Ultrasound median nerve localization by classification based on despeckle filtering and feature selection

Ultrasound-guided regional anaesthesia (UGRA) is growing rapidly in the medical field, and becomes a standard procedure in many worldwide hospitals. UGRA can specifically benefit from image processing and machine learning techniques. Very few studies have been developed for that purpose. This paper focuses on automatic localization of nerve in ultrasound images, in order to assist anaesthetists during UGRA procedure. Due to the complex structure of nerve and poor quality of ultrasound images, the automatic detection of nerve region is a challenging problem. To handle such issue, several processing phases are required. For that purpose, we propose a new method, based on despeckling, feature ranking and majority vote classification, for a robust and accurate median nerve localization. The proposed method is applied on a real dataset obtained from eight patients. The obtained results showed high performance for median nerve detection achieving accuracy of 89% of the f-score measure.