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An automated method for segmentation and quantification of blood vessels in histology images.

Abstract：

:Alzheimer's disease (AD) is a chronic neuro-degenerative disease that adversely affect many people on a global scale. Despite different diagnostic and therapeutic treatment, there is no cure for AD. The brain is one of the most complex organ and researchers are still trying to understand so as to find a cure. OBJECTIVE:To complement the efforts of clinical researchers engaged in research in alzheimer's disease, accurate segmentation and quantification of blood vessels in brain images is required. METHOD:For robust segmentation of blood vessels even in the presence of colour variation, we introduce a fully automated morphological tool that can extract and quantify vessels from haematoxylin and diaminobenzidine stained histology brain image. The method, exploits saturation channel of stained image slides, ISODATA threshold method is applied to obtain a binary image. This helps in eliminating background and remaining with only blood vessels. A one-stage procedure that includes eliminating small artefacts is performed on the binary mask. The intensity of the image is transformed. Joining is performed to deal with fragmentation of intact blood vessels on the images, and artefactual appearance of the blood vessel structures. The artefactual fragments based on measured incoherence with neighbouring tissue are removed. The vessels are then labelled to facilitate quantification. Morphometric measurements are used during the vessel quantification assess both vessels with lumen and vessels without lumen. We have quantified the diameter of blood vessels. RESULTS:The image processing technique is developed in close collaboration with neuroscientist experts to help clinician. We have evaluated our proposed approach qualitatively. The method was validated against their manual quantification results. Qualitative results show that the method can indeed segment the blood vessels in the presence of colour variations and artefacts. The quantitative method produces fairly better results.

journal_name

Microvasc Res

journal_title

Microvascular research

authors

Bukenya F,Nerissa C,Serres S,Pardon MC,Bai L

doi

10.1016/j.mvr.2019.103928

subject

Has Abstract

pub_date

2020-03-01 00:00:00

pages

103928

eissn

0026-2862

issn

1095-9319

pii

S0026-2862(18)30126-2

journal_volume

128

pub_type

杂志文章

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An automated method for segmentation and quantification of blood vessels in histology images.