Mr. Feiyu Chen Profile

Feiyu Chen

at Delaware State University

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Proceedings Article | 19 March 2013

Breast image registration by using non-linear local affine transformation

Feiyu Chen, Peng Zheng, Penglong Xu, Andrew Maidment, Predrag Bakic, David Pokrajac, Fengshan Liu, Xiquan Shi

Proc. SPIE. 8668, Medical Imaging 2013: Physics of Medical Imaging

KEYWORDS: Breast, Image compression, Breast cancer, Tissues, Databases, Composites, Control systems, Feature extraction, Image registration, Mammography

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A novel breast image registration method is proposed to obtain a composite mammogram from several images with partial breast coverage, for the purpose of accurate breast density estimation. The breast percent density estimated as a fractional area occupied by fibroglandular tissue has been shown to be correlated with breast cancer risk. Some mammograms, however, do not cover the whole breast area, which makes the interpretation of breast density estimates ambiguous. One solution is to register and merge mammograms, yielding complete breast coverage. Due to elastic properties of breast tissue and differences in breast positioning and deformation during the acquisition of individual mammograms, the use of linear transformations does not seem appropriate for mammogram registration. Non-linear transformations are limited by the changes in the mammographic projections pixel intensity with different positions of the focal spot. We propose a novel method based upon non-linear local affine transformations. Initially, pairs of feature points are manually selected and used to compute the best fit affine transformation in their small neighborhood. Finally, Shepherd interpolation is employed to compute affine transformations for the rest of the image area. The pixel values in the composite image are assigned using bilinear interpolation. Preliminary results with clinical images show a good match of breast boundaries, providing an increased coverage of breast tissue. The proposed transformation is continued and can be controlled locally. Moreover, the method is converging to the ground truth deformation if the paired feature points are evenly distributed and its number large enough.

Proceedings Article | 9 March 2012

Partial volume simulation in software breast phantoms

Feiyu Chen, David Pokrajac, Xiquan Shi, Fengshan Liu, Andrew D. Maidment, Predrag Bakic

Proc. SPIE. 8313, Medical Imaging 2012: Physics of Medical Imaging

KEYWORDS: Breast, Photovoltaics, Tissues, Signal attenuation, Image segmentation, Skin, X-rays, Computer programming, Computer simulations, Image quality

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A modification to our previous simulation of breast anatomy is proposed, in order to improve the quality of simulated projections generated using software breast phantoms. Anthropomorphic software breast phantoms have been used for quantitative validation of breast imaging systems. Previously, we developed a novel algorithm for breast anatomy simulation, which did not account for the partial volume (PV) of various tissues in a voxel; instead, each phantom voxel was assumed to contain single tissue type. As a result, phantom projection images displayed notable artifacts near the borders between regions of different materials, particularly at the skin-air boundary. These artifacts diminished the realism of phantom images. One solution is to simulate smaller voxels. Reducing voxel size, however, extends the phantom generation time and increases memory requirements. We achieved an improvement in image quality without reducing voxel size by the simulation of PV in voxels containing more than one simulated tissue type. The linear x-ray attenuation coefficient of each voxel is calculated by combining attenuation coefficients proportional to the voxel subvolumes occupied by the various tissues. A local planar approximation of the boundary surface is employed, and the skin volume in each voxel is computed by decomposition into simple geometric shapes. An efficient encoding scheme is proposed for the type and proportion of simulated tissues in each voxel. We illustrate the proposed methodology on phantom slices and simulated mammographic projections. Our results show that the PV simulation has improved image quality by reducing quantization artifacts.

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