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- W2022505809 abstract "3D Digital mammography (3DDM) is a new technology that provides high resolution X-ray breast tomographic data. Like any other tomographic medical imaging modalities, viewing a stack of tomographic images may require time especially if the images are of large matrix size. In addition, it may cause difficulty to conceptually construct 3D breast structures. Therefore, there is a need to readily visualize the data in 3D. However, one of the issues that hinder the usage of volume rendering (VR) is finding an automatic way to generate transfer functions that efficiently map the important diagnostic information in the data. We have developed a method that randomly samples the volume. Based on the mean and the standard deviation of these samples, the technique determines the lower limit and upper limit of a piecewise linear ramp transfer function. We have volume rendered several 3DDM data using this technique and compared visually the outcome with the result from a conventional automatic technique. The transfer function generated through the proposed technique provided superior VR images over the conventional technique. Furthermore, the improvement in the reproducibility of the transfer function correlated with the number of samples taken from the volume at the expense of the processing time." @default.
- W2022505809 created "2016-06-24" @default.
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- W2022505809 date "2002-05-16" @default.
- W2022505809 modified "2023-09-29" @default.
- W2022505809 title "<title>Automatic transfer function generation for volume rendering of high-resolution x-ray 3D digital mammography images</title>" @default.
- W2022505809 doi "https://doi.org/10.1117/12.466937" @default.
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