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Related Experiment Video

Updated: Jun 25, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

Latent Accelerated Diffusion-based Deformation Estimation for Real-time Volumetric Imaging.

Kangning Zhang¹, Grace He², Yinheng Zhu³

¹Stanford University, 875 Blake Wilbur Dr, Palo Alto, Palo Alto, California, 94304-2205, United States.

Physics in Medicine and Biology

|June 23, 2026

Summary

This summary is machine-generated.

The LADDER framework enables real-time 3D respiratory motion estimation and volumetric imaging from sparse X-ray views. This novel approach achieves submillimeter accuracy, significantly advancing lung SBRT image guidance.

Keywords:

lung SBRT real-time deformation real-time volumetric imaging x-ray projections

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Last Updated: Jun 25, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

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Published on: April 16, 2017

Diffusion Imaging in the Rat Cervical Spinal Cord

Diffusion Imaging in the Rat Cervical Spinal Cord

Published on: April 7, 2015

Area of Science:

Medical Imaging
Computational Anatomy
Image Reconstruction

Background:

Current 3D respiratory motion estimation faces technical limitations, hindering real-time applications.
Ultra-sparse view data acquisition poses challenges for conventional deformable image registration and volumetric imaging.

Purpose of the Study:

To develop a novel framework for real-time 3D respiratory motion estimation and volumetric image reconstruction from ultra-sparse views.
To overcome data-acquisition constraints in clinical applications.

Main Methods:

Proposed the Latent Accelerated Diffusion framework for Deformation Estimation enabling Real-time (LADDER) volumetric imaging.
Integrated a VoxelMorph deformation network and a latent diffusion model (LDM)-based DIR model.
Utilized a physics-informed loss for anatomical regularity and projection consistency.

Main Results:

Achieved a mean target registration error (TRE) of 0.87±0.33 mm with dual-projection input.
Maintained high volumetric structure similarity (3D SSIM > 0.95) and low reconstruction error (3D NMSE < 0.006).
Demonstrated real-time inference (~0.11-0.12s) and improved deformation fidelity with dual-projection input.

Conclusions:

LADDER enables real-time 3D motion estimation and reconstruction from ultra-sparse X-ray views.
The framework shows potential for advanced motion management and image guidance in lung SBRT.
Submillimeter accuracy and real-time performance enhance safety and efficacy of lung radiotherapy.