Computer-Aided Diagnosis of Breast Lesions in Mammograms

乳房 X 光检查中乳腺病变的计算机辅助诊断

• 批准号: 7842671
• 负责人: Yulei Jiang
• 金额: $ 31.34万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-04-01 至 2014-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7842671
• 关键词: Address; Biopsy; Breast; Breast Cancer Detection; Classification; Clinical; Computer Assisted; Computer-Assisted Diagnosis; Computers; Detection; Diagnosis; Diagnostic; Early Diagnosis; Effectiveness; Ensure; Goals; Hand; Health; Image; Image Analysis; Imaging Device; Investigation; Lateral; Lead; Lesion; Location; Magnetic Resonance Imaging; Malignant - descriptor; Malignant Neoplasms; Mammography; Methods; Performance; Reproducibility; Research; Research Design; Research Personnel; Screening procedure; Source; Techniques; Testing; Theoretical Studies; Ultrasonography; Work; base; breast lesion; burden of illness; calcification; clinically significant; digital imaging; effective therapy; imaging modality; improved; innovation; malignant breast neoplasm; novel; pre-clinical; public health relevance; radiologist; research clinical testing; tool

DESCRIPTION (provided by applicant): The application's broad, long-term objective is to reduce the disease burden of breast cancer through early detection and accurate diagnosis, which lead to effective treatment. The goal of this project is to develop innovative approaches to computer-aided diagnosis (CADx) of breast calcifications for breast cancer detection and diagnosis. Other researchers in our group are developing CADx for breast masses separately, in conjunction with this project, because diagnostic workup of breast masses requires multi-modality imaging (ultrasound and MRI) in addition to mammography. We will test the hypothesis that CADx of breast calcifications can help improve breast cancer detection and diagnosis. The Specific Aims of this project are: (1) reduce or eliminate influence on computer classification from inter- and intra-radiologist variability in their interaction with the computer; (2) investigate computer classification of magnification mammogram; (3) investigate and reduce computer variability in classification of a lesion in multiple views; and (4) investigate potential benefit of CADx to enhance the effectiveness of computer-aided detection (CADe) in screening mammography. The research design will be to understand the mechanisms of computer variability in its calculations from the identified sources, to develop new techniques to minimize computer calculation variability, to develop new techniques for new CADx applications, and to perform an observer performance study to show that CADx can potentially enhance the effectiveness of CADe. The methods to be used include computer image analysis, statistical classifier, ROC analysis, statistical comparison, and observer performance study. The rationales for pursuing these goals include an anticipated need to address critical clinical acceptance issues of CADx based on already demonstrated high performance of our CADx technique and a planned pre-clinical and clinical evaluation of CADx, and a new opportunity for potential novel application of CADx to enhance the effectiveness of CADe. The techniques that we will use are either proven in previous investigations, or based on theoretical studies, or based on our observation in working with radiologists developing CADx techniques. The importance and health relatedness of the research described in this application is that it will address significant limitations of current CADx technique that likely will hinder clinical acceptance of CADx and will address an innovative potential for CADx to enhance the effectiveness of CADe in breast cancer detection. If the Aims of the application are achieved, CADx will be advanced technologically and will become more clinically acceptable to radiologists: once clinical benefit of CADx is demonstrated, CADx will become an important new clinical tool for breast cancer detection and diagnosis. PUBLIC HEALTH RELEVANCE: The goal of this project is to develop innovative approaches to computer-aided diagnosis (CADx) of breast calcifications for breast cancer detection and diagnosis. This project will address significant limitations of current CADx technique with the objective of advancing CADx to become a clinical tool for breast cancer detection and diagnosis.

描述（由申请人提供）：该应用程序的广泛，长期目标是通过早期检测和准确诊断来减少乳腺癌的疾病负担，从而获得有效的治疗。该项目的目标是开发用于乳腺癌检测和诊断的乳腺钙化的计算机辅助诊断（CADx）的创新方法。我们小组的其他研究人员正在结合该项目单独开发乳腺肿块的CADx，因为乳腺肿块的诊断检查除了乳房X线摄影外还需要多模态成像（超声和MRI）。我们将测试乳腺钙化的CADx可以帮助提高乳腺癌检测和诊断的假设。本项目的具体目标是：（1）减少或消除放射科医师与计算机交互时的内部和内部差异对计算机分类的影响;（2）研究放大乳腺X线照片的计算机分类;（3）研究并减少多个视图中病变分类的计算机差异;（4）研究CADx在提高计算机辅助检测（CADe）在筛查乳腺X线摄影中的有效性方面的潜在益处。研究设计将是从确定的来源，以了解其计算的计算机可变性的机制，开发新的技术，以尽量减少计算机计算的变化，开发新的CADx应用程序的新技术，并进行观察员的性能研究，以表明CADx可以潜在地提高CADe的有效性。所采用的方法包括计算机图像分析、统计分类、ROC分析、统计比较和观察者表现研究。追求这些目标的理由包括：基于我们的CADx技术已经证明的高性能和计划的CADx临床前和临床评价，预期需要解决CADx的关键临床验收问题，以及CADx潜在新应用的新机会，以增强CADe的有效性。我们将使用的技术要么在以前的研究中得到证明，要么基于理论研究，要么基于我们与放射科医生合作开发CADx技术的观察。本申请中描述的研究的重要性和健康相关性在于，它将解决当前CADx技术的重大局限性，这些局限性可能会阻碍CADx的临床接受，并将解决CADx的创新潜力，以增强CADe在乳腺癌检测中的有效性。如果该应用程序的目标得以实现，CADx将在技术上取得进步，并将成为放射科医生在临床上更容易接受的工具：一旦CADx的临床受益得到证实，CADx将成为乳腺癌检测和诊断的重要新临床工具。公共卫生相关性：该项目的目标是开发乳腺钙化计算机辅助诊断（CADx）的创新方法，用于乳腺癌检测和诊断。该项目将解决当前CADx技术的重大局限性，旨在推动CADx成为乳腺癌检测和诊断的临床工具。