POST-IVUS: A perceptual organisation-aware selective transformer framework for intravascular ultrasound segmentation.
dc.contributor.author | Huang, X | |
dc.contributor.author | Bajaj, R | |
dc.contributor.author | Li, Y | |
dc.contributor.author | Ye, X | |
dc.contributor.author | Lin, J | |
dc.contributor.author | Pugliese, F | |
dc.contributor.author | Ramasamy, A | |
dc.contributor.author | Gu, Y | |
dc.contributor.author | Wang, Y | |
dc.contributor.author | Torii, R | |
dc.contributor.author | Dijkstra, J | |
dc.contributor.author | Zhou, H | |
dc.contributor.author | Bourantas, CV | |
dc.contributor.author | Zhang, Q | |
dc.date.accessioned | 2023-09-14T09:48:00Z | |
dc.date.available | 2023-08-01 | |
dc.date.available | 2023-09-14T09:48:00Z | |
dc.date.issued | 2023-08-05 | |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/90705 | |
dc.description.abstract | Intravascular ultrasound (IVUS) is recommended in guiding coronary intervention. The segmentation of coronary lumen and external elastic membrane (EEM) borders in IVUS images is a key step, but the manual process is time-consuming and error-prone, and suffers from inter-observer variability. In this paper, we propose a novel perceptual organisation-aware selective transformer framework that can achieve accurate and robust segmentation of the vessel walls in IVUS images. In this framework, temporal context-based feature encoders extract efficient motion features of vessels. Then, a perceptual organisation-aware selective transformer module is proposed to extract accurate boundary information, supervised by a dedicated boundary loss. The obtained EEM and lumen segmentation results will be fused in a temporal constraining and fusion module, to determine the most likely correct boundaries with robustness to morphology. Our proposed methods are extensively evaluated in non-selected IVUS sequences, including normal, bifurcated, and calcified vessels with shadow artifacts. The results show that the proposed methods outperform the state-of-the-art, with a Jaccard measure of 0.92 for lumen and 0.94 for EEM on the IVUS 2011 open challenge dataset. This work has been integrated into a software QCU-CMS2 to automatically segment IVUS images in a user-friendly environment. | en_US |
dc.format.extent | 102922 - ? | |
dc.language | eng | |
dc.relation.ispartof | Med Image Anal | |
dc.rights | Attribution 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | * |
dc.subject | Atherosclerosis | en_US |
dc.subject | Intravascular ultrasound | en_US |
dc.subject | Plaque burden | en_US |
dc.subject | Semantic segmentation | en_US |
dc.title | POST-IVUS: A perceptual organisation-aware selective transformer framework for intravascular ultrasound segmentation. | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1016/j.media.2023.102922 | |
pubs.author-url | https://www.ncbi.nlm.nih.gov/pubmed/37598605 | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Published online | en_US |
pubs.volume | 89 | en_US |
dcterms.dateAccepted | 2023-08-01 |
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