Optimal view detection for ultrasound-guided supraclavicular block using deep learning approaches.

Successful ultrasound-guided supraclavicular block (SCB) requires the understanding of sonoanatomy and identification of the optimal view. Segmentation using a convolutional neural network (CNN) is limited in clearly determining the optimal view. The present study describes the development of a computer-aided diagnosis (CADx) system using a CNN that can determine the optimal view for complete SCB in real time.