Incomplete Inverse Problems in Nondestructive Testing and Imaging with Penetrating Radiation

穿透辐射无损检测和成像中的不完全反问题

• 批准号: 4116-2013
• 负责人: Hussein, Esam
• 金额: $ 2.7万
• 依托单位: University of Regina
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=686948
• 关键词: Incomplete; Inverse; Problems; Nondestructive; Testing

Incomplete problems are encountered in scientific and engineering investigations when available measurable indications are not sufficient, or are not fully credible, to enable the determination of the state of a studied system. In radiological imaging, such incompleteness is compensated for by expert judgement and knowledge of the nature of the examined object or subject, or by comparison to previous or other independent indications. Although such measures are often effective, they sometimes fail, as evident by the medical imaging misdiagnosis reported in Canada and elsewhere within the past few years. Given available computing power, in terms of memory and speed, and the wide use of digital imaging, it is not inconceivable to numerically analyze such images in terms of the quality of data, the quality of the image and even the credibility of diagnosis. This can be accomplished by incorporating expert knowledge as probabilistic estimates with a certain degree of influence, or by accommodating other indications as constraints and utilizing previous trends to confine the range of assessment. Information from such exercise can also be utilized as feedback to the imaging process itself to improve its quality.This proposal addresses these incomplete problems in the particular area of non-destructive computed imaging with atomic/nuclear radiation for industrial, security and nuclear safeguard applications. The three fronts of (1) the quality of input data, (2) the image reconstruction process and (3) the quality of the produced image will be tackled. Methods for feedback from one front to the other will be developed. The goal is to benefit from expert knowledge and other available information, while liberating the process from subjective judgement. The developed processes can subsequently be adopted in medical imaging.

在科学和工程研究中，当可用的可测量的指示不充分或不完全可信时，就会遇到不完全问题，无法确定所研究系统的状态。在放射成像中，这种不完整可以通过专家判断和对被检查对象或主体性质的了解，或通过与先前或其他独立指征的比较来弥补。虽然这些措施通常是有效的，但它们有时会失败，正如过去几年在加拿大和其他地方报告的医学成像误诊所表明的那样。鉴于现有的计算能力，就内存和速度而言，以及数字成像的广泛使用，从数据质量、图像质量甚至诊断的可信度方面对此类图像进行数值分析并非不可想象。这可以通过将专家知识作为具有一定影响程度的概率估计来实现，或者通过将其他指示作为约束并利用以前的趋势来限制评估范围来实现。来自这种练习的信息也可以用作对成像过程本身的反馈，以提高其质量。本提案解决了工业、安全和核保障应用中原子/核辐射非破坏性计算机成像特定领域的这些不完整问题。将解决(1)输入数据的质量，(2)图像重建过程和(3)生成图像的质量这三个方面。将发展从一个方面到另一个方面的反馈方法。目标是从专家知识和其他可用信息中获益，同时将过程从主观判断中解放出来。所开发的过程可随后用于医学成像。