@inproceedings{PohleFroehlichDalitzRichteretal.2020,
  author    = {Pohle-Fr{\"o}hlich, Regina and Dalitz, Christoph and Richter, Charlotte and Hahnen, Tobias and St{\"a}udle, Benjamin and Albracht, Kirsten},
  title     = {Estimation of muscle fascicle orientation in ultrasonic images},
  series = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5},
  booktitle = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5},
  publisher = {SciTePress},
  address   = {Set{\´u}bal, Portugal},
  isbn      = {978-989-758-402-2},
  doi       = {10.5220/0008933900790086},
  pages     = {79 -- 86},
  year      = {2020},
  abstract  = {We compare four different algorithms for automatically estimating the muscle fascicle angle from ultrasonic images: the vesselness filter, the Radon transform, the projection profile method and the gray level cooccurence matrix (GLCM). The algorithm results are compared to ground truth data generated by three different experts on 425 image frames from two videos recorded during different types of motion. The best agreement with the ground truth data was achieved by a combination of pre-processing with a vesselness filter and measuring the angle with the projection profile method. The robustness of the estimation is increased by applying the algorithms to subregions with high gradients and performing a LOESS fit through these estimates.},
  language  = {en}
}