Computer Aided Detection for CT Colonography

CT 结肠成像的计算机辅助检测

• 批准号: 8565352
• 负责人: Ronald M. Summers
• 金额: --
• 依托单位: CLINICAL CENTER
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8565352
• 关键词: Affect; American; Cancer Etiology; Cathartics; Cessation of life; Clinical; Colon; Colonic Polyps; Colonoscopes; Colonoscopy; Colorectal; Colorectal Cancer; Computed Tomographic Colonography; Computer Assisted; Computer-Assisted Diagnosis; Detection; Diagnosis; Economics; Future; Goals; Human; Image; Incidence; Intestines; Laboratories; Length; Malignant Neoplasms; Mechanics; Methods; Modeling; Modification; Muscle; Optics; Patients; Perception; Performance; Physicians; Polyps; Preparation; Property; Research; Screening procedure; Sedation procedure; Sensitivity and Specificity; System; Taenia Coli; Techniques; Testing; Time; Training; Tube; colorectal cancer screening; computer aided detection; improved; innovation; novel; radiologist; research study; software development

We are improving CT colonography (virtual colonoscopy) by developing computer-assisted diagnosis methods. These methods attempt to identify and characterize colonic polyps automatically, thereby increasing physician accuracy and efficiency and helping patients by finding their polyps. We made a number of advances over the past year, including advances in polyp detection, false positive reduction and classifier optimization. We improved our innovative technique to use the tenia coli (longitudinal muscle bands) as a guide for orienting the supine and prone virtual colonoscopies. This technique has broad implications for research and clinical image interpretation. We are improving methods to co-register virtual colonoscopies and optical colonoscopies of the same patient by modeling the mechanical properties of colonoscopes. We are using novel crowdsourcing methods to conduct large-scale observer performance experiments to help us understand factors that promote improved diagnosis using computer-aided polyp detection. We developed a method to "electronically cleanse" the colon so that patients can avoid the need for cathartics in the bowel preparation for virtual colonoscopy, potentially leading to a more patient-friendly bowel preparation.

我们正在通过开发计算机辅助诊断方法来改善CT结肠造影（虚拟结肠镜检查）。 这些方法试图自动识别和表征结肠息肉，从而提高医师的准确性和效率，并通过寻找息肉来帮助患者。 在过去的一年中，我们取得了许多进步，包括息肉检测的进步，假阳性减少和分类器优化。我们改进了创新技术，使用Tenia Goli（纵向肌肉带）作为指导仰卧和俯卧的虚拟结肠镜检查的指南。该技术对研究和临床图像解释具有广泛的影响。我们正在改善通过对同一患者进行虚拟结肠镜检查和光学结肠镜检查的方法，通过对结肠镜的机械性能进行建模。我们正在使用新型的众包方法来进行大规模的观察者性能实验，以帮助我们了解使用计算机辅助息肉检测来改善诊断的因素。我们开发了一种“以电子方式清洁”结肠的方法，以便患者可以避免在肠道准备虚拟结肠镜检查中需要进行宣泄，从而导致更友好的肠术。