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Investigation of Breast Melanoma using Hybrid Image-Processing-Tool

机译:使用混合图像处理工具调查乳房黑色素瘤

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Breast-Cancer (BC) is a life intimidating illness among the women society and early revealing may assist to afford suitable treatment to reduce risk factor. Digital-Mammogram (DM) is an accepted practice to record and inspect BC. The work presented here implements a Hybrid Image-Processing-Tool by combining Tsallis-Thresholding (TT) and Level-Set-Segmentation (LSS). This tool helps to mine the apprehensive division of DM. Primarily, Jaya-Algorithm based TT using three-stage thresholding is executed to enhance the DM and later, the LSS is considered to mine the infected section. The mined region is then assessed with the GLCM to know the harshness of infection by investigating its texture-features. The investigational outcome of this paper authenticates the superiority of proposed tool in extracting the breast melanoma from the chosen DM dataset.
机译:乳腺癌(BC)是女性社会中令人生畏的疾病,尽早发现可能有助于提供适当的治疗方法以降低危险因素。乳腺钼靶检查(DM)是记录和检查BC的公认做法。本文介绍的工作通过结合Tsallis阈值(TT)和水平集分段(LSS)来实现混合图像处理工具。该工具有助于挖掘DM的复杂部门。首先,执行使用三阶段阈值的基于Jaya-Algorithm的TT来增强DM,然后考虑使用LSS来挖掘受感染的部分。然后通过GLCM对雷区进行评估,以通过研究其纹理特征来了解感染的严重性。本文的研究成果证实了所建议工具在从所选DM数据集中提取乳腺黑色素瘤中的优越性。

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