Fiducial-free Alignment Verification Techniques for Intracranial Radiosurgery

The current process of intracranial radiosurgery treatment uses implanted titanium fiducials in the skull to assist in alignment of the patient. These fiducials add an element of physical and emotional stress to the patient, and scheduling the implantation procedures adds a delay of a few extra days before the radiosurgery procedure can begin. During the radiosurgery treatment, each proton beam is manually aligned by the therapist/physician with X-ray images and the fiducials that are visible on these images. This method of alignment can be time-intensive and requires personnel who are specifically trained in patient alignment. We propose a new method using image registration to automate this process in an effort to eliminate the need for surgical implantation of fiducials prior to treatment as well as to improve the accuracy and efficiency of alignment during treatment. Image registration is a technique used to align a moving image with respect to its known fixed image. Several methods of image registration are used for comparison: an enhanced correlation coefficient maximization algorithm, a mutual information maximization algorithm, and an extended phase correlation algorithm. Accuracy, robustness, and performance are emphasized in the comparison of these algorithms. Due to patient privacy, test images from MATLAB will be shown in this paper. This research was conducted under the clinical supervision of Dr. Andrew Wroe and Dr. Reinhard Schulte of the Loma Linda University Medical Center (LLUMC)

Robust and efficient parametric face alignment

We propose a correlation-based approach to parametric object alignment particularly suitable for face analysis applications which require efficiency and robustness against occlusions and illumination changes. Our algorithm registers two images by iteratively maximizing their correlation coefficient using gradient ascent. We compute this correlation coefficient from complex gradients which capture the orientation of image structures rather than pixel intensities. The maximization of this gradient correlation coefficient results in an algorithm which is as computationally efficient as ℓ2 norm-based algorithms, can be extended within the inverse compositional framework (without the need for Hessian recomputation) and is robust to outliers. To the best of our knowledge, no other algorithm has been proposed so far having all three features. We show the robustness of our algorithm for the problem of face alignment in the presence of occlusions and non-uniform illumination changes. The code that reproduces the results of our paper can be found at http://ibug.doc.ic.ac.uk/resources

Mesh-to-raster based non-rigid registration of multi-modal images

Region of interest (ROI) alignment in medical images plays a crucial role in diagnostics, procedure planning, treatment, and follow-up. Frequently, a model is represented as triangulated mesh while the patient data is provided from CAT scanners as pixel or voxel data. Previously, we presented a 2D method for curve-to-pixel registration. This paper contributes (i) a general mesh-to-raster (M2R) framework to register ROIs in multi-modal images; (ii) a 3D surface-to-voxel application, and (iii) a comprehensive quantitative evaluation in 2D using ground truth provided by the simultaneous truth and performance level estimation (STAPLE) method. The registration is formulated as a minimization problem where the objective consists of a data term, which involves the signed distance function of the ROI from the reference image, and a higher order elastic regularizer for the deformation. The evaluation is based on quantitative light-induced fluoroscopy (QLF) and digital photography (DP) of decalcified teeth. STAPLE is computed on 150 image pairs from 32 subjects, each showing one corresponding tooth in both modalities. The ROI in each image is manually marked by three experts (900 curves in total). In the QLF-DP setting, our approach significantly outperforms the mutual information-based registration algorithm implemented with the Insight Segmentation and Registration Toolkit (ITK) and Elastix

An ECC Based Iterative Algorithm For Photometric Invariant Projective Registration

International audienceThe ability of an algorithm to accurately estimate the parameters of the geometric trans- formation which aligns two image profiles even in the presence of photometric distortions can be considered as a basic requirement in many computer vision applications. Projec- tive transformations constitute a general class which includes as special cases the affine, as well as the metric subclasses of transformations. In this paper the applicability of a recently proposed iterative algorithm, which uses the Enhanced Correlation Coefficient as a performance criterion, in the projective image registration problem is investigated. The main theoretical results concerning the proposed iterative algorithm are presented. Furthermore, the performance of the iterative algorithm in the presence of nonlinear photometric distortions is compared against the leading Lucas-Kanade algorithm and its simultaneous inverse compositional variant with the help of a series of experiments involving strong or weak geometric deformations, ideal and noisy conditions and even over-modelling of the warping process. Although under ideal conditions the proposed al- gorithm and simultaneous inverse compositional algorithm exhibit a similar performance and both outperform the Lucas-Kanade algorithm, under noisy conditions the proposed algorithm outperforms the other algorithms in convergence speed and accuracy, and exhibits robustness against photometric distortions

Fiducial-free alignment verification techniques for intracranial radiosurgery

This thesis serves as the basis for a method using image registration to automate patient alignment in an effort to eliminate the dependency on the fiducial markers as well as improve the accuracy efficiency of the alignment process. Proton beams are an external beam modality of radiation therapy that can be used effectively for radiosurgical applications due to the dosimetry advantage of the Bragg peak. The Bragg peak is a phenomenon exploited by proton beam therapy to concentrate the effect of the beams on the tumor while minimizing damage to critical structures and other health tissues within the patient

Non-contrast renal magnetic resonance imaging to assess perfusion and corticomedullary differentiation in health and chronic kidney disease

AIMS Arterial spin labelling (ASL) MRI measures perfusion without administration of contrast agent. While ASL has been validated in animals and healthy volunteers (HVs), application to chronic kidney disease (CKD) has been limited. We investigated the utility of ASL MRI in patients with CKD. METHODS We studied renal perfusion in 24 HVs and 17 patients with CKD (age 22-77 years, 40% male) using ASL MRI at 3.0T. Kidney function was determined using estimated glomerular filtration rate (eGFR). T1 relaxation time was measured using modified look-locker inversion and xFB02;ow-sensitive alternating inversion recovery true-fast imaging and steady precession was performed to measure cortical and whole kidney perfusion. RESULTS T1 was higher in CKD within cortex and whole kidney, and there was association between T1 time and eGFR. No association was seen between kidney size and volume and either T1, or ASL perfusion. Perfusion was lower in CKD in cortex (136 ± 37 vs. 279 ± 69 ml/min/100 g; p < 0.001) and whole kidney (146 ± 24 vs. 221 ± 38 ml/min/100 g; p < 0.001). There was significant, negative, association between T1 longitudinal relaxation time and ASL perfusion in both the cortex (r = -0.75, p < 0.001) and whole kidney (r = -0.50, p < 0.001). There was correlation between eGFR and both cortical (r = 0.73, p < 0.01) and whole kidney (r = 0.69, p < 0.01) perfusion. CONCLUSIONS Significant differences in renal structure and function were demonstrated using ASL MRI. T1 may be representative of structural changes associated with CKD; however, further investigation is required into the pathological correlates of reduced ASL perfusion and increased T1 time in CKD