@inproceedings{ff1713015a2a4b49929d1ba178856430,
title = "Multi-atlas based neointima segmentation in intravascular coronary OCT",
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.",
keywords = "IVOCT, multi-atlas based segmentation, neointima, patch-based label fusion, restenosis",
author = "Tung, {Kai Pin} and Bei, {Wen Jia} and Shi, {Wen Zhe} and Wang, {Hai Yan} and Tong Tong and {De Silva}, Ranil and Eddie Edwards and Daniel Rueckert",
year = "2013",
doi = "10.1109/ISBI.2013.6556765",
language = "English",
isbn = "9781467364546",
series = "Proceedings - International Symposium on Biomedical Imaging",
pages = "1280--1283",
booktitle = "ISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging",
note = "2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 ; Conference date: 07-04-2013 Through 11-04-2013",
}