Automatic pelvis segmentation from x-ray images of a mouse model

Okashi, Omar and Du, Hongbo and Al-Assam, Hisham (2017) Automatic pelvis segmentation from x-ray images of a mouse model. In: Proc. SPIE, Mobile Multimedia/Image Processing, Security, and Applications.

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Official URL: http://dx.doi.org/10.1117/12.2264803

Abstract

The automatic detection and quantification of skeletal structures has a variety of different applications for biological research. Accurate segmentation of the pelvis from X-ray images of mice in a high-throughput project such as the Mouse Genomes Project not only saves time and cost but also helps achieving an unbiased quantitative analysis within the phenotyping pipeline. This paper proposes an automatic solution for pelvis segmentation based on structural and orientation properties of the pelvis in X-ray images. The solution consists of three stages including pre-processing image to extract pelvis area, initial pelvis mask preparation and final pelvis segmentation. Experimental results on a set of 100 X-ray images showed consistent performance of the algorithm. The automated solution overcomes the weaknesses of a manual annotation procedure where intra- and inter-observer variations cannot be avoided.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Pelvis Segmentation; X-ray; Mouse Model image Segmentation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Science > Applied Computing
Depositing User: Hisham Al Assam
Date Deposited: 10 Oct 2017 14:41
Last Modified: 10 Oct 2017 14:41
URI: http://bear.buckingham.ac.uk/id/eprint/207

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