CAD FOR EARLIER DETECTION OF BREAST CANCER

描述(逐字摘自申请人摘要)：尽管乳房X光检查有 事实证明，这是最可靠和最具成本效益的早期治疗方法 在筛查环境中检测乳腺癌，乳房X光照相 口译是相当困难的，因为需要时间，复杂的 组织模式，以及低产量。所有当前的CAD方案都使用功能 从当时的图像和异常中提取出来的积极读数 已经被执行了。因此，这些系统经过优化，可用于检测 与确定的典型水平处于同一发展阶段的异常 由一位经验丰富的读者撰写。在这个项目中，我们打算开发和测试CAD 专注于优化具有以下特征的图像的检测的方案 被解释为阴性，但患者被发现患有乳腺癌 在接下来的一次(稍后)的研究中。该项目不仅将探索一种 检测微小和微小癌症的新方法，可能会带来巨大的好处 对患者来说，因为早期发现乳房溃疡可以实质上 降低死亡率和发病率。

DESCRIPTION (Verbatim from Applicant's Abstract): Although mammography has proven to be the most reliable and cost‑effective method for the early detection of breast cancer in a screening environment, mammographic interpretation is quite difficult, due to time required, the complexity of tissue patterns, and the low yield. All current CAD schemes use features extracted from images and abnorrnalities at the time when a positive reading was performed. Hence these systems are optimized for the detection of abnorrnalities at the same stage of development as the typical level identified by an experienced reader. In this project we propose to develop and test CAD schemes that focus on optimization of the detection in marnmograms that had been interpreted as negative but the patients were found to have breast cancers on a follow‑up (later) exarnination. This project will not only explore a new approach to detect small and subtle cancers, it may result in great benefit to the patients, since earlier detection of breast aulcer can substantially reduce mortality amd morbidity.