چكيده به لاتين
Ultrasound-guided regional anesthesia (UGRA) is the latest application of ultrasound imaging. A limitation of UGRA usage is the error in the exact detection of nerve blocks in the ultrasound images. In this study, an automatic method for the detection of the peripheral nerve is presented using a combination of anatomical and morphological information of nerves in the ultrasound images. At first, to remove noise and improve visual quality local histogram equalization and Laplacian filter are used. Then, the images are binarized using an adaptive threshold. Afterward, since fascia is continuous and brighter than other segments, probable segments corresponding to the fascia is detected. Moreover, due to the round shape of nerves in ultrasound images, the Hough algorithm is used to choose the nerve location candidates. Since the nerve is near the fascia and has more intensity brightness some nerve location candidates are eliminated. Finally, active contours are implemented to segment the nerve location candidates and the exact nerve location is detected by roundness criteria. The result has shown that the presented approach detected the nerve location in 72% of the data-set images correctly. The similarity between the detected nerve area and the marked nerve area, by the neurologist, according to the Dice coefficient is 71.8%±14.9%. Qualitative and quantitative investigations confirm the robustness and accuracy of the proposed method.
