An automatic algorithm for the segmentation and morphological analysis of microvessels in immunostained histological tumour sections

Reyes Aldasoro, C C, Williams, L J, Akerman, S, Kanthou, C and Tozer, G M (2011) An automatic algorithm for the segmentation and morphological analysis of microvessels in immunostained histological tumour sections. Journal of Microscopy, 242 (3). pp. 262-278. ISSN 0022-2720

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Abstract

A fully automatic segmentation and morphological analysis algorithm for the analysis of microvessels from CD31 immunostained histological tumour sections is presented. Development of the algorithm exploited the distinctive hues of stained vascular endothelial cells, cell nuclei and background, to provide the seeds for a region-growing method for object segmentation in the 3D hue, saturation, value (HSV) colour model. The segmented objects, identified as microvessels by CD31 immunostaining, were post-processed with three morphological tasks: joining separate objects that were likely to belong to a single vessel, closing objects that had a narrow gap around their periphery, and splitting objects with multiple lumina into individual vessels. The automatic segmentation was validated against a hand-segmented set of 44 images from three different SW1222 human colorectal carcinomas xenografted into mice. 96.3 0.9% of pixels were found to be correctly classified. Automated segmentation was carried out on a further 53 images from three histologically distinct mouse fibrosarcomas (MFs) for morphological comparison with the SW1222 tumours. Four morphometric measurements were calculated for each segmented vessel: vascular area (VA), ratio of lumen area to vascular area (lu/VA), eccentricity (e), and roundness (ro). In addition, the total vascular area relative to tumour tissue area (rVA) was calculated. lu/VA, e and ro were found to be significantly smaller in MF tumours than in SW1222 tumours (p < 0.05; unpaired t-test). The algorithm is available through the website http://www.caiman.org.uk where images can be uploaded, processed and sent back to users. The output from CAIMAN consists of the original image with boundaries of segmented vessels overlaid, the calculated parameters and a Matlab file, which contains the segmentation that the user can use to derive further results.

Item Type: Article
Additional Information: The algorithm presented in this publication is a very important algorithm and of a potential high impact due to its on-line availability. The algorithm allows the quantitative analysis of the blood vessels in immunostained tumour sections. This goes beyond the traditional counting of vessels in hotspots and allows the size and shape of the vessels to be analysed as well. To increase the impact of the algorithm, it was included in a website where researchers can upload their images to be processed with this algorithm without the need to programme or download any specialised software.
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Depositing User: Constantino Reyes Aldasoro
Date Deposited: 06 Feb 2012 20:40
Last Modified: 02 Apr 2012 11:17
URI: http://sro.sussex.ac.uk/id/eprint/27398
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