ArticleBioengineering (Basel, Switzerland)2024
Monte Carlo-Based Optical Simulation of Optical Distribution in Deep Brain Tissues Using Sixteen Optical Sources.
Article in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Water-sensitive photoacoustic temperature characterization at 960 nm in cerebral vascular phantoms with CT co-registration.Photoacoustics · 2026Article
- Monte Carlo-Based Optimization of Multi-Source Illumination for Photoacoustic Signal Generation in Human Gray-Matter Vessels.Journal of biophotonics · 2026Article
- Light transport in the human spine for optical bone density assessment: Monte Carlo modeling and validation.Biomedical optics express · 2025Article
- Monte Carlo Simulations in Nanomedicine: Advancing Cancer Imaging and Therapy.Nanomaterials (Basel, Switzerland) · 2025Review
- Skull Impact on Photoacoustic Imaging of Multi-Layered Brain Tissues with Embedded Blood Vessel Under Different Optical Source Types: Modeling and Simulation.Bioengineering (Basel, Switzerland) · 2025Article
- Optical Transmission in Single-Layer Brain Tissues under Different Optical Source Types: Modelling and Simulation.Bioengineering (Basel, Switzerland) · 2024Article
- Enhancing photoacoustic imaging for lung diagnostics and BCI communication: simulation of cavity structures artifact generation and evaluation of noise reduction techniques.Frontiers in bioengineering and biotechnology · 2024Article
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Authors and funding
7 authors.
Funding
Abstract
Optical-based imaging has improved from early single-location research to further sophisticated imaging in 2D topography and 3D tomography. These techniques have the benefit of high specificity and non-radiative safety for brain detection and therapy. However, their performance is limited by complex tissue structures. To overcome the difficulty in successful brain imaging applications, we conducted a simulation using 16 optical source types within a brain model that is based on the Monte Carlo method. In addition, we propose an evaluation method of the optical propagating depth and resolution, specifically one based on the optical distribution for brain applications. Based on the results, the best optical source types were determined in each layer. The maximum propagating depth and corresponding source were extracted. The optical source propagating field width was acquired in different depths. The maximum and minimum widths, as well as the corresponding source, were determined. This paper provides a reference for evaluating the optical propagating depth and resolution from an optical simulation aspect, and it has the potential to optimize the performance of optical-based techniques.
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Registered trials
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