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Adaptation of the Daugman-Downing texture demodulation to highlight circumscribed mass lesions on mammograms

机译:适应Daugman-Downing纹理解调以在乳房X线照片上突出显示外接肿块

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J. Daugman and C. Downing introduced a new method (see "Spatial Vision in Humans and Robots: The Proceedings of the 1991 York Conference on Spatial Vision in Humans and Robots", ch.5, p.63-87, Cambridge University Press, 1993) for decomposing textures using a demodulation transform that they claimed had its basis in human visual perception. We argue that their transform may be applied to mammograms for image texture analysis and tissue characterization. An adaptation made to their demodulation transform is presented for the purpose of highlighting circumscribed mass lesions on mammograms. Three major modifications are introduced: (a) Fourier half-plane selection; (b) amplitude-only and phase-only reconstruction; (c) image subtraction to highlight masses on mammograms. This adapted algorithm exhibits high sensitivity for detecting circumscribed mass lesions and initial results are promising.
机译:J. Daugman和C. Downing引入了一种新方法(请参阅“人类与机器人的空间视觉:1991年约克人类与机器人空间视觉会议论文集”,第5章,第63-87页,剑桥大学出版社) (1993年),他们使用解调变换分解纹理,他们声称这是人类视觉感知的基础。我们认为,它们的变换可以应用于乳房X线照片,以进行图像纹理分析和组织表征。提出了对其解调变换进行的改编,目的是在乳房X线照片上突出显示外接的肿块。引入了三个主要修改:(a)傅立叶半平面选择; (b)仅振幅和仅相位的重建; (c)图像相减以突出显示乳房X线照片上的肿块。这种经过改进的算法对检测外接肿块具有很高的灵敏度,初步结果令人鼓舞。

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