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Zhang et al., 2021 - Google Patents

Fully automated left atrium segmentation from anatomical cine long-axis MRI sequences using deep convolutional neural network with unscented Kalman filter

Zhang et al., 2021

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Document ID
16281524426933936405
Author
Zhang X
Noga M
Martin D
Punithakumar K
Publication year
Publication venue
Medical image analysis

External Links

Snippet

This study proposes a fully automated approach for the left atrial segmentation from routine cine long-axis cardiac magnetic resonance image sequences using deep convolutional neural networks and Bayesian filtering. The proposed approach consists of a classification …
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Classifications

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    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30048—Heart; Cardiac
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
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    • G06T7/0014—Biomedical image inspection using an image reference approach
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    • G06T2207/30101—Blood vessel; Artery; Vein; Vascular
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