Abstract
The accurate detection of vascular bifurcations is not helpful for pulmonary vascular disease diagnosis, but vital in (Computed Tomography) CT image analysis and processing of lung. We propose a tensor voting based method for vascular bifurcation detection in CT image of lung, which a vessel enhancement method is firstly proceeding to initially extract vessel structure, on which we perform ball voting with the pixels.
Highlights
During pulmonary image analysis or clinical diagnosis and treatment, it is necessary to extract plenty of feature points as land-markers to compare body structure images obtained at different time in order to identify the disease
It is applied to many medical fields as following: feature points can be an indicator of a separate vessel so that it is easy for doctors to track a specific vessel they need to observe during diagnosis of disease; feature point can identify a certain location as land-marker used for registration of multiple images so that they would be mapped to the same coordinate space; feature point has so good robustness to be used for object recognition
We propose a tensor voting based method for vascular bifurcation detection in CT image of lung
Summary
During pulmonary image analysis or clinical diagnosis and treatment, it is necessary to extract plenty of feature points as land-markers to compare body structure images obtained at different time in order to identify the disease. Feature point is so vital that it can be the cornerstone of such image technologies as image registration, image matching, object recognition, motion detection and image stitching. It is applied to many medical fields as following: feature points can be an indicator of a separate vessel so that it is easy for doctors to track a specific vessel they need to observe during diagnosis of disease; feature point can identify a certain location as land-marker used for registration of multiple images so that they would be mapped to the same coordinate space; feature point has so good robustness to be used for object recognition. Feature point detection is favorable to diagnose disease and a great important step for image subsequent processing
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