Lumen segmentation from clinical intravascular optical coherence tomography (IV-OCT) images has clinical relevance as it provides a full three-dimensional perspective of diseased coronary artery sections. Inaccurate segmentation may occur when there are artifacts in the image, resulting from issues such as inadequate blood clearance. This study proposes a transmittance-based lumen intensity enhancement method that ensures only lumen regions are highlighted. A level-set-based active contour method that utilizes the local speckle distribution properties of the image is then employed to drive an image-specific active contour toward the true lumen boundaries. By utilizing local speckle properties, the intensity variation issues within the image are resolved. This combined approach has been successfully applied to challenging clinical IV-OCT datasets that contains multiple lumens, residual blood flow, and its shadowing artifact. A method to identify the guide-wire and interpolate the lost lumen segments has been implemented. This approach is fast and can be performed even when guide-wire boundaries are not easily identified. Lumen enhancement also makes it easy to identify vessel side branches. This automated approach is not only able to extract the arterial lumen, but also the smaller microvascular lumens that are associated with the vasa vasorum and with atherosclerotic plaque.
Cross-correlation of Intravascular Optical Coherence Tomography (IV-OCT) images is affected by image distortion due to the non-uniform rotational velocity of the imaging catheter. It results in non-representative cross-correlation maps such that for a static scan, the coefficients fluctuate from high to low correlation values. The variation in cross-correlation at flow locations is muted, in comparison to stationary regions. In the present study, the variation of correlation values and its standard deviation (SD) is used to suppress the distortion related noise effects and to extract flow maps from static scan images. The standard deviation of the cross-correlation variation can distinguish flow locations from the surrounding tissue region. The advantage of this technique is its ability to identify slow flow, even Brownian flow, in the presence of motion artifacts. The SD mask used for generating flow maps, is optimized using tissue mimicking phantoms. Finally, the ability of this technique to suppress noise and capture flow maps is demonstrated by imaging microflow through excised porcine coronary artery wall and mucosa membrane imaging.
This paper describes a temporal carrier based Heterodyne Interferometer and associated phase demodulation
techniques which are suitable for phase imaging of live cells. A Mach-Zehnder Interferometer is integrated to the
microscope and two acousto-optic modulators are employed, to generate a temporal carrier that allows heterodyne
approach to phase demodulation. Two demodulation schemes are presented: (a) Digital heterodyne phase extraction
technique to extract the static phase information of the carrier signal, and (b) dynamic phase extraction technique for
extracting phase variation in the carrier signal. The Heterodyne interferometer enables fast phase imaging and
coupled with digital heterodyne phase extraction process, the system provides excellent temporal phase stability
(standard deviation < 2 nm for 16 second measurement). This technique is employed for quantitative phase imaging
of 3T3 fibroblast cells immersed in cell media. When there is phase variation, the temporal carrier signal is
modulated and its instantaneous frequency is directly related to the variation. The dynamic phase extraction
technique first determines the instantaneous frequency, which is then integrated with respect to time to obtain timevarying
phase. The algorithm is able to extract a time varying phase, caused by a stimulated vibration at 30 Hz and
40 nm amplitude.
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