可视化和后处理医学图像- MPR, MIP, VRT,分割。精华与应用

G. Valchev, Dimitrina Markova, Daniela Kaloyanova, Samar El Shemeri, S. Chausheva, M. Yordanova
{"title":"可视化和后处理医学图像- MPR, MIP, VRT,分割。精华与应用","authors":"G. Valchev, Dimitrina Markova, Daniela Kaloyanova, Samar El Shemeri, S. Chausheva, M. Yordanova","doi":"10.14748/VMF.V10I2.7876","DOIUrl":null,"url":null,"abstract":"The workload in radiology departments has been increasing substantially over the last few decades. This is due to the greater need of tomographic examinations, as well as the increasing number of slices in each examination, determined by the advancements in tomographic technology. In order to ameliorate this, it is necessary to implement means of optimising the workflow of the diagnostic radiologist. Among them the most widely spread and easily accessible are special methods for visualization and image postprocessing – multiplanar reformats, maximum intensity projections, volume rendering techniques, and segmentation. They enable easier differentiation of unclear findings, faster and more reliable discovery of fine small calibre lesions and thrombi, improved spatial orientation and pre-operative planning, as well as acquisition of reproducible and reliable medical scientific measurements. These methods are available as builtin modules in most medical imaging software packages (including ones with an open source) and are an integral part of radiological interpretation, saving time and effort. In the future they can be reinforced with highly specialized artificial intelligence, which could make automatic measurements and locate a specific type of finding.","PeriodicalId":23566,"journal":{"name":"Varna Medical Forum","volume":"80 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Visualization and postprocessing of medical images – MPR, MIP, VRT, segmentation. Essence and application\",\"authors\":\"G. Valchev, Dimitrina Markova, Daniela Kaloyanova, Samar El Shemeri, S. Chausheva, M. Yordanova\",\"doi\":\"10.14748/VMF.V10I2.7876\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The workload in radiology departments has been increasing substantially over the last few decades. This is due to the greater need of tomographic examinations, as well as the increasing number of slices in each examination, determined by the advancements in tomographic technology. In order to ameliorate this, it is necessary to implement means of optimising the workflow of the diagnostic radiologist. Among them the most widely spread and easily accessible are special methods for visualization and image postprocessing – multiplanar reformats, maximum intensity projections, volume rendering techniques, and segmentation. They enable easier differentiation of unclear findings, faster and more reliable discovery of fine small calibre lesions and thrombi, improved spatial orientation and pre-operative planning, as well as acquisition of reproducible and reliable medical scientific measurements. These methods are available as builtin modules in most medical imaging software packages (including ones with an open source) and are an integral part of radiological interpretation, saving time and effort. In the future they can be reinforced with highly specialized artificial intelligence, which could make automatic measurements and locate a specific type of finding.\",\"PeriodicalId\":23566,\"journal\":{\"name\":\"Varna Medical Forum\",\"volume\":\"80 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Varna Medical Forum\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14748/VMF.V10I2.7876\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Varna Medical Forum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14748/VMF.V10I2.7876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在过去的几十年里,放射科的工作量大幅增加。这是由于层析成像技术的进步决定了对层析成像检查的更大需求,以及每次检查中切片数量的增加。为了改善这一点,有必要实施优化诊断放射科医生工作流程的手段。其中最广泛传播和最容易获得的是用于可视化和图像后处理的特殊方法——多平面重新格式化、最大强度投影、体绘制技术和分割。它们可以更容易地区分不明确的发现,更快更可靠地发现细微的小口径病变和血栓,改进空间定向和术前规划,以及获得可重复和可靠的医学科学测量。这些方法在大多数医学成像软件包(包括开源软件包)中作为内置模块可用,并且是放射学解释的组成部分,节省了时间和精力。未来,它们可以用高度专业化的人工智能来加强,人工智能可以自动测量并定位特定类型的发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Visualization and postprocessing of medical images – MPR, MIP, VRT, segmentation. Essence and application
The workload in radiology departments has been increasing substantially over the last few decades. This is due to the greater need of tomographic examinations, as well as the increasing number of slices in each examination, determined by the advancements in tomographic technology. In order to ameliorate this, it is necessary to implement means of optimising the workflow of the diagnostic radiologist. Among them the most widely spread and easily accessible are special methods for visualization and image postprocessing – multiplanar reformats, maximum intensity projections, volume rendering techniques, and segmentation. They enable easier differentiation of unclear findings, faster and more reliable discovery of fine small calibre lesions and thrombi, improved spatial orientation and pre-operative planning, as well as acquisition of reproducible and reliable medical scientific measurements. These methods are available as builtin modules in most medical imaging software packages (including ones with an open source) and are an integral part of radiological interpretation, saving time and effort. In the future they can be reinforced with highly specialized artificial intelligence, which could make automatic measurements and locate a specific type of finding.
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
期刊最新文献
Key Apoptosis Signaling Pathways In Malignant Diseases Thrombocytopenia and Thrombosis Effect of Anethole on Visceral Obesity and Serum Triglycerides and Cholesterol Levels in Rats on a High-Calorie Diet Effects Of Melatonin Suplementation On Body Mass Index In A Diet-Induced Obesity Rat Model Bilateral Olfactory Bulbectomy (OBX) as a Model of Depression
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1