Interactive CAD for Mammography

用于乳腺 X 线摄影的交互式 CAD

• 批准号: 6770917
• 负责人: Bin Zheng
• 金额: $ 16.86万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6770917
• 关键词: clinical research; computer assisted diagnosis; computer data analysis; computer system design /evaluation; health science profession; human data; interactive multimedia; mammography; radiology; women' s health

DESCRIPTION (provided by applicant): Although commercial computer-aided detection (CAD) products have been used in a large number of medical institutions to assist radiologists in screening mammography, radiologists often have limited confidence in CAD cueing results for masses due to the relatively low sensitivity and reproducibility, as well as the higher false-positive rate, than that compared with the performance for microcalcification detection and characterization. There is no general agreement on whether and how a CAD system can best help improve radiologists' diagnostic performance. To address these issues, we propose to develop and evaluate a unique Interactive Computer-Aided Detection (ICAD) system for mammography. In addition to providing initial cues on the processed images as would current systems, radiologists can interact with the ICAD system in several ways. Observers can select any regions (cued or not cued) on the mammogram and query ICAD. Upon receiving a request from the observer, ICAD will extract the region, compute a feature vector, compare the vector with a large number of regions in a reference library, and generate a classification score using a weighted k-nearest neighbor algorithm. In addition, upon request, the system will provide the results of a scheme specifically optimized on "the latest prior images" to enable observers to assess "early signs" for abnormalities that may develop and later (on subsequent examinations) prove to be malignant. To test such a hypothesis, an observer performance study will also be carried out in this project to compare the performance difference when six radiologists use a CAD system operating at the performance level of leading commercial products and our newly proposed ICAD system.

描述（由申请人提供）： 虽然商业计算机辅助检测（CAD）产品已在大量的医疗机构中使用，以帮助放射科医生在筛查乳腺X射线摄影，放射科医生往往有有限的信心，在CAD提示结果的质量，由于相对较低的灵敏度和再现性，以及较高的假阳性率，相比，微钙化检测和表征的性能。关于CAD系统是否以及如何最好地帮助提高放射科医生的诊断能力，目前还没有普遍的共识。为了解决这些问题，我们建议开发和评估一个独特的交互式计算机辅助检测（ICAD）系统的乳房X线摄影。除了像当前系统那样在处理后的图像上提供初始提示之外，放射科医生还可以通过多种方式与ICAD系统进行交互。观察者可以选择乳房X线照片上的任何区域（提示或未提示）并查询ICAD。在收到来自观察者的请求后，ICAD将提取区域，计算特征向量，将该向量与参考库中的大量区域进行比较，并使用加权k最近邻算法生成分类得分。此外，该系统将根据要求提供一个专门针对“最新的先前图像”进行优化的方案的结果，使观察者能够评估可能出现的异常的“早期迹象”，并在随后的检查中证明是恶性的。为了验证这一假设，本项目还将进行一项观察员性能研究，以比较六名放射科医生使用CAD系统时的性能差异，CAD系统的性能水平与我们新提出的ICAD系统的性能水平相同。