Markerless real-time 3-D target region tracking by motion backprojection from projection images

A NOVEL ITERATIVE MATCHING SCHEME BASED ON HOMOGRAPHY METHOD FOR X-RAY IMAGE

Purpose anterior cervical decompression and fusion is a common surgical procedure. Traditionally, experienced doctors observe X-ray films regularly examined by patients to determine postoperative conditions by observing the tiny movements between the limited vertebral bodies. But it is not accurate. This may lead to error diagnostics and serious deterioration of the condition and secondary injury to the patient and will also put a greater financial burden on them. Doctors need a quantitative standard to determine small motion with limited vertebral landmarks after surgery. Computer vision technology is needed to match the over-extension and over-flexion cervical vertebral body to provide objective measurement data for further quantification of intervertebral activity. Based on conventional scheme, the point mean square error is used as the evaluation criterion of the matching effect, and the iterative matching scheme is proposed to improve the stability of the original scheme. The cervical X-ray films of patients from the China–Japan Friendship Hospital were collected as samples to verify the reliability of the scheme. Compared with the existing image matching schemes based on feature points, our scheme is superior in matching effect, matching speed and stability. This scheme can provide a solid foundation for further assisting doctors in the study of rehabilitation after anterior cervical fusion.

Dynamic 2-D/3-D Rigid Registration Framework Using Point-To-Plane Correspondence Model

In image-guided interventional procedures, live 2-D X-ray images can be augmented with preoperative 3-D computed tomography or MRI images to provide planning landmarks and enhanced spatial perception. An accurate alignment between the 3-D and 2-D images is a prerequisite for fusion applications. This paper presents a dynamic rigid 2-D/3-D registration framework, which measures the local 3-D-to-2-D misalignment and efficiently constrains the update of both planar and non-planar 3-D rigid transformations using a novel point-to-plane correspondence model. In the simulation evaluation, the proposed method achieved a mean 3-D accuracy of 0.07 mm for the head phantom and 0.05 mm for the thorax phantom using single-view X-ray images. In the evaluation on dynamic motion compensation, our method significantly increases the accuracy comparing with the baseline method. The proposed method is also evaluated on a publicly-available clinical angiogram data set with "gold-standard" registrations. The proposed method achieved a mean 3-D accuracy below 0.8 mm and a mean 2-D accuracy below 0.3 mm using single-view X-ray images. It outperformed the state-of-the-art methods in both accuracy and robustness in single-view registration. The proposed method is intuitive, generic, and suitable for both initial and dynamic registration scenarios.

2D/4D marker-free tumor tracking using 4D CBCT as the reference image

Tumor motion caused by respiration is an important issue in image-guided radiotherapy. A 2D/4D matching method between 4D volumes derived from cone beam computed tomography (CBCT) and 2D fluoroscopic images was implemented to track the tumor motion without the use of implanted markers. In this method, firstly, 3DCBCT and phase-rebinned 4DCBCT are reconstructed from cone beam acquisition. Secondly, 4DCBCT volumes and a streak-free 3DCBCT volume are combined to improve the image quality of the digitally reconstructed radiographs (DRRs). Finally, the 2D/4D matching problem is converted into a 2D/2D matching between incoming projections and DRR images from each phase of the 4DCBCT. The diaphragm is used as a target surrogate for matching instead of using the tumor position directly. This relies on the assumption that if a patient has the same breathing phase and diaphragm position as the reference 4DCBCT, then the tumor position is the same. From the matching results, the phase information, diaphragm position and tumor position at the time of each incoming projection acquisition can be derived. The accuracy of this method was verified using 16 candidate datasets, representing lung and liver applications and one-minute and two-minute acquisitions. The criteria for the eligibility of datasets were described: 11 eligible datasets were selected to verify the accuracy of diaphragm tracking, and one eligible dataset was chosen to verify the accuracy of tumor tracking. The diaphragm matching accuracy was 1.88 ± 1.35 mm in the isocenter plane and the 2D tumor tracking accuracy was 2.13 ± 1.26 mm in the isocenter plane. These features make this method feasible for real-time marker-free tumor motion tracking purposes.

Feasibility evaluation of a motion detection system with face images for stereotactic radiosurgery

In stereotactic radiosurgery we can irradiate a targeted volume precisely with a narrow high-energy x-ray beam, and thus the motion of a targeted area may cause side effects to normal organs. This paper describes our motion detection system with three USB cameras. To reduce the effect of change in illuminance in a tracking area we used an infrared light and USB cameras that were sensitive to the infrared light. The motion detection of a patient was performed by tracking his/her ears and nose with three USB cameras, where pattern matching between a predefined template image for each view and acquired images was done by an exhaustive search method with a general-purpose computing on a graphics processing unit (GPGPU). The results of the experiments showed that the measurement accuracy of our system was less than 0.7 mm, amounting to less than half of that of our previous system.

Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Simultaneous quantification of perfusion and permeability in the prostate using dynamic contrast-enhanced magnetic resonance imaging with an inversion-prepared dual-contrast sequence

The aim of the present study was to quantify both perfusion and extravasation in the prostate to discriminate tumor from healthy tissue, which might be achieved by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using a nonspecific low-molecular-weight contrast medium (CM). To determine extravasation as well as tissue perfusion an inversion-prepared dual-contrast sequence employing a parallel acquisition technique (PAT) was designed for interleaved acquisition of T(1)-weighted images for extravasation measurement and T(2)*-weighted images for determination of the highly concentrated bolus with a sufficiently high temporal and spatial resolution at an acceptable signal-to-noise ratio. Thirteen patients with proven prostate cancer were examined with the sequence using a combined body-array prostate coil. Before pharmacokinetic evaluation the images were intensity-corrected and, if required, motion-corrected. The pharmacokinetic model used to calculate perfusion, permeability, blood volume, interstitial volume, transit time, and vessel size index included two compartments and a correction of delay and dispersion of the arterial input function. The information provided by the dual-contrast sequence allowed application of a more elaborate model for evaluation and enabled quantification of all parameters. Peripheral prostate tumors were found to differ from peripheral healthy prostate tissue in perfusion (1.38 mL/(min cm(3)) vs. 0.23 mL/(min cm(3)), p=0.004), mean transit time (2.88 vs. 4.88 s, p=0.039), and blood volume (1.9 vs. 0.7%, p=0.019). A inversion-prepared dual-contrast sequence acquiring T(1)- and T*(2)-weighted images with sufficient temporal resolution and signal-to-noise ratio was successfully applied in patients with prostate cancer to quantify all pharmacokinetic parameters of inflow and extravasation of a low-molecular-weight inert tracer.