Artis-Zeego is an advanced interventional imaging system that can provide the three-dimensional (3-D) reconstruction of the coronary artery in real time. However, the mechanical accuracy will degenerate after long-time use. The inaccurate geometry will affect the spatial resolution of the 3-D reconstruction. We propose a calibration algorithm to tackle this problem. There are three steps of our algorithm. First, we propose a geometry estimation algorithm that is based on the classical helical phantom. Second, we transfer the geometry to the nominal C-arm coordinate system. Third, we propose the posteriori movement models at three imaging work positions. The contributions include three parts. First, the proposed geometry estimation algorithm is more robust and easier to implement than other algorithms that are based on the helical phantom. Second, the geometry parameters can be transferred to the nominal C-arm system. Therefore, the calibration work will be independent of the phantom placement. Third, the movement models can estimate and predict the geometries at any acquisition angle. The clinical experiments demonstrate that the proposed method can estimate and predict the acquisition geometry with accuracy. The acquisition trajectories can be modeled as a rigid motion at head and left work positions. The acquisition trajectory should be modeled as a rigid motion with a residual translation at Table30 work position.
Video-Assisted Thoracoscopic Surgery (VATS) is a promising surgical treatment for early-stage lung cancer. With
respect to standard thoracotomy, it is less invasive and provides better and faster patient recovery. However, a
main issue is the accurate localization of small, subsolid nodules. While intraoperative Cone-Beam CT (CBCT)
images can be acquired, they cannot be directly compared with preoperative CT images due to very large lung
deformations occurring before and during surgery. This paper focuses on the quantification of deformations
due to the change of positioning of the patient, from supine during CT acquisition to lateral decubitus in the
operating room. A method is first introduced to segment the lung cavity in both CT and CBCT. The images
are then registered in three steps: an initial alignment, followed by rigid registration and finally non-rigid
registration, from which deformations are measured. Accuracy of the registration is quantified based on the
Target Registration Error (TRE) between paired anatomical landmarks. Results of the registration process are
on the order of 1.01 mm in median, with minimum and maximum errors 0.35 mm and 2.34 mm. Deformations
on the parenchyma were measured to be up to 14 mm and approximately 7 mm in average for the whole lung
structure. While this study is only a first step towards image-guided therapy, it highlights the importance
of accounting for lung deformation between preoperative and intraoperative images, which is crucial for the
intraoperative nodule localization.
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