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3D high-resolution cardiac segmentation reconstruction from 2D views using conditional variational autoencoders
File | Description | Size | Format | |
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1902.11000v1.pdf | Accepted version | 2.31 MB | Adobe PDF | View/Open |
Title: | 3D high-resolution cardiac segmentation reconstruction from 2D views using conditional variational autoencoders |
Authors: | Biffi, C Cerrolaza, JJ Tarroni, G De Marvao, A Cook, SA O'Regan, DP Rueckert, D |
Item Type: | Conference Paper |
Abstract: | Accurate segmentation of heart structures imaged by cardiac MR is key for the quantitative analysis of pathology. High-resolution 3D MR sequences enable whole-heart structural imaging but are time-consuming, expensive to acquire and they often require long breath holds that are not suitable for patients. Consequently, multiplanar breath-hold 2D cines sequences are standard practice but are disadvantaged by lack of whole-heart coverage and low through-plane resolution. To address this, we propose a conditional variational autoencoder architecture able to learn a generative model of 3D high-resolution left ventricular (LV) segmentations which is conditioned on three 2D LV segmentations of one short-axis and two long-axis images. By only employing these three 2D segmentations, our model can efficiently reconstruct the 3D high-resolution LV segmentation of a subject. When evaluated on 400 unseen healthy volunteers, our model yielded an average Dice score of 87.92 ± 0.15 and outperformed competing architectures (TL-net, Dice score = 82.60 ± 0.23, p = 2.2 · 10 -16 ). |
Issue Date: | 11-Jul-2019 |
Date of Acceptance: | 1-Apr-2019 |
URI: | http://hdl.handle.net/10044/1/73720 |
DOI: | https://doi.org/10.1109/ISBI.2019.8759328 |
ISSN: | 1945-7928 |
Publisher: | IEEE |
Start Page: | 1643 |
End Page: | 1646 |
Journal / Book Title: | 2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019) |
Copyright Statement: | ©2019 IEEE. |
Sponsor/Funder: | Imperial College Healthcare NHS Trust- BRC Funding British Heart Foundation Imperial College Healthcare NHS Trust- BRC Funding |
Funder's Grant Number: | RDC04 NH/17/1/32725 RDB02 |
Conference Name: | 16th IEEE International Symposium on Biomedical Imaging (ISBI) |
Keywords: | Cardiac MR Variational Autoencoder 3D Segmentation Reconstruction Deep Learning MASS Cardiac MR Variational Autoencoder 3D Segmentation Reconstruction Deep Learning MASS cs.CV cs.CV |
Publication Status: | Published |
Start Date: | 2019-04-08 |
Finish Date: | 2019-04-11 |
Conference Place: | Venice, ITALY |
Online Publication Date: | 2019-07-11 |
Appears in Collections: | Computing Institute of Clinical Sciences |