基于离散小波变换的医学图像融合技术

P. Prasad, S. Subramani, V. Bhavana, H. Krishnappa
{"title":"基于离散小波变换的医学图像融合技术","authors":"P. Prasad, S. Subramani, V. Bhavana, H. Krishnappa","doi":"10.1109/ICCMC.2019.8819672","DOIUrl":null,"url":null,"abstract":"Identifying the ailments and to cure these ailments require accurate and defined evidence that has to be obtained from different kinds of medical images, like Positron Emission tomography(PET), Computed tomography(CT), Magnetic Resonance Imaging(MRI) etc. By undergoing their respective procedure and scans, these methods are commonly used, since they provide necessary evidence and indications about the disease whose information is insufficient and vague. In the given situation, fusion of medical images can be of greatest importance as the complete standard of scans can be improvised and upgraded. Hence, combining various multimodality medical images provides an adverse image with more properly specified data of body structure and high spectral data. Image fusion is highly opted in therapeutic analysis and testing. In this paper, the MRI and PET scans are processed. Before applying any further transformations, we enhance the standard of the images, as these images are tainted and non-readable due to numerous aspects. With the help of Gaussian filters, this is one of the important spatial filtering techniques. Discrete wavelet transform is applied on the images obtained after filtering two kinds of approaches are used 1) Averaging method 2) min-max method.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Medical Image Fusion Techniques Using Discrete Wavelet Transform\",\"authors\":\"P. Prasad, S. Subramani, V. Bhavana, H. Krishnappa\",\"doi\":\"10.1109/ICCMC.2019.8819672\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identifying the ailments and to cure these ailments require accurate and defined evidence that has to be obtained from different kinds of medical images, like Positron Emission tomography(PET), Computed tomography(CT), Magnetic Resonance Imaging(MRI) etc. By undergoing their respective procedure and scans, these methods are commonly used, since they provide necessary evidence and indications about the disease whose information is insufficient and vague. In the given situation, fusion of medical images can be of greatest importance as the complete standard of scans can be improvised and upgraded. Hence, combining various multimodality medical images provides an adverse image with more properly specified data of body structure and high spectral data. Image fusion is highly opted in therapeutic analysis and testing. In this paper, the MRI and PET scans are processed. Before applying any further transformations, we enhance the standard of the images, as these images are tainted and non-readable due to numerous aspects. With the help of Gaussian filters, this is one of the important spatial filtering techniques. Discrete wavelet transform is applied on the images obtained after filtering two kinds of approaches are used 1) Averaging method 2) min-max method.\",\"PeriodicalId\":232624,\"journal\":{\"name\":\"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCMC.2019.8819672\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCMC.2019.8819672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

识别疾病并治疗这些疾病需要准确和明确的证据,这些证据必须从不同类型的医学图像中获得,如正电子发射断层扫描(PET)、计算机断层扫描(CT)、磁共振成像(MRI)等。通过进行各自的程序和扫描,这些方法通常被使用,因为它们提供了关于疾病的必要证据和迹象,而这些疾病的信息是不充分和模糊的。在特定情况下,医学图像的融合可能是最重要的,因为可以临时制定和升级完整的扫描标准。因此,将各种多模态医学图像组合在一起,可以获得具有更合适的身体结构数据和高光谱数据的不利图像。图像融合在治疗分析和测试中被高度选择。本文对MRI和PET扫描结果进行了处理。在应用任何进一步的转换之前,我们提高了图像的标准,因为这些图像由于许多方面的原因而被污染和不可读。在高斯滤波器的帮助下,这是一种重要的空间滤波技术。对滤波后的图像进行离散小波变换,采用两种方法:1)平均法;2)最小-最大法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medical Image Fusion Techniques Using Discrete Wavelet Transform
Identifying the ailments and to cure these ailments require accurate and defined evidence that has to be obtained from different kinds of medical images, like Positron Emission tomography(PET), Computed tomography(CT), Magnetic Resonance Imaging(MRI) etc. By undergoing their respective procedure and scans, these methods are commonly used, since they provide necessary evidence and indications about the disease whose information is insufficient and vague. In the given situation, fusion of medical images can be of greatest importance as the complete standard of scans can be improvised and upgraded. Hence, combining various multimodality medical images provides an adverse image with more properly specified data of body structure and high spectral data. Image fusion is highly opted in therapeutic analysis and testing. In this paper, the MRI and PET scans are processed. Before applying any further transformations, we enhance the standard of the images, as these images are tainted and non-readable due to numerous aspects. With the help of Gaussian filters, this is one of the important spatial filtering techniques. Discrete wavelet transform is applied on the images obtained after filtering two kinds of approaches are used 1) Averaging method 2) min-max method.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信