Related Experiment Video
Updated: Jul 10, 2026
11:21
Integrated Photoacoustic Ophthalmoscopy and Spectral-domain Optical Coherence Tomography
Published on: January 15, 2013
Time-gated Fourier-domain optical coherence tomography
Matthew S Muller1, Paul J Webster, James M Fraser
1Department of Physics, Engineering Physics and Astronomy, Queen's University, Kingston, Ontario K7L 3N6, Canada. matt@physics.queensu.ca
Optics Letters
|November 21, 2007
Summary
A new optical coherence tomography (OCT) system uses nonlinear time gating for enhanced imaging. This innovation improves contrast and speed by selecting a specific depth of view, even when detecting visible light from infrared imaging.
Area of Science:
- Biomedical Optics
- Medical Imaging Technology
Background:
- Optical Coherence Tomography (OCT) is a valuable imaging modality.
- Fourier-domain OCT (FD-OCT) offers high resolution and speed.
- Limitations exist in contrast and depth of field control in conventional OCT.
Purpose of the Study:
- To introduce a novel OCT system combining FD-OCT with incoherent nonlinear time gating.
- To demonstrate improved contrast and acquisition speed through depth field selection.
- To present a unique infrared-to-visible spectral conversion capability for OCT imaging.
Main Methods:
- Implementation of a hybrid OCT system integrating Fourier-domain OCT principles.
- Application of incoherent nonlinear time gating for optical domain processing.
- Utilizing backscattered light for depth-of-view selection and spectral conversion.
Main Results:
- The novel system successfully achieved depth field selection, enhancing image contrast.
- Acquisition speed was improved due to the restricted field of view.
- Demonstrated successful imaging in the infrared spectrum (1280 nm) with detection in the visible spectrum (504 nm).
Conclusions:
- The presented OCT system offers enhanced performance through optical domain processing.
- Nonlinear time gating provides a powerful method for controlling depth of view in OCT.
- The infrared-to-visible spectral conversion opens new possibilities for OCT applications.
Related Concept Videos
01:11Continuous -time Fourier Transform
The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
01:10Computed Tomography
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
01:26Discrete-time Fourier transform
The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
One of the notable...
One of the notable...
01:10Fast Fourier Transform
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
The computational efficiency of the FFT becomes...
01:15Discrete Fourier Transform
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
01:18Imaging Biological Samples with Optical Microscopy
Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...