Abstract
Lumen segmentation in intravascular optical coherence tomography (IVOCT) images is a fundamental work for more advanced plaque analysis, stent recognition, fractional flow reserve (FFR) assessment, and so on. However, the catheter, guide-wire, inadequate blood clearance, and other factors will impact on the accuracy of lumen segmentation. We present a simple and effective method for automatic lumen segmentation method in IVOCT based on morphological features. We use image enhancement, median filtering, image binarization, and morphological closing operation to reduce speckle noise, minimize the effect of blood artifacts and fill in small holes inside vascular walls. We extract the orientation and area-size of connected regions as morphological features in images and remove the catheter and guide-wire completely by morphological corrosion operation, small area-size region removal, and orientation morphological feature comparison, and then the contour of the lumen can be discriminated. The evaluation metrics of this method, the Dice index, Hausdorff distance, Jaccard index, and accuracy of 99.32%, 0.06 mm, 99.4%, and 99.66%, respectively, are obtained from comparing with expert annotations on 268 IVOCT images. Compared with the other morphology-based lumen segmentation methods, the presented method can remove the catheter and guide-wire completely, even if the catheter and guide-wire cling to the lumen or the shape of the catheter is irregular. Since only morphological operations are used to complete all processes, the calculation burden is reduced greatly.
Highlights
Intravascular Optical Coherence Tomography (IVOCT) is a catheter-based examination method which uses near-infraredThe associate editor coordinating the review of this manuscript and approving it for publication was Huanqiang Zeng.light to obtain high-resolution imaging of the in vivo vascular wall microstructure [1]–[4]
VALIDATION METHODS AND RESULTS The presented lumen segmentation method is validated through directly comparison to the manual annotations made by one independent expert observer blinded to automated segmentation results
Dice coefficient (DICE) falls in the interval of [0-100%], it represents the similarity between the two segmentations, the higher the DICE, the more close the automatic segmentation to manual segmentation
Summary
Intravascular Optical Coherence Tomography (IVOCT) is a catheter-based examination method which uses near-infrared. It is noteworthy that morphology based methods are widely used in lumen segmentation, since they have many advantages including: 1) They are insensitive to intensity variation in images due to binarization process, so they have a robustness for noise. A wavelet transform is used for an adaptive threshold selection in Otsu binarization [20] These methods remove the catheter by setting pixels in the radial range of the catheter to zero. We present a simple and effective method for automatic lumen segmentation method in IVOCT based on morphological features. Compared with other morphology based lumen segmentation methods, the presented method can remove the catheter and guide-wire completely, even if the catheter and guide-wire cling to the lumen or the shape of catheter is irregular. Since only the morphological operations are used to complete all processes, the calculation burden is reduced greatly
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
