Compressive sensing-based sparse transducers for ultrasound imaging
Compressive sensing-based sparse transducers for ultrasound imaging
批准号:
RGPIN-2020-07053
负责人:
Masson, Patrice
金额:
$2.84万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31
中文摘要
超声波成像通常用于材料检测和许多疾病的诊断。超声成像的分辨率由多种因素决定,包括换能器的设计和工作频率。为了最大限度地提高分辨率,通常使用高工作频率(>;1 MHz)和多元件换能器,这导致了两个主要限制:1)穿透深度受到传播介质中超声波的大衰减以及与高频下的界面相关的像差和混响的限制;2)与大量换能器元件相关的信号处理的复杂性仍然限制了给定图像质量的可实现的帧速率。到目前为止,大多数工作都集中在成像算法或换能器设计上。使能技术的独特组合将使超声成像在穿透深度和帧速率方面取得重大突破:1)成像算法Excitlet,它利用较低频率的超声波,并内在地考虑全波传播路径的详细模型;2)压缩传感算法,它利用编码传播路径中的多样性;以及3)附加制造技术,它能够在超材料中编码波传播路径。该方案的目标是创建新一代稀疏超声换能器阵列,单元数少,信号处理复杂度低,帧速率高,并工作在低频,提高穿透深度,从而打破现有方法。这些阵列将用于超声成像介质,这些介质可以是工程材料,也可以是生物组织。在大穿透深度和1-10 kHz数量级的帧速率下,横向分辨率可达波长的1/30。这项研究计划沿着三个平行但相关的研究方向进行:1)超声换能器的压缩传感,其中将使用波的类型和频率来丰富信息编码;2)稀疏换能器阵列的优化,其中将在优化过程中考虑激励波;以及3)超声探头制造中的超材料,其中将使用添加制造技术来制造用于编码信息和探头的其他组件的超材料。在材料测试中,这项工作将允许更好地表征先进材料中的损伤先兆,例如复合材料结构(微裂纹、空洞、微屈曲、局部纤维断裂或局部纤维基质脱粘)。在医学诊断方面,这项工作将有助于满足对快速成像帧速率和更高分辨率的近、远场成像的迫切需求,以避免引导手术中周围器官的风险,此外还将扩大穿透深度,以适应日益增长的肥胖人口比例。
英文摘要
Ultrasound imaging is used routinely for material testing and for the diagnosis of many diseases. The resolution of ultrasound imaging is determined by various factors, including transducer design and frequency of operation. To maximize resolution, high operating frequencies (> 1 MHz) and multi-element transducers are usually employed, leading to two major limitations: 1) the penetration depth is limited by the large attenuation of the ultrasonic waves in the propagating medium and by the aberration and reverberation associated with the interfaces at high frequencies, 2) the complexity of the signal processing associated with a large number of transducer elements still limits the achievable frame rate for a given image quality. Until now, most of the work conducted has focused on either imaging algorithms or transducers design. A unique combination of enabling technologies will allow a major breakthrough in the penetration depth and frame rate in ultrasound imaging: 1) the imaging algorithm Excitelet, which exploits lower frequency ultrasound and inherently considers a detailed model of the full wave propagation path, 2) compressive sensing algorithms, which exploit diversity in encoded propagation paths, and 3) additive manufacturing technologies, which enable encoding wave propagation paths within metamaterials. The objective of this program is to create a new generation of sparse ultrasound transducer arrays with a low number of elements, for lower signal processing complexity and higher frame rate, and working at low frequency for improved penetration depth, therefore breaking with existing approaches. The arrays will be used for ultrasound imaging of media which can be either engineering materials or biological tissues. Lateral resolution down to 1/30 of the wavelength is sought at large penetration depth and at a frame rate in the order of 1-10 kHz. This research program articulates along three research thrusts, parallel but related: 1) compressive sensing with ultrasound transducers, where the type of waves and frequencies will be used to enrich information encoding, 2) optimization of sparse transducer arrays, where Excitelet will be considered within the optimization process, and 3) metamaterials in ultrasound probe fabrication, where additive manufacturing techniques will be used to fabricate the metamaterials for encoding the information and other components of the probe. In material testing, this work will allow better characterization of damage precursor in advanced materials, such as composite structures (micro-cracks, voids, micro-buckling, local fiber breakage, or local fiber-matrix debonding). In medical diagnosis, this work will contribute to answer an urgent need for fast imaging frame rates and better resolution in both near- and far-field to avoid the risks in the surrounding organs in guided procedures, in addition to extended penetration depth in order to adapt to the increasing proportion of the obese population.
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Compressive sensing-based sparse transducers for ultrasound imaging
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批准号:RGPIN-2020-07053
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$2.84万
-
财政年份:2022
-
负责人:Masson, Patrice
-
依托单位:
Compressive sensing-based sparse transducers for ultrasound imaging
-
批准号:RGPIN-2020-07053
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$2.84万
-
财政年份:2021
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负责人:Masson, Patrice
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依托单位:
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Surface tactile par réflexion d'ondes ultrasonores
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