可视化
窄带成像
内窥镜检查
人工智能
计算机科学
放射科
医学
模式识别(心理学)
作者
Nazila Esmaeili,Alfredo Illanes,Axel Boese,Nikolaos Davaris,Christoph Arens,Nassir Navab,Michael Friebe
出处
期刊:Sensors
[Multidisciplinary Digital Publishing Institute]
日期:2020-07-19
卷期号:20 (14): 4018-4018
被引量:22
摘要
Longitudinal and perpendicular changes in the vocal fold's blood vessels are associated with the development of benign and malignant laryngeal lesions. The combination of Contact Endoscopy (CE) and Narrow Band Imaging (NBI) can provide intraoperative real-time visualization of the vascular changes in the laryngeal mucosa. However, the visual evaluation of vascular patterns in CE-NBI images is challenging and highly depends on the clinicians' experience. The current study aims to evaluate and compare the performance of a manual and an automatic approach for laryngeal lesion's classification based on vascular patterns in CE-NBI images. In the manual approach, six observers visually evaluated a series of CE+NBI images that belong to a patient and then classified the patient as benign or malignant. For the automatic classification, an algorithm based on characterizing the level of the vessel's disorder in combination with four supervised classifiers was used to classify CE-NBI images. The results showed that the manual approach's subjective evaluation could be reduced by using a computer-based approach. Moreover, the automatic approach showed the potential to work as an assistant system in case of disagreements among clinicians and to reduce the manual approach's misclassification issue.
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