Towards Enhanced Analysis of Lung Cancer Lesions in EBUS-TBNA -- A Semi-Supervised Video Object Detection Method

arXiv:2404.01929v2 Announce Type: replace-cross
Abstract: This study aims to establish a computer-aided diagnostic system for lung lesions using bronchoscope endobronchial ultrasound (EBUS) to assist physicians in identifying lesion areas. During EBUS-transbronchial needle aspiration (EBUS-TBNA) procedures, physicians rely on grayscale ultrasound images to determine the location of lesions. However, these images often contain significant noise and can be influenced by surrounding tissues or blood vessels, making interpretation challenging. Previous research has lacked the application of object detection models to EBUS-TBNA, and …

abstract analysis arxiv cancer computer cs.cv detection diagnostic eess.iv images lung cancer object physicians semi-supervised study type video