Hybrid Deep Neural Network for Brachial Plexus Nerve Segmentation in Ultrasound Images

Autor:	van Boxtel, Juul P. A., Vousten, Vincent R. J., Pluim, Josien, Rad, Nastaran Mohammadian
Rok vydání:	2021
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition I.4.6
Druh dokumentu:	Working Paper
DOI:	10.23919/EUSIPCO54536.2021.9616329
Popis:	Ultrasound-guided regional anesthesia (UGRA) can replace general anesthesia (GA), improving pain control and recovery time. This method can be applied on the brachial plexus (BP) after clavicular surgeries. However, identification of the BP from ultrasound (US) images is difficult, even for trained professionals. To address this problem, convolutional neural networks (CNNs) and more advanced deep neural networks (DNNs) can be used for identification and segmentation of the BP nerve region. In this paper, we propose a hybrid model consisting of a classification model followed by a segmentation model to segment BP nerve regions in ultrasound images. A CNN model is employed as a classifier to precisely select the images with the BP region. Then, a U-net or M-net model is used for the segmentation. Our experimental results indicate that the proposed hybrid model significantly improves the segmentation performance over a single segmentation model. Comment: The first two authors contributed equally
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2106.00373 Zobrazit plný text záznamu View this record from Arxiv