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A Model-based Approach to Comparing Breast Images

基于模型的乳房图像比较方法

基本信息

批准号：
EP/E031307/1
负责人：
Chris Taylor
金额：
$ 48.66万
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2008
资助国家：
英国
起止时间：
2008 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FE031307%2F1
关键词：
Model based Approach Comparing Breast

项目摘要

X-ray mammography is the method of choice in screening for breast cancer. Mammograms are x-ray images of the breast, taken with the breast tightly compressed between approximately parallel plates. Two different views, are commonly used: cranio-caudal (CC / looking vertically down on the breast) and medio-lateral oblique (MLO / looking at the breast from the opposite shoulder). In a few cases, potential signs of cancer can be detected in a single mammogram, but more usually, radiologists detect abnormalities by comparing mammograms. In bilateral comparison, the radiologist compares the mammograms of the left and right breasts and looks for asymmetries and architectural distortions between the images, though these terms are ill-defined (and thus not easily built into an algorithm). In temporal comparison, the radiologist compares the current mammogram with the previous one and looks for signs of significant change. In multi-view comparison, the radiologist compares the CC and MLO views of the same breast and looks for consistent evidence of an abnormality. Through experience, radiologists learn to make these comparisons, but the task is intrinsically difficult, because the effects of biological variation, soft tissue deformation, and projection imaging are confounded, so that establishing point-by-point correspondence between mammograms is impossible. Our aim is to develop computational methods for assisting the radiologist in this comparison. We plan to take a comprehensive model-based approach to making meaningful comparisons. This will draw on our previous experience of image registration together with modelling the statistics of anatomical variability, the biomechanics of tissue deformation, and the physics of image formation. To understand the effects of these different sources of variability in 2D mammograms, and develop appropriate models, we will make use of a large existing collection of 3D MR breast images, with corresponding mammograms. The application to breast imaging is of value in its own right, with the potential to make a significant contribution to more effective systems for computer-aided detection, but the methods we propose to develop are generic and capable of broad application to other applications in medical image analysis, where organs are imaged whilst undergoing mechanical deformation / for example, the heart, liver, lung, stomach and colon.

X 射线乳房X 线摄影是筛查乳腺癌的首选方法。乳房X光检查是乳房的X射线图像，是在将乳房紧紧压缩在近似平行的板之间时拍摄的。 Two different views, are commonly used: cranio-caudal (CC / looking vertically down on the breast) and medio-lateral oblique (MLO / looking at the breast from the opposite shoulder).在少数情况下，可以在单次乳房X光检查中检测到潜在的癌症迹象，但更常见的是，放射科医生通过比较乳房X光检查来检测异常情况。在双边比较中，放射科医生会比较左右乳房的乳房X光照片，并寻找图像之间的不对称性和结构扭曲，尽管这些术语定义不明确（因此不容易构建到算法中）。在时间比较中，放射科医生将当前的乳房 X 光检查与之前的乳房 X 光检查进行比较，并寻找显着变化的迹象。在多视图比较中，放射科医生会比较同一乳房的 CC 和 MLO 视图，并寻找一致的异常证据。通过经验，放射科医生学会了进行这些比较，但这项任务本质上是困难的，因为生物变异、软组织变形和投影成像的影响是混杂的，因此不可能在乳房X光照片之间建立逐点对应关系。我们的目标是开发计算方法来协助放射科医生进行这种比较。我们计划采用基于模型的综合方法来进行有意义的比较。这将利用我们之前的图像配准经验，以及对解剖变异性统计、组织变形的生物力学和图像形成的物理学进行建模。为了了解 2D 乳房 X 光照片中这些不同变异源的影响并开发适当的模型，我们将利用大量现有的 3D MR 乳房图像以及相应的乳房 X 光照片。乳腺成像的应用本身就具有价值，有可能为更有效的计算机辅助检测系统做出重大贡献，但我们建议开发的方法是通用的，能够广泛应用于医学图像分析的其他应用，其中器官在经历机械变形时进行成像（例如心脏、肝脏、肺、胃和结肠）。