Rapid scanning wide-field clutter elimination in epi-optoacoustic imaging using comb LOVIT

Petrosyan, Tigran; Theodorou, Maria; Bamber, Jeffrey C.; Frenz, Martin; Jaeger, Michael

doi:10.1016/j.pacs.2018.02.001

Cited by 9 publications

(7 citation statements)

References 56 publications

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“…This limits the real-time capability and has safety challenges. Recently, LOVIT has been further improved by using multiple foci [19]. Another method exploits the acoustic tissue information by inversion of a linear scatter model using plane wave US measurements [16].…”

Section: Introductionmentioning

confidence: 99%

Reflection artifact identification in photoacoustic imaging using multi-wavelength excitation

Nguyen

Hussain

Steenbergen

2018

Biomed. Opt. Express

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Photoacoustic imaging has been a focus of research for clinical applications owing to its ability for deep visualization with optical absorption contrast. However, there are various technical challenges remaining for this technique to find its place in clinics. One of the challenges is the occurrence of reflection artifacts. The reflection artifacts may lead to image misinterpretation. Here we propose a new method using multiple wavelengths for identifying and removing the reflection artifacts. By imaging the sample with multiple wavelengths, the spectral response of the features in the photoacoustic image is obtained. We assume that the spectral response of the reflection artifact is better correlated with the proper image feature of its corresponding absorber than with other features in the image. Based on this, the reflection artifacts can be identified and removed. Here, we experimentally demonstrated the potential of this method for real-time identification and correction of reflection artifacts in photoacoustic images in phantoms as well as in vivo using a handheld photoacoustic imaging probe.

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Section: Introductionmentioning

confidence: 99%

Reflection artifact identification in photoacoustic imaging using multi-wavelength excitation

Nguyen

Hussain

Steenbergen

2018

Biomed. Opt. Express

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“…Furthermore, reflection artefacts can occur that may be mistaken for real vessel structures. While some studies have attempted to identify and remove reflection artefacts, approaches are elaborate, using additional ultrasound measurements 37,40 , tissue deformations 16 , localized vibrations using acoustic radiation force impulses 19,38 , multi-wavelength illumination 17 , or training of convolutional neural networks 41 . Nonetheless, the full range of photoacoustic mesoscopy artefacts cannot yet be automatically detected or corrected and as such, understanding the resulting limitations on the acquired data is of utmost importance to prevent misinterpretation.…”

Section: Photoacoustic Mesoscopy Shows Greater Variation During In Vi...mentioning

confidence: 99%

“…Moreover, the non-isotropic illumination from the sides of the ultrasound detector array results in inefficient light delivery to the region of interest 15 , thereby leading to limited penetration depth, particularly in specimens that exhibit high absorption. Finally, the limited view can cause in-plane or out-of-plane artefacts, reducing the clarity of the images [16][17][18][19] . In addition to these technical limitations impacting accuracy, precision-related variations in image data arise from temporal, positioning, or operator-dependent factors.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of mesoscopic photoacoustic imaging

Hacker

Brown

Lefebvre

et al. 2022

Preprint

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Photoacoustic mesoscopy visualises vascular architecture and associated tissue structures at high resolution at up to 3 mm depth. The technique has shown promise in both preclinical and clinical imaging studies, with possible applications in oncology and dermatology, however, the accuracy and precision of photoacoustic mesoscopy has not been well established. Here, we present a performance evaluation of a commercial photoacoustic mesoscopy system for imaging vascular structures. Typical artefact types are first highlighted and limitations due to non-isotropic illumination and detection are evaluated with respect to rotation, angularity, and depth of the target. Then, using tailored phantoms and mouse models we demonstrate high system precision, with acceptable coefficients of variation (COV) between repeated scans (short term (1h): COV=1.2%; long term (25 days): COV=9.6%), from target repositioning (without: COV=1.2%, with: COV=4.1%), or from varyingin vivouser experience (experienced: COV=15.9%, unexperienced: COV=20.2%). While our findings support the robustness of the technique, they also underscore the general challenges of limited field-of-view photoacoustic systems in accurately imaging vessel-like structures, thereby guiding users to correctly interpret biologically-relevant information.

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“…A similar approach used a gelatin-cellulose phantom but quantified clutter reduction using target SBR. 84 While not all studies quantified artifact strength or reduction efficacy, most that did compared contrast-based image quality metrics, rather than noise-based metrics.…”

Section: Current Image Quality Evaluation Practices In Photoacoustic Imagingmentioning

confidence: 99%

Review of consensus test methods in medical imaging and current practices in photoacoustic image quality assessment

et al. 2021

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. Significance : Photoacoustic imaging (PAI) is a powerful emerging technology with broad clinical applications, but consensus test methods are needed to standardize performance evaluation and accelerate translation. Aim : To review consensus image quality test methods for mature imaging modalities [ultrasound, magnetic resonance imaging (MRI), x-ray CT, and x-ray mammography], identify best practices in phantom design and testing procedures, and compare against current practices in PAI phantom testing. Approach : We reviewed scientific papers, international standards, clinical accreditation guidelines, and professional society recommendations describing medical image quality test methods. Observations are organized by image quality characteristics (IQCs), including spatial resolution, geometric accuracy, imaging depth, uniformity, sensitivity, low-contrast detectability, and artifacts. Results : Consensus documents typically prescribed phantom geometry and material property requirements, as well as specific data acquisition and analysis protocols to optimize test consistency and reproducibility. While these documents considered a wide array of IQCs, reported PAI phantom testing focused heavily on in-plane resolution, depth of visualization, and sensitivity. Understudied IQCs that merit further consideration include out-of-plane resolution, geometric accuracy, uniformity, low-contrast detectability, and co-registration accuracy. Conclusions : Available medical image quality standards provide a blueprint for establishing consensus best practices for photoacoustic image quality assessment and thus hastening PAI technology advancement, translation, and clinical adoption.

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Rapid scanning wide-field clutter elimination in epi-optoacoustic imaging using comb LOVIT

Cited by 9 publications

References 56 publications

Reflection artifact identification in photoacoustic imaging using multi-wavelength excitation

Reflection artifact identification in photoacoustic imaging using multi-wavelength excitation

Performance evaluation of mesoscopic photoacoustic imaging

Review of consensus test methods in medical imaging and current practices in photoacoustic image quality assessment

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