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Temperature Dependent Deformation

Temperature Dependent Deformation

In a nonhomogeneous rod made up of steel and brass, restrained at both ends and subjected to a temperature change, several steps are involved in calculating the stress and compressive load. Due to the problem's static indeterminacy, one end support is disconnected, allowing the rod to experience the temperature change freely. Next, an unknown force is applied at the free end, triggering deformations in the rod's steel and brass portions. These deformations are then calculated and added...

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Updated: May 4, 2026

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

An implicit neural deformable ray model for limited and sparse view-based spatiotemporal reconstruction.

Yuanwei He¹, Dan Ruan^1,2

¹Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.

Medical Physics

|March 4, 2025

Summary

This study introduces a novel method for continuous 4D imaging in radiation therapy, enabling accurate anatomical monitoring. The INDeR model reconstructs detailed patient volumes from sparse X-ray views, improving treatment analysis.

Keywords:

CT reconstruction implicit neural field motion estimation ray tracing

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Area of Science:

Medical Imaging
Computational Anatomy
Radiation Oncology

Background:

Continuous spatiotemporal volumetric reconstruction is crucial for radiation therapy to analyze treatment outcomes.
Current methods face limitations due to radiation exposure and hardware, often relying on intermittent imaging.
Accurate tracking of patient anatomy during treatment is essential for dose calculation and outcome prediction.

Purpose of the Study:

To develop a method for spatiotemporal reconstruction from limited X-ray views.
To achieve continuous-time dynamic volume reconstruction using minimal input projections.
To enable patient-specific volumetric reconstruction with as few as 20 views and real-time tracking with two orthogonal views.

Main Methods:

Introduced the implicit neural deformable ray (INDeR) model.
Utilized a ray bundle coordinate system and embedded sparse view measurements into an implicit neural field.
Estimated real-time motion via low-dimensional modulation for deformable ray bundles.

Main Results:

The INDeR model achieved robust image reconstruction and motion tracking.
Demonstrated high peak signal-to-noise ratio (PSNR) of 30.13 dB with 20 views, outperforming existing methods.
Maintained a PSNR > 27.41 dB in real-time using only two orthogonal projections.

Conclusions:

The INDeR framework successfully reconstructs continuous spatiotemporal representations from sparse views.
Achieved highly accurate reconstruction with minimal projections and effective real-time tracking.
Shows significant potential for anatomical monitoring in radiation therapy.