Multi-ROI segmentation for effective texture features of mammogram images

被引：4
|
作者：
Kumar, C. Praveen [1 ]
Prasad, K. Rajendra [2 ]
机构：
[1] Shri Jagdish Prasad Jhabarmal Tibrewala Univ, Dept Comp Sci & Engn, Jhunjhunu 333001, Rajasthan, India
[2] Rajeev Gandhi Mem Coll Engn & Technol, Dept Comp Sci & Engn, Kurnool 518501, Andhra Pradesh, India
来源：
JOURNAL OF DISCRETE MATHEMATICAL SCIENCES & CRYPTOGRAPHY | 2021年 / 24卷 / 08期
关键词：
Digital mammography; Calcifications; Enhancement techniques; Pre-processing; KEY DISTRIBUTION PROTOCOL; BLACK-HOLE; DESIGN;
D O I：
10.1080/09720529.2021.2016192
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Image segmentation is an emerging requirement in digital mammography for segmenting the mammogram images. It is performed by region of interest (ROI), which is useful for the extraction of suspected tumors or masses from the mammogram images. In the classification of mammogram images, the number of training images are required; in such cases, ROI demands more computational time. This paper is focused on this problem for resolving the time complexity issues with the proposed multi-ROI technique. Experiment is conducted on benchmarked datasets for demonstrating the efficiency of proposed multi-ROI with the comparison of the existing segmentation method.
引用
收藏
页码：2461 / 2469
页数：9
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