Related Experiment Video
Updated: Mar 5, 2026
08:50
Longitudinal Morphological and Physiological Monitoring of Three-dimensional Tumor Spheroids Using Optical Coherence Tomography
Published on: February 9, 2019
8.3K
Robust and fast characterization of OCT-based optical attenuation using a novel frequency-domain algorithm for brain
Wu Yuan1, Carmen Kut1, Wenxuan Liang1
1Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Scientific Reports
|March 23, 2017
Summary
A new frequency-domain algorithm accurately maps optical attenuation from OCT images for real-time intraoperative brain cancer detection. This method enhances surgical guidance for identifying difficult-to-detect tumors.
Area of Science:
- Biomedical Optics
- Medical Imaging
- Cancer Detection
Background:
- Cancer alters tissue optical properties, making detection challenging.
- Optical Coherence Tomography (OCT) offers quantitative analysis of these changes.
- Intraoperative OCT aids real-time cancer identification, especially for brain tumors lacking clear structural layers.
Purpose of the Study:
- To develop a novel, high-speed frequency-domain (FD) algorithm for OCT attenuation mapping.
- To enable robust and fast characterization of optical attenuation from OCT intensity images.
- To improve intraoperative brain cancer detection and surgical guidance.
Main Methods:
- Implemented a novel frequency-domain (FD) algorithm for OCT attenuation mapping.
- Utilized a 1310 nm swept-source OCT (SS-OCT) system.
- Employed graphics processing unit (GPU)-based CUDA C/C++ for real-time processing.
Main Results:
- The FD algorithm demonstrated robust and accurate optical attenuation mapping.
- Performance was validated against traditional fitting methods using human brain cancer and phantom data.
- The algorithm provides real-time quantitative interpretation of OCT images.
Conclusions:
- The developed FD algorithm significantly enhances OCT-based intraoperative brain cancer detection.
- This method offers a substantial improvement over existing techniques for real-time surgical guidance.
- The algorithm facilitates accurate identification of cancerous tissues during surgery.
