[Preliminary application of an improved Demons deformable registration algorithm in tumor radiotherapy].

Abstract

OBJECTIVE:

To validate the efficiency of an improved Demons deformable registration algorithm and evaluate its application in registration of the treatment image and the planning image in image-guided radiotherapy (IGRT).

METHODS:

Based on Brox's gradient constancy assumption and Malis's efficient second-order minimization algorithm, a grey value gradient similarity term was added into the original energy function, and a formula was derived to calculate the update of transformation field. The limited Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm was used to optimize the energy function for automatic determination of the iteration number. The proposed algorithm was validated using mathematically deformed images, physically deformed phantom images and clinical tumor images.

RESULTS:

Compared with the original Additive Demons algorithm, the improved Demons algorithm achieved a higher precision and a faster convergence speed.

CONCLUSION:

Due to the influence of different scanning conditions in fractionated radiation, the density range of the treatment image and the planning image may be different. The improved Demons algorithm can achieve faster and more accurate radiotherapy.

• Authors: Lu Zhou, Xin Zhen, Wenting Lu, Jianhong Dou, Linghong Zhou
• Journal: Nan fang yi ke da xue xue bao = Journal of Southern Medical University (Nan Fang Yi Ke Da Xue Xue Bao) Vol. 32 Issue 1 Pg. 40-5 (Jan 2012) ISSN: 1673-4254 [Print] China
• PMID: 22366002 (Publication Type: English Abstract, Journal Article, Research Support, Non-U.S. Gov't)

Topics

• Algorithms
• Humans
• Liver Neoplasms (radiotherapy)
• Radiotherapy Dosage
• Radiotherapy Planning, Computer-Assisted (methods)
• Radiotherapy, Conformal (methods)
• Radiotherapy, Image-Guided (methods)