Biomedical data analysis on heterogeneous platform

摘要

Methods and apparatus for biomedical data analysis to produce enhanced images of tubular structures are disclosed. A Gaussian convolution of an input image is used to calculate a Hessian matrix. An Eigen decomposition of the Hessian matrix produces eigenvectors and eigenvalues, which are sorted to determine bright tubular structure detection according to high and low values that represent brightness, and structure shape. A tubularity computation calculates the probability of a voxel of interest being part of a tubular network. Embodiments may be implemented to share computer resources such as between a computer processing unit (CPU) and a graphic processing unit (GPU).

主权项

1. A method for image enhancement comprising:
performing a Gaussian convolution between at least one Gaussian kernel and voxels of an input image; calculating a Hessian matrix of the convolution; performing an Eigen decomposition of the Hessian matrix to derive eigenvectors and eigenvalues of the voxels; sorting the eigenvectors according to the magnitude of the corresponding eigenvalues; and performing a tubularity computation to calculate the probability of a voxel of the image being part of a tubular structure representation in the image whereby voxels determined to be part of tubular structures are used to provide an enhanced depiction of the image.