The proposed E-Pix2Vox++ network achieved accurate 3D whole-heart reconstructions with a peak intersection over union score of 0.881 from just two standard anatomical 2D views.
Does the Efficient Pix2Vox++ pipeline enable accurate 3D cardiac reconstruction from 2D echo views?
The proposed Efficient Pix2Vox++ pipeline enables accurate 3D anatomical reconstruction of the heart from limited 2D echocardiography data, potentially reducing reliance on operator expertise.
Absolute Event Rate: 0.881% vs 0.873%
Accurate geometric quantification of the human heart is a key step in the diagnosis of numerous cardiac diseases, and in the management of cardiac patients. Ultrasound imaging is the primary modality for cardiac imaging, however acquisition requires high operator skill, and its interpretation and analysis is difficult due to artifacts. Reconstructing cardiac anatomy in 3D can enable discovery of new biomarkers and make imaging less dependent on operator expertise, however most ultrasound systems only have 2D imaging capabilities. We propose both a simple alteration to the Pix2Vox++ networks for a sizeable reduction in memory usage and computational complexity, and a pipeline to perform reconstruction of 3D anatomy from 2D standard cardiac views, effectively enabling 3D anatomical reconstruction from limited 2D data. We evaluate our pipeline using synthetically generated data achieving accurate 3D whole-heart reconstructions (peak intersection over union score > 0.88) from just two standard anatomical 2D views of the heart. We also show preliminary results using real echo images.
Stojanovski et al. (Sat,) conducted a other in 3D Cardiac Reconstruction (n=1,000). E-Pix2Vox++ (E-PiVox) vs. Pix2Vox++ (PiVox) was evaluated on Peak intersection over union (IoU) score for 3D reconstruction from two 2D views. The proposed E-Pix2Vox++ network achieved accurate 3D whole-heart reconstructions with a peak intersection over union score of 0.881 from just two standard anatomical 2D views.