Patient-Specific Skeletal Muscle Fiber Modeling from Structure Tensor Field of Clinical CT Images

Citation:

Yoshito Otake, Futishi Yokota, Norio Fukuda, Masaki Takao, Shu Takagi, Naoto Yamamura, Lauren O'Donnell, Westin Carl-Fredrik, Nobuhiko Sugano, and Yoshinobu Sato. 9/2017. “Patient-Specific Skeletal Muscle Fiber Modeling from Structure Tensor Field of Clinical CT Images.” Int Conf Med Image Comput Comput Assist Interv. 20 (Pt1), Pp. 656-63.
Otake-MICCAI2017.pdf6.67 MB

Abstract:

We propose an optimization method for estimating patient- specific muscle fiber arrangement from clinical CT. Our approach first computes the structure tensor field to estimate local orientation, then a geometric template representing fiber arrangement is fitted using a B- spline deformation by maximizing fitness of the local orientation using a smoothness penalty. The initialization is computed with a previously proposed algorithm that takes account of only the muscle’s surface shape. Evaluation was performed using a CT volume (1.0mm3/voxel) and high resolution optical images of a serial cryosection (0.1mm3/voxel). The mean fiber distance error at the initialization of 6.00 mm was decreased to 2.78mm after the proposed optimization for the gluteus maximus muscle, and from 5.28 mm to 3.09 mm for the gluteus medius muscle. The result from 20 patient CT images suggested that the proposed algorithm reconstructed an anatomically more plausible fiber arrangement than the previous method.
Last updated on 10/18/2017