Evaluation of Demons- and FEM-Based Registration Algorithms for Lung Cancer. (April 2016)

• Record Type: Journal Article
• Authors: Yang, Juan; Li, Dengwang; Yin, Yong; Zhao, Fen; Wang, Hongjun
• Is Part Of: Technology in cancer research & treatment. Volume 15:Number 2(2016:Apr.)
• Page Start: 275
• Page End: 284
• Publication Date: 2016-04
• Subjects: 4D CT -- registration accuracy -- deformable image registration -- diffeomorphic demons algorithm -- FEM-based algorithm; Oncology -- Periodicals; Cancer -- Diagnosis -- Periodicals; Cancer -- Treatment -- Technological innovations -- Periodicals; 616.994
• DOI: 10.1177/1533034615574950
• Languages: English
• ISSNs: 1533-0346

Abstract

We evaluated and compared the accuracy of 2 deformable image registration algorithms in 4-dimensional computed tomography images for patients with lung cancer. Ten patients with non-small cell lung cancer or small cell lung cancer were enrolled in this institutional review board-approved study. The displacement vector fields relative to a specific reference image were calculated by using the diffeomorphic demons (DD) algorithm and the finite element method (FEM)-based algorithm. The registration accuracy was evaluated by using normalized mutual information (NMI), the sum of squared intensity difference (SSD), modified Hausdorff distance ( d H _ M ), and ratio of gross tumor volume ( rGTV ) difference between reference image and deformed phase image. We also compared the registration speed of the 2 algorithms. Of all patients, the FEM-based algorithm showed stronger ability in aligning 2 images than the DD algorithm. The means (±standard deviation) of NMI were 0.86 (±0.05) and 0.90 (±0.05) using the DD algorithm and the FEM-based algorithm, respectively. The means of SSD were 0.006 (±0.003) and 0.003 (±0.002) using the DD algorithm and the FEM-based algorithm, respectively. The means of d H _ M were 0.04 (±0.02) and 0.03 (±0.03) using the DD algorithm and the FEM-based algorithm, respectively. The means of rGTV were 3.9% (±1.01%) and 2.9% (±1.1%) using the DD algorithm and the FEM-based algorithm, respectively. However, the FEM-based algorithm costs a longer time than the DD algorithm, with the average running time of 31.4 minutes compared to 21.9 minutes for all patients. The preliminary results showed that the FEM-based algorithm was more accurate than the DD algorithm while compromised with the registration speed.