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4Dsegment (bi-ventricular segmentation + motion tracking)

Imperial College London (Duan et al., UK Digital Heart Project) · 2019

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Code & model weights public

Automated pipeline that segments both heart ventricles and tracks their motion throughout the cardiac cycle from short-axis cine cardiac MRI, producing 3D bi-ventricular models with per-vertex wall-thickness and curvature measurements over time. Built on a shape-refined multi-task fully convolutional network, followed by non-rigid registration and mesh-based motion tracking. Trained on roughly 400 manually annotated pulmonary hypertension patients as part of Imperial College London's UK Digital Heart Project, and underlies the related 4Dsurvival cardiac-motion survival-prediction study.

Cardiac MRI

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Cardiac MRI

Cardiac chamber segmentation

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Structural Heart & Cardiomyopathy

Segmentation

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Segmentation & Detection

CNN (2D)

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Convolutional (CNN)

TensorFlow

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TensorFlow / Keras

GPL 3.0

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Copyleft


Model ID: 0002

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Subject Count: 400