Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/111750
Author(s): | Pedro Morais João L. Vilaça Sandro Queirós Alberto Marchi Felix Bourier Isabel Deisenhofer Jan D'hooge João Manuel R. S. Tavares |
Title: | Automated segmentation of the atrial region and fossa ovalis towards computer-aided planning of inter-atrial wall interventions |
Issue Date: | 2018-07 |
Abstract: | Background and objective: Image-fusion strategies have been applied to improve inter-atrial septal (IAS) wall minimally-invasive interventions. Hereto, several landmarks are initially identified on richly-detailed datasets throughout the planning stage and then combined with intra-operative images, enhancing the relevant structures and easing the procedure. Nevertheless, such planning is still performed manually, which is time-consuming and not necessarily reproducible, hampering its regular application. In this article, we present a novel automatic strategy to segment the atrial region (left/right atrium and aortic tract) and the fossa ovalis (FO). Methods: The method starts by initializing multiple 3D contours based on an atlas-based approach with global transforms only and refining them to the desired anatomy using a competitive segmentation strategy. The obtained contours are then applied to estimate the FO by evaluating both IAS wall thickness and the expected FO spatial location. Results: The proposed method was evaluated in 41 computed tomography datasets, by comparing the atrial region segmentation and FO estimation results against manually delineated contours. The automatic segmentation method presented a performance similar to the state-of-the-art techniques and a high feasibility, failing only in the segmentation of one aortic tract and of one right atrium. The FO estimation method presented an acceptable result in all the patients with a performance comparable to the inter-observer variability. Moreover, it was faster and fully user-interaction free. Conclusions: Hence, the proposed method proved to be feasible to automatically segment the anatomical models for the planning of IAS wall interventions, making it exceptionally attractive for use in the clinical practice. |
Subject: | Ciências Tecnológicas, Ciências médicas e da saúde Technological sciences, Medical and Health sciences |
Scientific areas: | Ciências médicas e da saúde Medical and Health sciences |
URI: | https://hdl.handle.net/10216/111750 |
Document Type: | Artigo em Revista Científica Internacional |
Rights: | openAccess |
Appears in Collections: | FEUP - Artigo em Revista Científica Internacional |
Files in This Item:
File | Description | Size | Format | |
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263262.pdf | Paper draft | 12.84 MB | Adobe PDF | View/Open |
263262.1.png | 1st page | 382.64 kB | image/png | View/Open |
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