Heart segmentation from chest x-ray images based on improved active shape model

Rui Jiang; XiaoLin Tian

doi:10.1117/12.2503007

9 August 2018 Heart segmentation from chest x-ray images based on improved active shape model

Rui Jiang, XiaoLin Tian

Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108065C (2018) https://doi.org/10.1117/12.2503007
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China

Abstract

In this paper, we propose an improved active shape model (ASM) which is based on a distance constraint to segment hearts from digital chest X-ray images. It includes three steps: 1) predict a rough position of a heart (RPOH) through projection, 2) train the shape model of the heart and register it to RPOH, so as to obtain an initial heart contour, and 3) utilize a cost function based on the distance constraint we introduce to get a more accurate contour of the heart. Further, to improve the accuracy of segmentation results, we minimize the cost function by minimizing the distance constraint. With the improved cost function, the probability of mark points falling into the non-target region can be reduced, thus improving the accuracy. The experiment results show that the improved cost function with eight neighboring points distance constraint effectively reduces influence of noises and avoids the problem of over segmentation of a heart to a certain extent.

Citation Download Citation

Rui Jiang and XiaoLin Tian "Heart segmentation from chest x-ray images based on improved active shape model", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108065C (9 August 2018); https://doi.org/10.1117/12.2503007

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