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.

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.

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.

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.

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.

SENSE-DTI at 3 T.

While holding vast potential, diffusion tensor imaging (DTI) with single-excitation protocols still faces serious challenges. Limited spatial resolution, susceptibility to magnetic field inhomogeneity, and low signal-to-noise ratio (SNR) may be considered the most prominent limitations. It is demonstrated that all of these shortcomings can be effectively mitigated by the transition to parallel imaging technology and high magnetic field strength.

[Computer-assisted visualization of digital mammography images].

Purpose: In a clinical study, the feasibility of using a mammography workstation for the display and interpretation of digital mammography images was evaluated and the results were compared with the corresponding laser film hard copies.

Materials And Methods: Digital phosphorous plate radiographs of the entire breast were obtained in 30 patients using a direct magnification mammography system. The images were displayed for interpretation on the computer monitor of a dedicated mammography workstation and also presented as laser film hard copies on a film view box for comparison.

Scale-space signatures for the detection of clustered microcalculations in digital mammograms.

A method is described for the automated detection of microcalcifications in digitized mammograms. The method is based on the Laplacian scale-space representation of the mammogram only. First, possible locations of microcalcifications are identified as local maxima in the filtered image on a range of scales.