Abstract: In modern medicine,the image of the brachial plexus segmentation and recognition is optimized by contrast enhancement to help the physician identify the disease and tumor.Brachial plexus block is a commonly used method of local anesthesia in upper limb surgery and postoperative care.In order to accurately determine the position of thebrachialplexus,the hospital extensively applies ultrasound equipment to detect and locate the nervous system.This paper described the accurate recognition and segmentation of brachial plexus in ultrasound dynamic images based on deeplear-ning and neural network,and optimized the display of ultrasound images through adaptive contrast enhancement in the cut-out images.The experiment data come from the Beijing Jishuitan Hospital,which are divided into ultrasound images of patients and corresponding pictures of benign malignancies.The enhanced contrast algorithm was used to process the extracted features.The experimental results show that this algorithm enhances the contrast of the image and the accuracy of the displayed content.

Key words: Adaptive enhancement contrast algorithm, Brachial plexus, Convolution and neural network, Deep learning, Image process, Ultrasound image