Mean nodal reconstruction error averaged across all train and test cases for the three geometries for NN and RR models.

Mean nodal reconstruction error averaged across all train and test cases for the three geometries for NN and RR models.

<p>Mean nodal reconstruction error averaged across all train and test cases for the three geometries for NN and RR models.</p>

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Bibliographic Details
Main Author:	Haolin Liu (789542) (author)
Other Authors:	Ye Han (261096) (author), Daniel Emerson (21087696) (author), Yoed Rabin (740690) (author), Levent Burak Kara (15301648) (author)
Published:	2025
Subjects:	Biophysics Physiology Biotechnology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Physical Sciences not elsewhere classified Information Systems not elsewhere classified techniques allow clinicians prediction takes less minimally invasive surgeries computed deformation field 3d deformed version body &# 8217 around 1 mm finite element method fidelity roi model autoencoder neural network fiducial marker displacements soft tissue deformations neural network soft tissues fiducial markers &# 64260 xlink "> work presents typical resolution surgical region simply tracking severe mismatch registers accurately realistic environment proposed approach new approach neck tumor linear deformations latent space interventional ultrasound ine setting driven approach diagnostic imaging ct imaging computational tests clinically relevant approach works apparatus used accurately map accurate tracking accurate registration 5 mm
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