Lung image registration by featured surface matching method
Journal
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION
Date Issued
2022
Author(s)
Abstract
The objective is to validate lung image registration using the featured surface matching method. The method can be applied to volume-to-surface deformable image registration, which is the 3D volume image to be deformed and aligned with a 3D surface image. Curvature variation extracts the surface feature. A group of neighbour curvature variations forms a local surface feature. A surface-matching scheme uses the local surface feature to determine the correspondence between two surface points. A finite element model uses the surface point correspondence to propagate the surface displacement into internal tissues and determine the intraoperative landmark locations from the deformed image. The validation uses the publicly available DIRLAB and POPI datasets to assess target registration errors. The work shows that the target registration error is 1.88 ± 1.16 mm, 4.77 ± 2.59 mm, and 4.12 ± 2.22 mm, and the initial error is 4.01 ± 2.91 mm, 11.10 ± 6.98 mm, 11.66 ± 6.23 mm for DIRLAB lung #1, DIRLAB lung #6 and POPI lung #1, respectively. The proposed method outperforms the average of other methods. The proposed novel surface matching method is feasible and validated.
Subjects
Deformable models; finite element analysis; image registration; DEFORMABLE REGISTRATION; MOTION
SDGs
Publisher
TAYLOR & FRANCIS LTD
Type
journal article