Limited Angle Image Reconstruction

有限角度图像重建

• 批准号: 8633010
• 负责人: Emil Y Sidky
• 金额: $ 30.97万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2016-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8633010
• 关键词: Address; Affect; Algorithms; Breast; Breast Cancer Early Detection; Breast Microcalcification; Breast Part; Cations; Clinic; Clinical; Clinical Trials; Data; Data Set; Detection; Development; Devices; Digital Breast Tomosynthesis; Digital Mammography; Discipline of Nuclear Medicine; Dose; Evaluation; FDA approved; Goals; Human; Image; Investigation; Lead; Lighting; Malignant Neoplasms; Manufacturer Name; Maps; Masks; Measures; Medical Device; Metric; Modality; Modeling; Modification; Morphologic artifacts; Motion; Muscle; Nature; Noise; Normal tissue morphology; Patients; Performance; Phase; Photons; Positioning Attribute; Reader; Research; Resolution; Roentgen Rays; Scanning; Selection Criteria; Signal Transduction; Staging; Structure; System; Techniques; Testing; Translating; Translations; X-Ray Tomography; attenuation; base; computerized data processing; design; detector; diagnostic accuracy; image reconstruction; improved; interest; mortality; operation; radiologist; reconstruction; theories; tomography; tumor; young woman

DESCRIPTION (provided by applicant): Digital breast tomosynthesis (DBT) is being pursued by many medical device manufacturers, because its limited tomographic capability directly addresses a major short-coming of full-field digital mammography (FFDM). Namely, due to the nature of projection imaging, false positives can occur because overlapping normal tissue structures sometimes resemble tumors, and false negatives happen because tumors may be masked by normal tissue - particularly in dense breasts of young women. Many studies on DBT have been performed or ongoing and the general sense is that DBT does help for tumor detection, but it may perform worse than FFDM on microcalcification detection and characterization, which are imaging tasks that can indirectly indicate malignancy. The proposed research aims at optimizing image reconstruction algorithms for DBT. Our preliminary results indicate already, for example, that microcalcification imaging in DBT is limited by the sub-optimality of the image reconstruction algorithm: our initial investigations already yield a factor-of-two gain in microcalcification signal-to-noise ratio. As many of the current iterative image reconstruction (IIR) algorithms employed in DBT were essentially borrowed, with little modification, from nuclear medicine imaging there is clearly room for large gains in image quality for tailoring IIR to DBT. The fact that DBT devices are already undergoing clinical trials with sub-optimal image reconstruction algorithms increases the urgency of the proposed research. The goal of the research is to show that clinical utility of DBT can be enhanced significantly by tailoring IIR to application in DBT. The aims of the proposed research are: (1) Construct a framework for IIR addressing the limited angular scan and fixed-dose trade-off of image noise and number of projections. (2) Design optimization-based approaches robust against projection truncation. (3) Develop data consistency checks and automated correction techniques for DBT projections. (4) Design image quality metrics of DBT images for algorithm optimization. (5) Evaluate algorithm performance with human observers.

描述（由申请人提供）：数字乳腺断层合成摄影（DBT）正受到许多医疗器械制造商的追捧，因为其有限的断层摄影能力直接解决了全视野数字乳腺X射线摄影（FFDM）的主要缺点。也就是说，由于投影成像的性质，可能发生假阳性，因为重叠的正常组织结构有时类似于肿瘤，并且假阴性发生，因为肿瘤可能被正常组织掩盖-特别是在年轻女性的致密乳房中。已经进行或正在进行许多关于DBT的研究，一般认为DBT确实有助于肿瘤检测，但在微钙化检测和表征方面可能比FFDM表现更差，这是可以间接指示恶性肿瘤的成像任务。该研究旨在优化DBT的图像重建算法。例如，我们的初步结果已经表明，DBT中的微钙化成像受到图像重建算法的次优性的限制：我们的初步研究已经产生了微钙化信噪比的二分之一增益。由于DBT中采用的许多当前迭代图像重建（IIR）算法基本上都是从核医学成像中借用的，几乎没有修改，因此显然有很大的空间来大幅提高图像质量，以便将IIR定制为DBT。DBT设备已经在进行次优图像重建算法的临床试验，这一事实增加了拟议研究的紧迫性。本研究的目的是表明，DBT的临床效用可以通过定制IIR应用于DBT来显着提高。本研究的主要目的是：（1）建立一个有限角度扫描和固定剂量下图像噪声和投影次数的平衡的IIR框架。(2)基于设计优化的方法对投影截断的鲁棒性。(3)为DBT预测开发数据一致性检查和自动校正技术。(4)为算法优化设计DBT图像的图像质量指标。(5)与人类观察者一起评估算法性能。