A Combined Random Forests and Active Contour Model Approach for Fully Automatic Segmentation of the Left Atrium in Volumetric MRI

Joint Authors

Luo, Gongning
Ma, Chao
Wang, Kuanquan

Source

BioMed Research International

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-02-19

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Medicine

Abstract EN

Segmentation of the left atrium (LA) from cardiac magnetic resonance imaging (MRI) datasets is of great importance for image guided atrial fibrillation ablation, LA fibrosis quantification, and cardiac biophysical modelling.

However, automated LA segmentation from cardiac MRI is challenging due to limited image resolution, considerable variability in anatomical structures across subjects, and dynamic motion of the heart.

In this work, we propose a combined random forests (RFs) and active contour model (ACM) approach for fully automatic segmentation of the LA from cardiac volumetric MRI.

Specifically, we employ the RFs within an autocontext scheme to effectively integrate contextual and appearance information from multisource images together for LA shape inferring.

The inferred shape is then incorporated into a volume-scalable ACM for further improving the segmentation accuracy.

We validated the proposed method on the cardiac volumetric MRI datasets from the STACOM 2013 and HVSMR 2016 databases and showed that it outperforms other latest automated LA segmentation methods.

Validation metrics, average Dice coefficient (DC) and average surface-to-surface distance (S2S), were computed as 0.9227±0.0598 and 1.14±1.205 mm, versus those of 0.6222–0.878 and 1.34–8.72 mm, obtained by other methods, respectively.

American Psychological Association (APA)

Ma, Chao& Luo, Gongning& Wang, Kuanquan. 2017. A Combined Random Forests and Active Contour Model Approach for Fully Automatic Segmentation of the Left Atrium in Volumetric MRI. BioMed Research International،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1139057

Modern Language Association (MLA)

Ma, Chao…[et al.]. A Combined Random Forests and Active Contour Model Approach for Fully Automatic Segmentation of the Left Atrium in Volumetric MRI. BioMed Research International No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1139057

American Medical Association (AMA)

Ma, Chao& Luo, Gongning& Wang, Kuanquan. A Combined Random Forests and Active Contour Model Approach for Fully Automatic Segmentation of the Left Atrium in Volumetric MRI. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1139057

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1139057