Developing a fully automatic segmentation algorithm for breast MRI

开发乳腺 MRI 全自动分割算法

• 批准号: 434897-2012
• 负责人: Martel, Anne
• 金额: $ 8.13万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Idea to Innovation
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=499041
• 关键词: Developing; fully; automatic; segmentation; algorithm

Magnetic resonance imaging of the breast is a more sensitive method of detecting breast cancer than conventional x-ray mammography and it is now recommended for screening women who are known to be at higher risk of breast cancer. The number of breast MRI exams carried out in Canada and around the world is increasing rapidly and this has lead to a major problem in finding enough trained radiologists to interpret the exams. Each MRI exam contains over 1000 images and reviewing all of the information is time consuming. This has lead to a huge demand for workstations that are able to support the radiologist and streamline the work flow by preparing the images for 3D viewing and using image processing techniques to identify suspicious regions.

乳房磁共振成像是一种比传统的x射线乳房x光检查更敏感的检测乳腺癌的方法，现在它被推荐用于筛查已知有较高乳腺癌风险的妇女。在加拿大和世界各地进行的乳房核磁共振检查的数量正在迅速增加，这导致了一个主要问题，即寻找足够的训练有素的放射科医生来解释这些检查。每个MRI检查包含超过1000张图像，回顾所有信息是非常耗时的。这导致了对工作站的巨大需求，这些工作站能够支持放射科医生，并通过准备3D查看图像和使用图像处理技术识别可疑区域来简化工作流程。