OCT imaging reconstruction on spectral-domain optical coherence tomography
Project description
PyOCT: Imaging Reconstruction of Spectral-Domain Optical Coherence Tomography
PyOCT is developed to conduct normal spectral-domain optical coherence tomography (SD-OCT) imaging reconstruction with main steps as:
- Reading Data
- Background Subtraction
- Spectral Resampling
- Comutational Aberration Correction (Alpha-correction)
- Camera Dispersion Correction (Beta-correction with camera calibration factors)
- Inverse Fourier Transform
- Obtain OCT Image
The algorithms was developed initially in Prof. Steven G. Adie research lab at Cornell University using MATLAB. The reconstruction speed has been improved with matrix-operation. Compared with MATLAB, Python language have a much better performance in loading data from binary files tested only in our lab computer.
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