Image Enhancement based
Improved Multi-scale Hessian Matrix for Coronary Angiography
The coronary angiography image is easy to be
affected by many factors, such as vascular thickness varied huge, complex
background noise, uneven illumination intensity and so on. Many vascular image
enhancement methods are propose, such as linear filters , morphology filter, anisotropic diffusion filter and so on. The
most common method is vascular enhancement filter based on Hessian matrix
introduced in paper.
Multi-scale fusion in the multi-scale vessel
enhancement filter is used to solve the vascular characteristics that the size
of blood vessel images is different. Multi-scale Hessian matrix method is mentioned
through combining Hessian matrix method with other image enhancement methods.
In
this paper, a method of image de-noising and enhancement based on the improved
multi-scale Hessian matrix that integrate the multi-scale Hessian matrix with
morphological top-hat method for coronary angiography images is proposed.
MORPHOLOGICAL TOP-HAT
OPERATIONS
Morphological
opening operation can be used to smooth the outline of objects, disconnect
narrow neck, eliminate thin projections etc
The
highlights can be removed by the morphological opening operation, because the
area of highlights smaller than the structure element. Background
image obtained by the opening operation is subtracted from the original image,
the acquired vascular tree have got image enhancement, the process is known as
top-hat operation.
MULTI-SCALE HESSIAN
MATRIX VESSEL EXTRACTION
Hessian
matrix, resulting in a lot of background noise (aperture etc.), and many small
tiny blood vessels disappeared at the same time. To be able to solve these
problems, an improved method combining multi-scale Hessian matrix with
morphological top-hat operation is proposed in this paper.
An
improved multi-scale Hessian matrix, combined with morphological top-hat
operation for the detection of coronary angiography is presented in the paper.
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