, most automated methods "morph" an existing atlas mesh to match with a subject anatomy, which usually result in degradation in mesh quality because of mesh distortion. We present an automated meshing technique that produces satisfactory mesh quality and accuracy without mesh repair. An atlas mesh is first developed using a script. A subject-specific mesh is generated with the same script after transforming the geometry into the atlas space following rigid image registration, and is transformed back into the subject space. By meshing the brain in 11 subjects, we demonstrate that the technique's performance is satisfactory in terms of both mesh quality (99.5% of elements had a scaled Jacobian >0.6 while <0.01% were between 0 and 0.2) and accuracy (average distance between mesh boundary and geometrical surface was 0.07 mm while <1% greater than 0.5mm). The combined computational cost for image registration and meshing was <4 min. Our results suggest that the technique is effective for generating subject-specific, all-hexahedral meshes and that it may be useful for meshing a variety of anatomical structures across different biomechanical research fields.
authors: Thayer School of Engineering, Dartmouth College, Hanover, NH, USA.
authors: Songbai
authors: S
authors: Ji
authors: James C
authors: JC
authors: Ford
authors: Richard M
authors: RM
authors: Greenwald
authors: Jonathan G
authors: JG
authors: Beckwith
authors: Keith D
authors: KD
authors: Paulsen
authors: Laura A
authors: LA
authors: Flashman
authors: Thomas W
authors: TW
authors: McAllister