Work

Towards real-time diffuse optical tomography with a handheld scanning probe

Year: 2025

Type: article

Abstract: Diffuse optical tomography (DOT) performed using deep-learning allows high-speed reconstruction of tissue optical properties and could thereby enable image-guided scanning, e.g., to enhance clinical breast imaging. Previously published models are geometry-specific and, therefore, require extensive data generation and training for each use case, restricting the scanning protocol at the point of use. A transformer-based architecture is proposed to overcome these obstacles that encode spatially unstructured DOT measurements, enabling a single trained model to handle arbitrary scanning pathways and measurement density. The model is demonstrated with breast tissue-emulating simulated and phantom data, yielding - for 24 mm-deep absorptions ( μ a ) and reduced scattering ( μ s ′) images, respectively - average RMSEs of 0.0095±0.0023 cm −1 and 1.95±0.78 cm −1 , Sørensen-Dice coefficients of 0.55±0.12 and 0.67±0.1, and anomaly contrast of 79±10% and 93.3±4.6% of the ground-truth contrast, with an effective imaging speed of 14 Hz. The average absolute μ a and μ s ′ values of homogeneous simulated examples were within 10% of the true values.

Source: Biomedical Optics Express

DOI: 10.1364/boe.549880

Authors: Robin Dale, Nicholas Ross, Scott Howard, Thomas D. O’Sullivan, Hamid Dehghani

Institutions: University of Birmingham, University of Notre Dame

Language: English

Topic: Optical Imaging and Spectroscopy Techniques

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,913