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Journal of Applied Nonlinear Dynamics
Miguel A. F. Sanjuan (editor), Albert C.J. Luo (editor)
Miguel A. F. Sanjuan (editor)

Department of Physics, Universidad Rey Juan Carlos, 28933 Mostoles, Madrid, Spain


Albert C.J. Luo (editor)

Department of Mechanical and Industrial Engineering, Southern Illinois University Ed-wardsville, IL 62026-1805, USA

Fax: +1 618 650 2555 Email:

Fractional Order Image Processing of Medical Images

Journal of Applied Nonlinear Dynamics 6(2) (2017) 181--191 | DOI:10.5890/JAND.2017.06.005

Tiago Bento $^{1}$,$^{2}$, Duarte Valério$^{1}$, Pedro Teodoro$^{3}$, Jorge Martins$^{1}$

$^{1}$ IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

$^{2}$ Deloitte Portugal, Portugal

$^{3}$ Escola Superior Náutica Infante D. Henrique, Paço d’Arcos, Portugal

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To perform a robot-assisted surgery of a prosthesis implantation on a patient’s femur, we may need to get the femoral head-neck orientation for the application. We can extract that information from Computed Tomography scans, using image processing. In image processing, edge detection often makes use of integer-order differentiation operators (e.g. Canny and LoG operators). This paper shows that introducing non-integer (fractional) differentiation to edge detectors (Fractional Canny, Fractional LoG, Fractional Derivative operators) can improve automatic edge detection results.


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