02-05-2017, 10:28 PM
Pls send matlab code blood vessel matched filter
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matlab code blood vessel matched filter
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Pls send matlab code blood vessel matched filter
03-05-2017, 12:49 PM
The adapted filter has been widely used in the detection of blood vessels of the digital image of human retina. The response of the filter adapted to the detection of blood vessels is increased by proposing better filter parameters. These filter parameters are found using an optimization procedure on 20 retina images from the DRIVE database. Comparisons with other approaches show that the matched filter using the newly found parameters outperforms the matched filter using the classic filter parameters as well as some vessel detection techniques. Also discussed is a technique for finding the best threshold value for the continuous matched filter output image and thus the best segmented container image.
One of the earliest and reasonably effective proposals for segmentation of blood vessels in retinal images is the use of adapted filters oriented for the detection of long linear structures.
Blood vessels often have a gaussian cross-section (see Fig. 11.3) which is quite consistent along the segments of the vessels. As long as the vessels are not too tortuous, they may be approximated as elongated cylinders of Gaussian cross-section between the branching points of the vessel. Therefore, the two-dimensional model consisting of an elongated cylinder of Gaussian cross-section must be well correlated with a container segment provided they have the same orientation. The model moves to each possible position in the image and the correlation of the local image patch with the model is calculated to form a correlation image. Peaks in the correlation image occur at the locations of blood vessels.
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