Computer-Aided Diagnosis of Breast Lesions in Mammograms
Computer-Aided Diagnosis of Breast Lesions in Mammograms
批准号:
7580691
负责人:
Yulei Jiang
金额:
$31.34万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-04-01 至 2014-05-31
关键词:
AddressBiopsyBreastBreast Cancer DetectionClassificationClinicalComputer AssistedComputer-Assisted DiagnosisComputersDetectionDiagnosisDiagnosticEarly DiagnosisEffectivenessEnsureGoalsHandHealthImageImage AnalysisImaging DeviceInvestigationLateralLeadLesionLocationMagnetic Resonance ImagingMalignant - descriptorMalignant NeoplasmsMammographyMethodsPerformanceReproducibilityResearchResearch DesignResearch PersonnelScreening procedureSourceTechniquesTestingTheoretical StudiesUltrasonographyWorkbasebreast lesionburden of illnesscalcificationclinically significantdigital imagingeffective therapyimaging modalityimprovedinnovationmalignant breast neoplasmnovelpre-clinicalpublic health relevanceradiologistresearch clinical testingtool
中文摘要
描述(申请人提供):该申请的广泛和长期目标是通过早期发现和准确诊断减少乳腺癌的疾病负担,从而导致有效的治疗。该项目的目标是开发用于乳腺癌检测和诊断的乳房钙化计算机辅助诊断(CADx)的创新方法。我们团队中的其他研究人员正在结合这个项目单独开发用于乳房肿块的CADx,因为乳房肿块的诊断工作除了乳房X光检查外,还需要多模式成像(超声波和MRI)。我们将检验这一假设,即乳房钙化的CADx有助于提高乳腺癌的检测和诊断。该项目的具体目标是:(1)减少或消除放射科医生之间和内部在与计算机交互时对计算机分类的影响;(2)研究放大乳房X光照片的计算机分类;(3)在多个切面下调查和减少计算机对病变分类的可变性;以及(4)调查CADx的潜在益处,以提高计算机辅助检测(CADE)在筛查乳房X光检查中的有效性。研究设计将从已确定的来源了解计算机在计算中的可变性的机制,开发新的技术以最大限度地减少计算机计算的可变性,为新的CADx应用开发新的技术,并进行观察者性能研究,以表明CADx可以潜在地增强CADE的有效性。将使用的方法包括计算机图像分析、统计分类器、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对CADx的计划的临床前和临床评估,预期需要解决CADx的关键临床接受问题,以及潜在的CADx的潜在新应用以增强CADe的有效性的新机会。我们将使用的技术要么在以前的研究中得到证实,要么基于理论研究,或者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与健康相关的是,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,以提高CADx在乳腺癌检测中的有效性。如果应用的目标实现,CADx将在技术上得到进步,并将在临床上更容易被放射科医生接受:一旦CADx的临床益处得到证明,CADx将成为乳腺癌检测和诊断的重要新的临床工具。公共卫生相关性:该项目的目标是开发用于乳腺癌检测和诊断的乳房钙化的计算机辅助诊断(CADx)的创新方法。该项目将解决当前CADx技术的重大局限性,目标是推动CADx成为乳腺癌检测和诊断的临床工具。
英文摘要
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.
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会议论文
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