Copy of Digital Breast Tomosynthesis

数字乳房断层合成的副本

• 批准号: DT/F002785/1
• 负责人: David Hawkes
• 金额: $ 37.67万
• 依托单位: University College London
• 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=DT%2FF002785%2F1
• 关键词: Copy; Digital; Breast; Tomosynthesis

We propose a project that combines the skills of the imaging groups at UCL and Oxford with the expertise of Dexela, a UK SME dedicated to the development and commercialisation of DBT that was co-founded by leading researchers in DBT from the US. The project will be managed by Dexela. Our clinical advisory group will comprise radiologists from King's College Hospital, the Royal Marsden Hospital, and St. Bartholomew's Hospital, all in London, together with The Massuchusetts General Hospital in the US. The overall aim of our project is to establish Digital Breast Tomosynthesis (DBT) as the modality of choice in breast cancer detection by enhancing its sensitivity and specificity sufficiently to create compelling clinical and economic benefits. We will first establish DBT for difficult cases (e.g. the dense breast, previous surgery, younger women, implants and suspicious regions in inaccessible areas), while aiming ultimately to replace mammography in national screening programmes. This project combines innovative work in optical imaging of the breast and neo-natal brain (Arridge), in mammography image processing (Brady), in registration and change detection (Hawkes) and DBT (Dexela). While some of the core components already exist in isolation, this project is the first attempt at such a combination and novel contributions are expected in all the areas. The new DBT image acquisition device developed by Dexela will have a superior geometry to existing systems and significant flexibility in acquisition geometry, breast compression and exposure parameters per view. The project will explore the optimisation of acquisition parameters informed by sophisticated image processing. The innovative steps concern: i) iterative reconstruction methods applied to very large DBT datasets (over 1 gigabyte) verses filtered back projection (FBP), ii) the wide 90 degree angular range (verses 16-50 degrees for the majors) and variable angular spacing of projections iii) varying voltage, current and detector resolution between projections (verses invariant parameters) iv) the low number of projection images (11 verses 15- 48), which results in faster acquisition, less patient movement and better signal to noise ratio, v) the implementation of Intelligent Image Acquisition which provides real-time feedback to the image acquisition parameters, and vi) the innovative combination of 4D reconstruction methods, and change detection. The work on registration and automated comparison in DBT is innovative and there is no similar research which has been reported related to DBT. This innovative work may have application beyond this field in other medical and non-medical applications.

我们提出了一个项目，将伦敦大学学院和牛津大学成像团队的技能与Dexela的专业知识结合起来，Dexela是一家致力于DBT开发和商业化的英国中小企业，由来自美国的DBT领域的领先研究人员共同创立。该项目将由德克塞拉管理。我们的临床顾问团将包括来自伦敦国王学院医院、皇家马斯登医院和圣巴塞洛缪医院的放射科医生，以及美国的马萨诸塞州综合医院。我们项目的总体目标是通过充分提高数字乳腺断层扫描(DBT)的敏感性和特异性，使其成为乳腺癌检测的首选方法，从而创造令人信服的临床和经济效益。我们将首先为疑难病例(例如乳房致密、以前的手术、年轻妇女、植入物和人迹罕至地区的可疑区域)建立DBT，同时最终目标是在国家筛查计划中取代乳房X光检查。该项目结合了乳房和新生儿大脑光学成像(Arbridge)、乳房X光照相图像处理(Brady)、配准和变化检测(Hawkes)和DBT(Dexela)方面的创新工作。虽然一些核心组成部分已经孤立存在，但该项目是这种组合的第一次尝试，预计所有领域都将做出新的贡献。Dexela开发的新DBT图像采集设备将拥有比现有系统更优越的几何形状，并在每个视图的采集几何形状、乳房压缩和曝光参数方面具有极大的灵活性。该项目将探索通过复杂的图像处理来优化采集参数。创新步骤涉及：i)应用于非常大的DBT数据集(超过1千兆字节)与滤波反投影(FBP)的迭代重建方法，ii)宽90度角度范围(相对于主要的16-50度)和可变的投影的角间距，iii)改变投影之间的电压、电流和探测器分辨率(相对于不变参数)IV)低数量的投影图像(11对15-48)，这导致更快的采集、更少的耐心移动和更好的信噪比，v)实现向图像采集参数提供实时反馈的智能图像采集，以及vi)4D重建方法的创新组合，和变化检测。DBT中的注册和自动比对工作是创新的，目前还没有关于DBT的类似研究报告。这一创新工作可能会在该领域以外的其他医疗和非医疗应用中得到应用。

项目成果

Using statistical deformation models for the registration of multimodal breast images

使用统计变形模型来配准多模态乳房图像

• DOI: 10.1117/12.811631
• 发表时间: 2009
• 作者: Tanner C

Automated registration of diagnostic to prediagnostic x-ray mammograms: evaluation and comparison to radiologists' accuracy.

诊断到诊断前 X 射线乳房 X 射线照片的自动注册：与放射科医生准确性的评估和比较。

• DOI: 10.1118/1.3457470
• 发表时间: 2010
• 期刊: Medical physics
• 影响因子: 3.8
• 作者: Pinto Pereira SM