Erik Normann Steen

Method and system for performing real time navigation of ultrasound volumetric data

An ultrasound system is provided that includes a display processor that accesses data volumes stored in an image buffer successively to control generation of at least one of 2D and 3D renderings based on display parameters. The display processor obtains from the image buffer a first data volume defined based on first scan parameter values, while a probe acquires ultrasound information for a second data volume that is entered into the image buffer. The second data volume is defined based on second scan parameter values. A navigation view presents in real time the renderings generated by the display processor with their corresponding 31) orientation. A navigator is provided that controls the display of the navigation view in real time such that, as the user adjusts a display parameter value to change a view plane, images presented in the navigation view are updated to reflect the view plane.

Multiscale nonlocal means method for ultrasound despeckling

Speckle noise is inherent in ultrasound imaging where it causes reduced contrast resolution and degrades the detectability of small structures. In this paper we propose a real-time multiscale despeckling filter based on the recently proposed Nonlocal Means (NL-means) filter. Our proposed despeckling method applies a cascade of NL-means filters from fine to coarse scale. It has been tested using an optimized OpenCL GPU implementation. We apply the filter to the US image prior to scan conversion to allow a more uniform filter response and better adaption to the point spread function of the imaging system. The filter compares favourably to other state-of-the-art methods according to three quantitative image measures on a simulated ultrasound image. On real ultrasound images the filter achieved good smoothing of speckle, while preserving small and low contrast features. The running time is between 10-20 ms on typical image sizes using a mid-range GPU.

Real-Time Nonlocal Means-Based Despeckling

In this paper, we propose a multiscale nonlocal means-based despeckling method for medical ultrasound. The multiscale approach leads to large computational savings and improves despeckling results over single-scale iterative approaches. We present two variants of the method. The first, denoted multiscale nonlocal means (MNLM), yields uniform robust filtering of speckle both in structured and homogeneous regions. The second, denoted unnormalized MNLM (UMNLM), is more conservative in regions of structure assuring minimal disruption of salient image details. Due to the popularity of anisotropic diffusion-based methods in the despeckling literature, we review the connection between anisotropic diffusion and iterative variants of NLM. These iterative variants in turn relate to our multiscale variant. As part of our evaluation, we conduct a simulation study making use of ground truth phantoms generated from clinical B-mode ultrasound images. We evaluate our method against a set of popular methods from the despeckling literature on both fine and coarse speckle noise. In terms of computational efficiency, our method outperforms the other considered methods. Quantitatively on simulations and on a tissue-mimicking phantom, our method is found to be competitive with the state-of-the-art. On clinical B-mode images, our method is found to effectively smooth speckle while preserving low-contrast and highly localized salient image detail.

Fixed Point Motion Estimation for frame rate up conversion in cardiac ultrasound

Frame rate up conversion in a low frame rate cardiac ultrasound scan makes the images run smoother and potentially increases the diagnostic value of the scan. Linear interpolation is one way of increasing frame rate; however, ghosting and blurring are the main drawbacks of this type of interpolation. In low frame rate cardiac ultrasound imaging, motion estimation and motion compensation techniques commonly used in optical imaging are not suitable, because of speckle noise as well as large movement of the cardiac valves compared to other anatomical features. We propose a novel method termed Fixed Point Motion Estimation(FPME) to handle these problems. FPME is a bidirectional tracker which extracts search regions from the previous and next frames in a pyramidal manner. The bottom of the pyramid uses a large search area around the moving object. At the higher level in the pyramid, the search region is narrowed down to capture the moving object. The motion vector at each level of the pyramid is used as an offset for the next level and the overall displacement will be the vector summation of motion vector at each level of the pyramid. This method works well if we do not have any out of plane movement. To have more reliable motion vectors, at each level a vector median filter is applied on the vector field. The result is used as an initialization for an optical flow regularization to capture subpixel movement. We demonstrate the performance of FPME on four standard cardiac ultrasound recordings. Our experiments show that, in ultrasound images, FPME works well compared to current motion estimation techniques in optical imaging; it removes ghosting and blurring artifacts in the movie. FPME frame rate up conversion reduces the average sum of squares error in the valve region by 5.6% relative to linear interpolation and increases the average peak signal-to-noise ratio by 2 db.