Application of transfer learning for rapid calibration of spatially resolved diffuse reflectance probes for extraction of tissue optical properties.

ABSTRACT:

Significance

Treatment planning for light-based therapies including photodynamic therapy requires tissue optical property knowledge. This is recoverable with spatially resolved diffuse reflectance spectroscopy (DRS) but requires precise source-detector separation (SDS) determination and time-consuming simulations.

Aim

An artificial neural network (ANN) to map from DRS at multiple SDS to optical properties was created. This trained ANN was adapted to fiber-optic probes with varying SDS using transfer learning (TL).

Approach

An ANN mapping from measurements to Monte Carlo simulation to optical properties was created with one fiber-optic probe. A second probe with different SDS was used for TL algorithm creation. Data from a third were used to test this algorithm.

Res

SUBMITTER: Hannan MN 

PROVIDER: S-EPMC10901350 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature