Multi-atlas based neointima segmentation in intravascular coronary OCT

Tung KP, Bei WJ, Shi WZ, Wang HY, Tong T, De Silva R, Edwards E, Rueckert D (2013)

Publication Type: Conference contribution

Publication year: 2013

Journal

Proceedings - International Symposium on Biomedical Imaging

Pages Range: 1280-1283

Conference Proceedings Title: Proceedings - International Symposium on Biomedical Imaging

Event location: USA

ISBN: 9781467364546

DOI: 10.1109/ISBI.2013.6556765

Abstract

Neointima thickening plays a decisive role in coronary restenosis after stenting. The aim of this study is to detect neointima tissue in intravascular optical coherence tomography (IVOCT) sequences. We developed a multi-atlas based segmentation method to detect neointima without stent struts locations. The atlases are selected by measurements of stenosis and a similarity metric. The probability map is then used to estimate neointima label in the unseen image. To account for the registration errors, a patch-based label fusion approach is applied. Validation is performed using 18 typical in-vivo IVOCT sequences. The comparison against manual expert segmentation and other fusion approaches demonstrates that the proposed neointima identification is robust and accurate. © 2013 IEEE.

Involved external institutions

Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB) Royal Brompton Hospital GB United Kingdom (GB)

How to cite

APA:

Tung, K.P., Bei, W.J., Shi, W.Z., Wang, H.Y., Tong, T., De Silva, R.,... Rueckert, D. (2013). Multi-atlas based neointima segmentation in intravascular coronary OCT. In Proceedings - International Symposium on Biomedical Imaging (pp. 1280-1283). USA.

MLA:

Tung, Kai Pin, et al. "Multi-atlas based neointima segmentation in intravascular coronary OCT." Proceedings of the 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013, USA 2013. 1280-1283.

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