Rule-Based CAD of Digitized Mammograms

基于规则的数字化乳房 X 光检查 CAD

• 批准号: 6846047
• 负责人: DAVID GUR
• 金额: $ 27.49万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-15 至 2007-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6846047
• 关键词: bioimaging /biomedical imaging; clinical research; computer assisted diagnosis; diagnosis design /evaluation; diagnosis quality /standard; digital imaging; female; human data; mammography

DESCRIPTION (provided by applicant): Given the recognized and widely accepted importance of mammography in early identification of breast cancer in general, and in screening, in particular, computer-aided diagnosis (CAD) schemes for mammography have been developed and investigated extensively in recent years. The diagnostic performance of some CAD systems is at the point where clinical utility has been demonstrated. However, despite significant efforts and major improvements, the performance level of CAD schemes, particularly as related to masses, remains less than optimal. In addition, it is becoming increasingly important to explore ways not only to optimize these schemes, but also to assess and compare their performance and robustness when used in the clinical environment. As we increase efforts to detect abnormalities at an earlier stage, this field is likely to progress incrementally in several important areas. In this project, we propose to continue to conduct a variety of studies to improve and test the performance and robustness of several of our own CAD schemes. We will also assess a number of issues associated with system's performance when multiple images, such as multiple views or sequences of images, are available and are used to optimize the results of a diagnostic examination. Many of the methods we will develop and the techniques we propose to use in order to optimize performance and assure robustness of these schemes should be applicable to other investigations in this and related fields. Last, there is no direct comparison of schemes developed by different groups (and companies) that will enable a better understanding of some of the advantages and limitations of different approaches. We propose to do so twice during the project on a large number of biopsy-proven cases.

描述（由申请人提供）：考虑到乳房X线照相术在乳腺癌早期识别、特别是筛查中的重要性已得到公认和广泛接受，近年来，乳房X线照相术的计算机辅助诊断（CAD）方案已得到广泛开发和研究。年。某些 CAD 系统的诊断性能已达到临床实用性。然而，尽管付出了巨大的努力和重大改进，CAD 方案的性能水平（尤其是与质量相关的性能水平）仍然达不到最佳水平。此外，探索优化这些方案的方法，以及评估和比较它们在临床环境中使用时的性能和稳健性变得越来越重要。随着我们加大在早期阶段检测异常的力度，该领域可能会在几个重要领域取得逐步进展。在这个项目中，我们建议继续进行各种研究，以改进和测试我们自己的几个 CAD 方案的性能和稳健性。当多个图像（例如多个视图或图像序列）可用并用于优化诊断检查结果时，我们还将评估与系统性能相关的许多问题。我们将开发的许多方法和我们建议使用的用于优化性能并确保这些方案的稳健性的技术应该适用于该领域和相关领域的其他研究。最后，没有对不同团体（和公司）开发的方案进行直接比较，从而可以更好地理解不同方法的一些优点和局限性。我们建议在项目期间对大量活检证实的病例进行两次。