Laser speckle contrast imaging with principal component and entropy analysis: a novel approach for depth-independent blood flow assessment.

Current study presents an advanced method for improving the visualization of subsurface blood vessels using laser speckle contrast imaging (LSCI), enhanced through principal component analysis (PCA) filtering. By combining LSCI and laser speckle entropy imaging with PCA filtering, the method effectively separates static and dynamic components of the speckle signal, significantly improving the accuracy of blood flow assessments, even in the presence of static scattering layers located above and below the vessel. Experiments conducted on optical phantoms, with the vessel depths ranging from 0.

Optical Clearing of Ex Vivo Adipose Tissue.

Objectives: The paper focuses on the development of technology of adipose tissue optical clearing using different complex hyperosmotic optical clearing agents and tissue permeability enhancers.

Methods: To quantify optical clearing efficiency, reduced scattering coefficient was estimated from the ex vivo spatially resolved backreflectance measurements using a multi-distant fiber optical device. Tissue morphology modification was monitored with the help of histological studies.

Optical parameters of healthy and tumor breast tissues in mice.

Knowledge of the optical parameters of tumors is important for choosing the correct laser treatment parameters. In this paper, optical properties and refraction indices of breast tissue in healthy mice and a 4T1 model mimicking human breast cancer have been measured. A significant decrease in both the scattering and refractive index of tumor tissue has been observed.

Multimodal Method for Differentiating Various Clinical Forms of Basal Cell Carcinoma and Benign Neoplasms In Vivo.

Correct classification of skin lesions is a key step in skin cancer screening, which requires high accuracy and interpretability. This paper proposes a multimodal method for differentiating various clinical forms of basal cell carcinoma and benign neoplasms that includes machine learning. This study was conducted on 37 neoplasms, including benign neoplasms and five different clinical forms of basal cell carcinoma.