Paralisia Facial: Técnicas de Reconstrução Neuro-Muscular

Several surgical procedures have been proposed through the years for the treatment of facial paralysis. The multiplicity and diversity of techniques portray the complexity and challenge represented by this pathology. Two basic dynamic options are available: -Reconstruction of nerve continuity through direct micro suture, with interposition grafts or nerve transpositions. -Regional muscular transposition, most often using the temporalis. Facial reanimation with the temporalis transfer has withstood the test of time and still is a reference technique. In a few weeks, good results can be obtained with a single and rather simple surgical procedure. Functional free flaps have been used with increasing frequency in the last two decades, most often combining a cross-facial nerve graft followed by a gracilis free flap nine months later. With this method there is a potential for restoration of spontaneous facial mimetic function. Apparently there is a limit in microsurgical technique and expertise beyond which there is no clear improvement in nerve regeneration. Current research is now actively studying and identifying nerve growth factors and pharmacological agents that might have an important and complementary role in the near future.

Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.