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Optica, Biomedical Optics Express, 5(11), p. 2679, 2020

DOI: 10.1364/boe.389373

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Lymphatic vessel segmentation in optical coherence tomography by adding U-Net-based CNN for artifact minimization

Journal article published in 2020 by Pei-Yu Lai, Chung-Hsing Chang, Hong-Ren Su, Wen-Chuan Kuo
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

The lymphatic system branches throughout the body to transport bodily fluid and plays a key immune-response role. Optical coherence tomography (OCT) is an emerging technique for the noninvasive and label-free imaging of lymphatic capillaries utilizing low scattering features of the lymph fluid. Here, the proposed lymphatic segmentation method combines U-Net-based CNN, a Hessian vesselness filter, and a modified intensity-thresholding to search the nearby pixels based on the binarized Hessian mask. Compared to previous approaches, the method can extract shapes more precisely, and the segmented result contains minimal artifacts, achieves the dice coefficient of 0.83, precision of 0.859, and recall of 0.803.