Development of a computer-aided algorithm using artificial intelligence for the segmentation of ultrasonographic features of lymph nodes during endobronchial ultrasound.

使用人工智能开发计算机辅助算法，用于支气管内超声期间淋巴结的超声特征分割。

• 批准号: 411232
• 负责人: Churchill Isabella F
• 金额: $ 1.27万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Studentship Programs
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-12-01 至 2019-12-01
• 项目状态: 已结题
• 来源: https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=411232&lang=en
• 关键词: Artificial Intelligence; Endobronchial Ultrasound; Lung Cancer; Lymph Nodes; Machine Learning; Ultrasonographic Features

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer death worldwide, warranting the need for accurate lymph node (LN) staging to determine treatment plans. A four-point, binary scale known as the Canada Lymph Node Score has p

肺癌是最常诊断的癌症，也是全球癌症死亡的主要原因，因此需要准确的淋巴结（LN）分期来确定治疗计划。一个四点，二进制规模被称为加拿大淋巴结评分有p