ENHANCEMENT OF SCREEN FILM MAMMOGRAM UP TO A LEVEL OF DIGITAL MAMMOGRAM: EXPERIMENTAL ANALYSIS

Author:

BHALE APARNA NARENDRA1,JOSHI MANISH RATNAKAR1

Affiliation:

1. School of Computer Sciences, North Maharashtra University, Jalgaon, Maharashtra, India

Abstract

Breast cancer is one of the major causes of death among women. If a cancer can be detected early, the options of treatment and the chances of total recovery will increase. From a woman's point of view, the procedure practiced (compression of breasts to record an image) to obtain a digital mammogram (DM) is exactly the same that is used to obtain a screen film mammogram (SFM). The quality of DM is undoubtedly better than SFM. However, obtaining DM is costlier and very few institutions can afford DM machines. According to the National Cancer Institute 92% of breast imaging centers in India do not have digital mammography machines and they depend on the conventional SFM. Hence in this context, one should answer "Can SFM be enhanced up to a level of DM?" In this paper, we discuss our experimental analysis in this regard. We applied elementary image enhancement techniques to obtain enhanced SFM. We performed the quality analysis of DM and enhanced SFM using standard metrics like PSNR and RMSE on more than 350 mammograms. We also used mean opinion score (MOS) analysis to evaluate enhanced SFMs. The results showed that the clarity of processed SFM is as good as DM. Furthermore, we analyzed the extent of radiation exposed during SFM and DM. We presented our literally findings and clinical observations.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Classification of Mammogram Abnormalities Using Legendre Moments;International Journal of Image and Graphics;2020-12-18

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3