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Shift invariant extrema based feature analysis scheme to discriminate the spiculation nature of mammograms

机译:基于转移不变的极值的特征分析方案,以区分乳房X线图的刺激性质

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摘要

Since uncontrolled growth of malignant masses introduces uneven shape irregularities and spiculations in the boundary, shape representing shift invariant features are essential to resolve the problem of discrimination. However, ambiguous nature of shape, size, margin, orientation of masses produces imprecise feature values. In this view, a new concept of extrema based feature characterization scheme is proposed for capturing radiating nature of mass morphology. Computation of extrema patterns needs only few algorithmic steps. Beside this, present study employs an automated enhancement procedure to improve the classification accuracy. Experimental results show that extrema characterization reduces the feature redundancy to produce high efficiency in reasonably low time. (C) 2020 ISA. Published by Elsevier Ltd. All rights reserved.
机译:由于恶性肿块的不受控制的增长引入了边界中的不均匀形状和植精,因此代表换档不变特征的形状对于解决歧视问题至关重要。 然而,形状,尺寸,裕度,质量方向的模糊性质产生了不精确的特征值。 在这种观景中,提出了一种新的基于极值的特征表征方案的概念,用于捕获质量形态的辐射性质。 Extrema模式的计算只需要很少的算法步骤。 除此之外,目前的研究采用自动化增强程序来提高分类准确性。 实验结果表明,极值表征可降低特征冗余,以在相当低的时间内产生高效率。 (c)2020 ISA。 elsevier有限公司出版。保留所有权利。

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