AUTOMATIC LOCALIZATION OF EPIDURAL NEEDLE ENTRY SITE WITH LUMBAR ULTRASOUND IMAGE PROCESSING

Abstract

Epidural anesthesia (EA) is rated as one of the most difficult procedures to perform in anesthesiology. A key technical challenge of EA is the identification of the needle entry site, which is clinically determined by palpating the surface landmarks of the spine. Previous researches have confirmed the effectiveness of ultrasound imaging compared with traditional palpation method. However, the low resolution and speckle noises influence the interpretation of ultrasound images, leading to the difficulties of anaesthetists in adopting ultrasonography in the clinical practice. In this thesis, an intelligent image processing algorithm and procedure based on machine learning is developed for lumbar ultrasound image processing. The algorithm is able to provide guidance to locate the precise needle entry site as the operator moving the ultrasound probe, thus facilitating the interpretation of ultrasound images and realizing automatic localization of needle entry site.