3D model-based approach to lung registration and prediction of respiratory cardiac motion

  • Authors:

  • Mikhail G. Danilouchkine;Jos J. M. Westenberg;Hans C. van Assen;Johan H. C. van Reiber;Boudewijn P. F. Lelieveldt

  • Affiliations:

  • Division of Image Processing, Dept. Radiology, Leiden University Medical Center, Leiden, The Netherlands;Division of Image Processing, Dept. Radiology, Leiden University Medical Center, Leiden, The Netherlands;Division of Image Processing, Dept. Radiology, Leiden University Medical Center, Leiden, The Netherlands;Division of Image Processing, Dept. Radiology, Leiden University Medical Center, Leiden, The Netherlands;Division of Image Processing, Dept. Radiology, Leiden University Medical Center, Leiden, The Netherlands

  • Venue:
  • MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper presents a new approach for lung registration and cardiac motion prediction, based on a 3D geometric model of the left lung. Feature points, describing a shape of this anatomical object, are automatically extracted from acquired tomographic images. The "goodness-of-fit" measure is assessed at each step in the iterative scheme until spatial alignment between the model and subject's specific data is achieved. We applied the proposed methods to register the 3D lung surfaces of 5 healthy volunteers of thoracic MRI acquired in different respiratory phases. We also utilized this approach to predict the spatial displacement of the human heart due to respiration. The obtained results demonstrate a promising registration performance.