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.
Highlights
The lymphatic system maintains tissue fluid and plays an essential role in immune cell trafficking and surveillance [1,2]
The results demonstrate that the trained model can generalize well in images captured in a different area of mouse ear
Representative Optical coherence tomography (OCT) cross-sectional images of wild type mice (WT) and BRAF V600E/V600E;Pten −/− mice ear are shown in Fig. 5(A) and (B) where magenta line represents human-annotated result
Summary
The lymphatic system maintains tissue fluid and plays an essential role in immune cell trafficking and surveillance [1,2]. Non-invasive visualization techniques currently used in clinics include computed tomography (CT), positron emission tomography (PET), magnetic resonance imaging (MRI), and near-infrared (NIR) fluorescence imaging [3,4]. Each of these techniques, has certain limitations, such as poor spatial resolution, ionizing contrast agent or tracer dye have to be used, and possible phototoxicity effect. OCT has the capability of imaging the lymphatic capillaries without contrast agent. It has a competitive edge over other techniques like PET, CT, and MRI in observation of tumor microenvironment. Lymphatic vessels appear as low scattering areas in OCT are owing to the transparency of the lymph fluid
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