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An improved matched filter for blood vessel detection of digital retinal images. Source: Computers in Biology and Medicine (2007) pp. 262 – 267 Authors: Mohammed Al-Rawi, Munib Qutaishat, and Mohammed Arrar Impact factor: 1.068 (2006) Reporter: Kai Hung Chen Date: Mar 11, 2008. Outline.
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An improved matched filter for blood vessel detection of digital retinal images Source: Computers in Biology and Medicine (2007) pp. 262 – 267 Authors: Mohammed Al-Rawi, Munib Qutaishat, and Mohammed Arrar Impact factor: 1.068 (2006) Reporter: Kai Hung Chen Date: Mar 11, 2008
Outline • Introduction • Proposed method • Experiment results
Introduction • : The green band of a digital retina image • : The profile of a one pixel width at the 200th row of the retina image shown in (a)
ProposedMethod L: the length of the vessel segment that has the same orientation σ: the spread of the intensity profile
ProposedMethod Neighborhood N is defined as: The pointPithat belongs to N is:
ProposedMethod The corresponding weights in the kernel i ( i =1, . . . , 12 which is the number of kernels) are given by: The filter is normalized as:
Quality Factor • True pixels: pixels detected as vessels and they appear as vessels in the hand label image. • False pixels: pixels detected as vessels yet they appear as non-vessels in the hand labeled image. • true_ratio: divide the true pixels by the number of vessel pixels in the hand labeled image. • false_ratio: divide the false pixels by the number of non-vessel pixels in the hand labeled image. • Quality Factor ( QLσT )= true_ratio − false_ratio
ExperimentResults MAA: maximum accuracy average, the average accuracy of all images.
