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Found 3 papers, 1 papers with code
Implicit Tubular Surface Generation Guided by Centerline
Most machine learning-based coronary artery segmentation methods represent the vascular lumen surface in an implicit way by the centerline and the associated lumen radii, which makes the subsequent modeling process to generate a whole piece of watertight coronary artery tree model difficult.
Fast Segmentation of Left Ventricle in CT Images by Explicit Shape Regression using Random Pixel Difference Features
On a dataset consisting of 139 CT volumes, a 5-fold cross validation shows the segmentation error is $1. 21 \pm 0. 11$ for LV endocardium and $1. 23 \pm 0. 11$ millimeters for epicardium.
Globally Tuned Cascade Pose Regression via Back Propagation with Application in 2D Face Pose Estimation and Heart Segmentation in 3D CT Images
We empirically show that global training with BP outperforms layer-wise (pre-)training.
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