4.7 Article

Superiorized Photo-Acoustic Non-NEgative Reconstruction (SPANNER) for Clinical Photoacoustic Imaging

期刊

IEEE TRANSACTIONS ON MEDICAL IMAGING
卷 40, 期 7, 页码 1888-1897

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2021.3068181

关键词

Imaging; Image reconstruction; Acoustics; Radiology; Radio frequency; Optical imaging; Image resolution; Optoacoustic; photoacoustic imaging; prostate; image reconstruction; iterative methods; molecular and cellular imaging

资金

  1. Philips Healthcare
  2. Sir Peter Michael Foundation
  3. National Research Foundation of Korea (NRF) [NRF-2019R1A2C2006269, NRF-2020R1A6A1A03047902]
  4. National Research Foundation of Korea [4199990114297] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

The SPANNER algorithm is a new robust algorithm for photoacoustic imaging that can reconstruct images in real-time and address artifacts associated with limited viewing angles and imaging depth. Comparisons with other reconstruction algorithms and experiments on tissue samples and prostate cancer patients demonstrate SPANNER's ability to improve contrast to background ratio and axial resolution, as well as accurately quantify PA signals from contrast agents.
Photoacoustic (PA) imaging can revolutionize medical ultrasound by augmenting it with molecular information. However, clinical translation of PA imaging remains a challenge due to the limited viewing angles and imaging depth. Described here is a new robust algorithm called Superiorized Photo-Acoustic Non-NEgative Reconstruction (SPANNER), designed to reconstruct PA images in real-time and to address the artifacts associated with limited viewing angles and imaging depth. The method utilizes precise forward modeling of the PA propagation and reception of signals while accounting for the effects of acoustic absorption, element size, shape, and sensitivity, as well as the transducer's impulse response and directivity pattern. A fast superiorized conjugate gradient algorithm is used for inversion. SPANNER is compared to three reconstruction algorithms: delay-and-sum (DAS), universal back-projection (UBP), and model-based reconstruction (MBR). All four algorithms are applied to both simulations and experimental data acquired from tissue-mimicking phantoms, ex vivo tissue samples, and in vivo imaging of the prostates in patients. Simulations and phantom experiments highlight the ability of SPANNER to improve contrast to background ratio by up to 20 dB compared to all other algorithms, as well as a 3-fold increase in axial resolution compared to DAS and UBP. Applying SPANNER on contrast-enhanced PA images acquired from prostate cancer patients yielded a statistically significant difference before and after contrast agent administration, while the other three image reconstruction methods did not, thus highlighting SPANNER's performance in differentiating intrinsic from extrinsic PA signals and its ability to quantify PA signals from the contrast agent more accurately.

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