Yugang Min

3D kinect camera systems are essential for real-time imaging of 3D treatment space that consists of both the patient anatomy as well as the treatment equipment setup. In this paper, we present the technical details of a 3D treatment room monitoring system that employs a scalable number of calibrated and coregistered Kinect v2 cameras. The monitoring system tracks radiation gantry and treatment couch positions, and tracks the patient and immobilization accessories. The number and positions of the cameras were selected to avoid line-of-sight issues and to adequately cover the treatment setup. The cameras were calibrated with a calibration error of 0.1 mm. Our tracking system evaluation show that both gantry and patient motion could be acquired at a rate of 30 frames per second. The transformations between the cameras yielded a 3D treatment space accuracy of < 2 mm error in a radiotherapy setup within 500mm around the isocenter.

The aim of this paper is to model and visualize cardiovascular deformations in order to better understand vascular movements inside the lung and heart caused by abnormal cardiac conditions. The modeling was performed in two steps: first step involved modeling the cardiac output taking into account of the heart rate and preload blood volume, contractility and systematic vascular resistance. The second step involved deforming a 3D cine cardiac gated Magnetic Resonance Volume to the corresponding cardiac output. Cardiac-gated MR imaging of 4 healthy volunteers were acquired. For each volunteer, a total of 24 short-axis and 18 radial planar views were acquired on a 1.5 T MR scanner during a series of 12-15 second breath-hold maneuvers. A 3D multi-resolution optical flow deformable image registration algorithm was used to quantify the volumetric cardiovascular displacements for known cardiac outputs. Results show that a real-time visualization of the vascular deformations inside both the lung as well as the heart can be seen for different cardiac outputs representing normal and abnormal cardiac conditions.

The aim of this paper is to enable model guided multi-scale and multi-modal image integration for the head and neck anatomy. The image modality used for this purpose includes multi-pose Magnetic Resonance Imaging (MRI), Mega Voltage CT, and hand-held Optical Coherence Tomography. A biomechanical model that incorporates subject-specific young's modulus and shear modulus properties is developed from multi-pose MRI, positioned in the treatment setup using Mega Voltage CT (MVCT), and actuated using multiple kinect surface cameras to mimic patient postures during Optical Coherence Microscopy (OCM) imaging. Two different 3D tracking mechanisms were employed for aligning the patient surface and the probe position to the MRI data. The results show the accuracy of the two tracking algorithms and the 3D head and neck deformation representing the multiple poses, the subject will take during the OCM imaging.

The aim of this paper is to model the airflow inside lungs during breathing and its fluid-structure interaction with the lung tissues and the lung tumor using subject-specific elastic properties. The fluid-structure interaction technique simultaneously simulates flow within the airway and anisotropic deformation of the lung lobes. The three-dimensional (3D) lung geometry is reconstructed from the end-expiration 3D CT scan datasets of humans with lung cancer. The lung is modeled as a poro-elastic medium with anisotropic elastic property (non-linear Young's modulus) obtained from inverse lung elastography of 4D CT scans for the same patients. The predicted results include the 3D anisotropic lung deformation along with the airflow pattern inside the lungs. The effect is also presented of anisotropic elasticity on both the spatio-temporal volumetric lung displacement and the regional lung hysteresis.

This paper reports on the usage of physics-based 3D volumetric lung dynamic models for visualizing and monitoring the radiation dose deposited on the lung of a human subject during lung radiotherapy. The dynamic model of each subject is computed from a 4D Computed Tomography (4DCT) imaging acquired before the treatment. The 3D lung deformation and the radiation dose deposited are computed using Graphics Processing Units (GPU). Additionally, using the dynamic lung model, the airflow inside the lungs during the treatment is also investigated. Results show the radiation dose deposited on the lung tumor as well as the surrounding tissues, the combination of which is patient-specific and varies from one treatment fraction to another.