An automated 3D registration method for optical coherence tomography volumes

Area of Science:

• Biomedical Imaging
• Optical Engineering

Background:

• Optical coherence tomography (OCT) provides high-resolution 3D data for biological tissues.
• Limited field of view (FOV) in OCT restricts its clinical applications.

Purpose of the Study:

• To develop a novel method for registering and stitching overlapped volumetric OCT data.
• To overcome the FOV limitation of OCT for enhanced biological sample visualization.

Main Methods:

• Proposed a novel algorithm to register multiple overlapped volumetric OCT data.
• Utilized Scale Invariant Feature Transform (SIFT) for keypoint extraction on en face planes.
• Estimated relative positions using keypoint matching, linear modeling, and least squares.
• Calibrated depth displacement and aligned z-coordinates globally.

Main Results:

• Successfully stitched multiple volumetric OCT datasets of human cervix and swine heart tissues.
• Demonstrated enhanced visualization of biological samples over a wider FOV.
• Improved investigation of tissue structures, such as fiber orientation.

Conclusions:

• The developed method effectively stitches volumetric OCT data to expand FOV.
• This technique enhances the clinical applicability of OCT for detailed tissue analysis.