Correction of misaligned slices in multi-slice cardiovascular magnetic resonance using slice-to-volume registration.

A popular technique to reduce respiratory motion for cardiovascular magnetic resonance is to perform a multi-slice acquisition in which a patient holds their breath multiple times during the scan. The feasibility of rigid slice-to-volume registration to correct for misalignments of slice stacks in such images due to differing breath-hold positions is explored. Experimental results indicate that slice-to-volume registration can compensate for the typical misalignments expected. Correction of slice misalignment results in anatomically more correct images, as well as improved left ventricular volume measurements. The interstudy reproducibility has also been improved reducing the number of samples needed for cardiac MR studies.

Projection extension for region of interest imaging in cone-beam CT.

RATIONALE AND OBJECTIVES: For 3D X-ray imaging during interventions, changes of the imaged object are often restricted to a small part of the field of view, suggesting region of interest (ROI) imaging by irradiating this area only. In this article, we present a novel method for extension of truncated projections in order to avoid truncation artifacts in C-arm based 3D ROI imaging. MATERIALS AND METHODS: The method makes use of prior knowledge by combining forward projections of a previously acquired, nontruncated 3D reference image with the truncated ROI projections. Rigid registration between the two datasets is achieved by using a technique based on local cross-correlation. To account for a gray value mismatch between the two data sets due to, e.g., differing beam quality and different contributions of scattered radiation, a linear gray level transformation is applied to the forward-projected reference data. RESULTS: The performance of different gray value transformation schemes is systematically assessed by means of numerical simulations. For various simulated scenarios, the best performing transformation has been identified, providing practical guidelines for selecting a scheme depending on the origin of the gray-level mismatch. Experiments prove the high performance of the developed method. CONCLUSION: The presented technique enables almost artifact-free 3D ROI imaging during interventions. This actually allows for repeated scans at low dose and enables intraprocedural imaging of large objects even with a small detector. However, applicability of the method is limited to scenarios where direct access to a reference image, e.g., a prior CT scan, is available.

Quantitative evaluation of image-based distortion correction in diffusion tensor imaging.

A statistical method for the evaluation of image registration for a series of images based on the assessment of consistency properties of the registration results is proposed. Consistency is defined as the residual error of the composition of cyclic registrations. By combining the transformations of different algorithms the consistency error allows a quantitative comparison without the use of ground truth, specifically, it allows a determination as to whether the algorithms are compatible and hence provide comparable registrations. Consistency testing is applied to evaluate retrospective correction of eddy current-induced image distortion in diffusion tensor imaging of the brain. In the literature several image transformations and similarity measures have been proposed, generally showing a significant reduction of distortion in side-by-side comparison of parametric maps before and after registration. Transformations derived from imaging physics and a three-dimensional affine transformation as well as mutual information (MI) and local correlation (LC) similarity are compared to each other by means of consistency testing. The dedicated transformations could not demonstrate a significant difference for more than half of the series considered. LC similarity is well-suited for distortion correction providing more consistent registrations which are comparable to MI.

Automatic image-driven segmentation of the ventricles in cardiac cine MRI.

PURPOSE: To propose and to evaluate a novel method for the automatic segmentation of the heart's two ventricles from dynamic ("cine") short-axis "steady state free precession" (SSFP) MR images. This segmentation task is of significant clinical importance. Previously published automated methods have various disadvantages for routine clinical use. MATERIALS AND METHODS: The proposed method is primarily image-driven: it exploits the spatiotemporal information provided by modern 3D+time SSFP cardiac MRI, and makes only few and plausible assumptions about the image acquisition and about the imaged heart. Specifically, the method does not require previously trained statistical shape models or gray-level appearance models, as often used by other methods. RESULTS: The performance of the segmentation method was demonstrated through a qualitative visual validation on 32 clinical exams: no gross failures for the left-ventricle (right-ventricle) on 31 (29) of the exams were found. A validation of resulting quantitative cardiac functional parameters showed good agreement with a manual quantification of 19 clinical exams. CONCLUSION: The proposed method is feasible, fast, and robust against anatomical variability and image contrast variations.

Real-time interactive viewing of 4D kinematic MR joint studies.

Assessment of soft tissue in normal and abnormal joint motion today gets feasible by acquiring time series of 3D MRI images. However, slice-by-slice viewing of such 4D kinematic images is cumbersome, and does not allow appreciating the movement in a convenient way. Simply presenting slice data in a cine-loop will be compromised by through-plane displacements of anatomy and "jerks" between frames, both of which hamper visual analysis of the movement. To overcome these limitations, we have implemented a demonstrator for viewing 4D kinematic MRI datasets. It allows to view any user defined anatomical structure from any viewing perspective in real-time. Smoothly displaying the movement in a cine-loop is realized by image post processing, fixing any user defined anatomical structure after image acquisition.