Image Quality Improvement Techniques and Assessment Adequacy in Clinical Optoacoustic Imaging: A Systematic Review.
Image Quality Improvement Techniques and Assessment Adequacy in Clinical Optoacoustic Imaging: A Systematic Review.
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DOI:
10.3390/bios12100901
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发表时间:
2022-10-20
期刊:
影响因子:
5.4
通讯作者:
Hadjileontiadis, Leontios
中科院分区:
文献类型:
--
作者:
Dimaridis, Ioannis;Sridharan, Patmaa;Ntziachristos, Vasilis;Karlas, Angelos;Hadjileontiadis, Leontios
Optoacoustic imaging relies on the detection of optically induced acoustic waves to offer new possibilities in morphological and functional imaging. As the modality matures towards clinical application, research efforts aim to address multifactorial limitations that negatively impact the resulting image quality. In an endeavor to obtain a clear view on the limitations and their effects, as well as the status of this progressive refinement process, we conduct an extensive search for optoacoustic image quality improvement approaches that have been evaluated with humans in vivo, thus focusing on clinically relevant outcomes. We query six databases (PubMed, Scopus, Web of Science, IEEE Xplore, ACM Digital Library, and Google Scholar) for articles published from 1 January 2010 to 31 October 2021, and identify 45 relevant research works through a systematic screening process. We review the identified approaches, describing their primary objectives, targeted limitations, and key technical implementation details. Moreover, considering comprehensive and objective quality assessment as an essential prerequisite for the adoption of such approaches in clinical practice, we subject 36 of the 45 papers to a further in-depth analysis of the reported quality evaluation procedures, and elicit a set of criteria with the intent to capture key evaluation aspects. Through a comparative criteria-wise rating process, we seek research efforts that exhibit excellence in quality assessment of their proposed methods, and discuss features that distinguish them from works with similar objectives. Additionally, informed by the rating results, we highlight areas with improvement potential, and extract recommendations for designing quality assessment pipelines capable of providing rich evidence.
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