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Related Experiment Video

Updated: Jul 8, 2026

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Automated contour mapping with a regional deformable model.

Ming Chao¹, Tianfang Li, Eduard Schreibmann

¹Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305-5847, USA.

International Journal of Radiation Oncology, Biology, Physics

|January 22, 2008

Summary

This summary is machine-generated.

A new narrow-band algorithm efficiently auto-propagates region of interest contours across four-dimensional computed tomography (4D-CT) phases. This method achieves high spatial accuracy for contour mapping in radiation therapy planning.

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Published on: June 24, 2025

Area of Science:

Medical Imaging
Radiotherapy Physics
Computational Anatomy

Background:

Accurate delineation of regions of interest (ROI) is crucial for radiotherapy planning.
Four-dimensional computed tomography (4D-CT) captures respiratory motion, requiring contour propagation across multiple phases.
Manual contouring is time-consuming and subject to inter-observer variability.

Purpose of the Study:

To develop and evaluate a novel regional narrow-band algorithm for automated contour propagation.
To enable efficient transfer of ROI contours between different phases of 4D-CT data.
To improve the speed and accuracy of contouring in motion-adaptive radiotherapy.

Main Methods:

A narrow band representing the ROI boundary was created on a reference 4D-CT phase.
BSpline deformable registration mapped this band to other phases using Mattes mutual information.
The derived deformation field transformed manual contours to other phases; bidirectional mapping was used for validation.

Main Results:

The algorithm achieved high accuracy, with spatial accuracy better than 1.5 mm for adjacent 4D-CT phases and 3 mm for opposite phases.
Testing on synthetic and clinical data (thoracic 4D-CT, head-and-neck Cone-beam CT) demonstrated feasibility.
Computational efficiency was significantly improved (order of magnitude faster) with reduced memory usage compared to whole-image methods.

Conclusions:

The narrow-band approach provides an efficient and accurate method for contour mapping in 4D imaging.
This technique holds significant potential for widespread adoption in 4D treatment planning workflows.
Automation of contour propagation can streamline radiotherapy planning and potentially improve treatment consistency.