Enhancing laser speckle contrast imaging based on adaptive scale and directional kernel during V-PDT

Ren, Chenfei; Chen, Tianlong; Cao, Mengyu; Shen, Yi; Li, Buhong

doi:10.1117/12.2683138

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…This phenomenon is referred to as a speckle pattern [137]. LSCI has been employed extensively due to its advantages of high speed, wide field of view, and ease of implementation, with a particular focus on the visualization of blood flow and vascular damage during V-PDT [138]. The method was employed to visualize microcirculation and to monitor microcirculatory alterations in port wine stains (PWSs) during V-PDT, which involved the intravenous administration of photocarcinorin (4-5 mg/kg).…”

Section: Discussionmentioning

confidence: 99%

Devices and Methods for Dosimetry of Personalized Photodynamic Therapy of Tumors: A Review on Recent Trends

Alekseeva,

Makarov,

Efendiev

et al. 2024

Cancers

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Significance: Despite the widespread use of photodynamic therapy in clinical practice, there is a lack of personalized methods for assessing the sufficiency of photodynamic exposure on tumors, depending on tissue parameters that change during light irradiation. This can lead to different treatment results. Aim: The objective of this article was to conduct a comprehensive review of devices and methods employed for the implicit dosimetric monitoring of personalized photodynamic therapy for tumors. Methods: The review included 88 peer-reviewed research articles published between January 2010 and April 2024 that employed implicit monitoring methods, such as fluorescence imaging and diffuse reflectance spectroscopy. Additionally, it encompassed computer modeling methods that are most often and successfully used in preclinical and clinical practice to predict treatment outcomes. The Internet search engine Google Scholar and the Scopus database were used to search the literature for relevant articles. Results: The review analyzed and compared the results of 88 peer-reviewed research articles presenting various methods of implicit dosimetry during photodynamic therapy. The most prominent wavelengths for PDT are in the visible and near-infrared spectral range such as 405, 630, 660, and 690 nm. Conclusions: The problem of developing an accurate, reliable, and easily implemented dosimetry method for photodynamic therapy remains a current problem, since determining the effective light dose for a specific tumor is a decisive factor in achieving a positive treatment outcome.

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Section: Discussionmentioning

confidence: 99%

Devices and Methods for Dosimetry of Personalized Photodynamic Therapy of Tumors: A Review on Recent Trends

Alekseeva,

Makarov,

Efendiev

et al. 2024

Cancers

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“…The adaptive processing of the RSI is one of the most studied approaches to deal with the problem of loss of spatial resolution in the CI besides noise reduction by adding invasive agents to the bloodstream [32][33][34][35][36], or through filtering [37,38]. Adaptive methods aim to select suitable analysis windows for the morphology of the blood vessels in the image, obtaining a more representative and larger sample to compute the statistics [39][40][41][42][43]. Although adaptive methods have improved the quality of CIs, it is necessary to improve the pixel selection process.…”

Section: Introductionmentioning

confidence: 99%

Improving Blood Vessel Segmentation and Depth Estimation in Laser Speckle Images Using Deep Learning

Morales-Vargas,

Peregrina-Barreto,

Fuentes-Aguilar

et al. 2024

Information

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Microvasculature analysis is an important task in the medical field due to its various applications. It has been used for the diagnosis and threat of diseases in fields such as ophthalmology, dermatology, and neurology by measuring relative blood flow or blood vessel morphological properties. However, light scattering at the periphery of the blood vessel causes a decrease in contrast around the vessel borders and an increase in the noise of the image, making the localization of blood vessels a challenging task. Therefore, this work proposes integrating known information from the experimental setup into a deep learning architecture with multiple inputs to improve the generalization of a computational model for the segmentation of blood vessels and depth estimation in a single inference step. The proposed R-UNET + ET + LA obtained an intersection over union of 0.944 ± 0.065 and 0.812 ± 0.080 in the classification task for validation (in vitro) and test sets (in vivo), respectively, and a root mean squared error of 0.0085 ± 0.0275 μm in the depth estimation. This approach improves the generalization of current solutions by pre-training with in vitro data and adding information from the experimental setup. Additionally, the method can infer the depth of a blood vessel pixel by pixel instead of in regions as the current state of the art does.

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Enhancing laser speckle contrast imaging based on adaptive scale and directional kernel during V-PDT

Cited by 2 publications

References 19 publications

Devices and Methods for Dosimetry of Personalized Photodynamic Therapy of Tumors: A Review on Recent Trends

Devices and Methods for Dosimetry of Personalized Photodynamic Therapy of Tumors: A Review on Recent Trends

Improving Blood Vessel Segmentation and Depth Estimation in Laser Speckle Images Using Deep Learning

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