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Proceedings Paper

Volume and tissue composition preserving deformation of breast CT images to simulate breast compression in mammographic imaging
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Paper Abstract

Images of mastectomy breast specimens have been acquired with a bench top experimental Cone beam CT (CBCT) system. The resulting images have been segmented to model an uncompressed breast for simulation of various CBCT techniques. To further simulate conventional or tomosynthesis mammographic imaging for comparison with the CBCT technique, a deformation technique was developed to convert the CT data for an uncompressed breast to a compressed breast without altering the breast volume or regional breast density. With this technique, 3D breast deformation is separated into two 2D deformations in coronal and axial views. To preserve the total breast volume and regional tissue composition, each 2D deformation step was achieved by altering the square pixels into rectangular ones with the pixel areas unchanged and resampling with the original square pixels using bilinear interpolation. The compression was modeled by first stretching the breast in the superior-inferior direction in the coronal view. The image data were first deformed by distorting the voxels with a uniform distortion ratio. These deformed data were then deformed again using distortion ratios varying with the breast thickness and re-sampled. The deformation procedures were applied in the axial view to stretch the breast in the chest wall to nipple direction while shrinking it in the mediolateral to lateral direction re-sampled and converted into data for uniform cubic voxels. Threshold segmentation was applied to the final deformed image data to obtain the 3D compressed breast model. Our results show that the original segmented CBCT image data were successfully converted into those for a compressed breast with the same volume and regional density preserved. Using this compressed breast model, conventional and tomosynthesis mammograms were simulated for comparison with CBCT.

Paper Details

Date Published: 11 March 2009
PDF: 8 pages
Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72580K (11 March 2009); doi: 10.1117/12.813813
Show Author Affiliations
Tao Han, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Lingyun Chen, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Chao-Jen Lai, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Xinming Liu, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Youtao Shen, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Yuncheng Zhong, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Shuaiping Ge, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Ying Yi, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Tianpeng Wang, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Chris C. Shaw, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)


Published in SPIE Proceedings Vol. 7258:
Medical Imaging 2009: Physics of Medical Imaging
Ehsan Samei; Jiang Hsieh, Editor(s)

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