Podoplanin, lymphatic vessel endothelial hyaluronic acid receptor-1, prospero-related homeobox-1 and vascular endothelial growth factor receptor 3 have been demonstrated to have crucial roles in the development of the lymphatic system and lymphangiogenesis process by combining with their corresponding receptors. Thus, the four markers have been widely used in labelling lymphatic vessels for the...

Characterization of blood vessel elastic properties can help in detecting thrombosis and preventing life-threatening conditions such as acute myocardial infarction or stroke. Vascular elastic photoacoustic tomography (VE-PAT) is proposed to measure blood vessel compliance in humans. Implemented on a linear-array-based photoacoustic computed tomography system, VE-PAT can quantify blood vessel co...

Vision impairment due to pathological damage of the retina can largely be prevented through periodic screening using fundus color imaging. However the challenge with large scale screening is the inability to exhaustively detect fine blood vessels crucial to disease diagnosis. In this work we present a computational imaging framework using deep and ensemble learning for reliable detection of blo...

BACKGROUND Robust reconstructions of the three-dimensional network of blood vessels in developing embryos imaged by optical coherence tomography (OCT) are needed for quantifying the longitudinal development of vascular networks in live mammalian embryos, in support of developmental cardiovascular research. Past computational methods [such as speckle variance (SV)] have demonstrated the feasibil...

Accurate detection and quantification of coronary artery stenoses is fundamental in correct patient diagnosis and optimal treatment planning. Central to detection and quantification is the correct estimation of lumen in the coronary vessel. Here, we describe a method for accurate lumen segmentation in CTA and present results of an early prototype for stenosis detection and quantification for a ...

This system proposes a new supervised approach for the blood vessel segmentation method in retina image. This proposed system overcomes the problem of segmenting thin vessels. This method uses a Fuzzy Neural Network (FNN) scheme for pixel classification and computes a 7-D vector composed of gray-level, moment invariants-based features for pixel representation and AM-FM method for composition of...

Blood vessel extraction is an important step for abnormality detection and for obtaining good retinopathy diabetic diagnosis in digital retinal images. The use of filter bank has shown to be a powerful technique for detecting blood vessels. In particular, the Matched Filter is appropriate and efficient for this task and in combination with other methods the blood vessel detection can be improve...