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

We propose an optimization method for estimating patientspecific 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 Bspline 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 (1.0mm/voxel) and high resolution optical images of a serial cryo-section (0.1mm/voxel). The mean fiber distance error at the initialization of 6.00mm was decreased to 2.78mm after the proposed optimization for the gluteus maximus muscle, and from 5.28mm to 3.09mm 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.