Abstract:

The paper is addressed to detect the parameters of a sphere-center coordinates and radius based on a stack of CT slices. It is proposing a new hierarchical Hough transform approach. In the first step, all slices are taken into consideration sequentially and a 2D accumulator array is used to obtain the coordinates (x"0,y"0), the projecting value of the sphere center into every X-Y-plane. In this step, also a new type of 2D Hough transform for circle or circular detection is proposed based on an effective point filtering. In the second step, the radii of the circles in the different slices are obtained using 1D accumulator arrays. In the last step, the coordinate z"0 and the radius R of the sphere are acquired using a 2D planar Hough transform based on the correlation between the radii of circles, the coordinates z of the slice and the sphere radius. The hierarchical Hough transform is applied to analyze the structure of femoral head of human hip joints. Compared to the established Hough transform techniques for 3D object detection, the hierarchical Hough transform reduces storage space and calculation time significantly and it has a good robustness to noise in the images.

Abstract:

A computer-implemented method for reconstruction of a magnetic resonance image includes acquiring a first incomplete k-space data set comprising a plurality of first k-space lines spaced according to an acceleration factor and one or more calibration lines. A parallel imaging reconstruction technique is applied to the first incomplete k-space data to determine a plurality of second k-space lines not included in the first incomplete k-space data set, thereby yielding a second incomplete k-space data set. Then, the parallel imaging reconstruction technique is applied to the second incomplete k-space data to determine a plurality of third k-space lines not included in the second incomplete k-space data, thereby yielding a complete k-space data set.

Abstract:

A computer-implemented method for calculating a multi-dimensional wavelet transform in an image processing system comprising a plurality of computation units includes receiving multi-dimensional image data. An overlap value corresponding to a number of non-zero filter coefficients associated with the multi-dimensional wavelet transform is identified. Then the multi-dimensional image data is divided into a plurality of multi-dimensional arrays, wherein the multi-dimensional arrays overlap in each dimension by a number of pixels equal to the overlap value. A multi-dimensional wavelet transform is calculated for each multi-dimensional array, in parallel, across the plurality of computation units