Exploring the role of sample thickness for hyperspectral microscopy tissue discrimination through Monte Carlo simulations

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Quintana-quintana, Laura, Witteveen, Mark, Dashtbozorg, Behdad, Ortega, Samuel, Ruers, Theo J. m., Sterenborg, Henricus J. c. m., Callico, Gustavo M.
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866911081695281152
author Quintana-quintana, Laura
Witteveen, Mark
Dashtbozorg, Behdad
Ortega, Samuel
Ruers, Theo J. m.
Sterenborg, Henricus J. c. m.
Callico, Gustavo M.
author_facet Quintana-quintana, Laura
Witteveen, Mark
Dashtbozorg, Behdad
Ortega, Samuel
Ruers, Theo J. m.
Sterenborg, Henricus J. c. m.
Callico, Gustavo M.
contents Recent advancements in multispectral (MS) and hyperspectral (HS) microscopy have focused on sensor and system improvements, yet sample processing remains overlooked. We conducted an analysis of the literature, revealing that 40 percent of studies do not report sample thickness. Among those that did report it, the vast majority, 98 percent, used 2 to 10 micrometer samples. This study investigates the impact of unstained sample thickness on MS/HS image quality through light transport simulations. Monte Carlo simulations were conducted on various tissue types (i.e., breast, colorectal, liver, and lung). The simulations revealed that thin samples reduce tissue differentiation, while higher thicknesses (approximately 500 micrometers) improve discrimination, though at the cost of reduced light intensity. These findings highlight the need to study and optimize sample thickness for enhanced tissue characterization and diagnostic accuracy in MS/HS microscopy.
format Preprint
id arxiv_https___arxiv_org_abs_2507_21675
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Exploring the role of sample thickness for hyperspectral microscopy tissue discrimination through Monte Carlo simulations
Quintana-quintana, Laura
Witteveen, Mark
Dashtbozorg, Behdad
Ortega, Samuel
Ruers, Theo J. m.
Sterenborg, Henricus J. c. m.
Callico, Gustavo M.
Optics
Biological Physics
Recent advancements in multispectral (MS) and hyperspectral (HS) microscopy have focused on sensor and system improvements, yet sample processing remains overlooked. We conducted an analysis of the literature, revealing that 40 percent of studies do not report sample thickness. Among those that did report it, the vast majority, 98 percent, used 2 to 10 micrometer samples. This study investigates the impact of unstained sample thickness on MS/HS image quality through light transport simulations. Monte Carlo simulations were conducted on various tissue types (i.e., breast, colorectal, liver, and lung). The simulations revealed that thin samples reduce tissue differentiation, while higher thicknesses (approximately 500 micrometers) improve discrimination, though at the cost of reduced light intensity. These findings highlight the need to study and optimize sample thickness for enhanced tissue characterization and diagnostic accuracy in MS/HS microscopy.
title Exploring the role of sample thickness for hyperspectral microscopy tissue discrimination through Monte Carlo simulations
topic Optics
Biological Physics
url https://arxiv.org/abs/2507.21675