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Advanced image reconstruction for accurate and high-resolution breast ultrasound tomography

Advanced image reconstruction for accurate and high-resolution breast ultrasound tomography
先进的图像重建,可实现精确、高分辨率的乳腺超声断层扫描
批准号:
10442593
负责人:
Mark A Anastasio
金额:
$57.49万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-13 至 2024-05-31

项目摘要

项目成果

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中文摘要
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英文摘要
ABSTRACT The broad objective of this project is to develop and refine advanced tomographic image reconstruction methods for ultrasound computed tomography (UST), referred to as waveform inversion methods, which will permit high resolution and quantitative breast imaging. These methods will yield volumetric estimates of the speed of sound (SOS) and acoustic attenuation (AA) distributions within the breast. The SOS and AA represent bio-parameters that can reveal differences in the geometric and elastic properties of tissue. Such information can greatly facilitate the differentiation of breast cancer from normal tissue or benign disease. Accordingly, UST holds great potential for improving the detection and management of breast cancer since it exploits effective endogenous tissue contrasts, is radiation- and breast-compression-free, and is relatively inexpensive. The SoftVue whole breast UST system developed by members of our team has been awarded FDA 510(k) clearance for diagnostic applications. Most reported methods for breast UST are ray-based and do not take into account acoustic diffraction effects; this results in images of relatively poor spatial resolution and accuracy. This is highly undesirable for breast imaging applications, in which the ability to resolve fine features is important for distinguishing healthy from diseased tissues. Waveform inversion methods for UST image reconstruction are based on the full acoustic wave equation and can circumvent the limitations of ray-based methods, thereby permitting high- resolution quantitative UST breast imaging. However, the application of waveform inversion methods to breast UST employing ring-transducer arrays has to-date employed 2D reconstruction methods to estimate sectional UST images. Because 3D wave propagation physics and the focusing properties of the transducers are not accounted for in this 2D approach, the images can contain significant artifacts and degraded spatial resolution. In this project, we will develop and optimize 3D UST waveform inversion methods for reconstructing SOS and AA images of the breast of unprecedented quality. These methods will utilize acoustic data measured at one or more locations of the ring-transducer array and will compensate for 3D wave physics and the focusing properties of the transducers. In this approach, a thin (in height) volume will be reconstructed instead of a single 2D slice. Whole breast imaging can then be accomplished by merging the thin reconstructed volumes corresponding to different locations instead of stacking lower quality 2D slices as done in existing 2D methods. The developed methods will be evaluated and refined by use of phantom and clinical data. The specific aims of this project are: (1) Develop waveform inversion methods for high resolution SOS imaging; (2) Develop waveform inversion methods for high resolution AA imaging; (4) Refinement of reconstruction methods via breast phantom studies; (5) Assessment and refinement of reconstruction methods using clinical data.
期刊论文(1)
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会议论文
DOI: 10.1109/tuffc.2023.3313549
发表时间: 2023-10
期刊: IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL
影响因子: 3.6
作者: [Li, Fu, Villa, Umberto, Duric, Nebojsa, Anastasio, Mark A]
通讯作者: Anastasio, Mark A
Deep learning technologies for estimating the optimal task performance of medical imaging systems
A Computational Framework Enabling Virtual Imaging Trials of 3D Quantitative Optoacoustic Tomography Breast Imaging
Computational imaging and intelligent specificity (Anastasio)
A Computational Framework Enabling Virtual Imaging Trials of 3D Quantitative Optoacoustic Tomography Breast Imaging
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