Observer Performance with Varying Radiation Dose and Reconstruction Methods for Detection of Hepatic Metastases
Author:
Affiliation:
1. From the Departments of Radiology (J.G.F., J.L.F., S.K.V., D.M.H., N.T., L.Y., S.L., C.H.M.), Health Sciences Research (M.J., R.C.), and Physiology and Biomedical Research (D.R.H.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.
Funder
National Institutes of Health
Publisher
Radiological Society of North America (RSNA)
Subject
Radiology, Nuclear Medicine and imaging
Link
http://pubs.rsna.org/doi/pdf/10.1148/radiol.2018180125
Reference24 articles.
1. Methods for Clinical Evaluation of Noise Reduction Techniques in Abdominopelvic CT
2. State of the Art: Iterative CT Reconstruction Techniques
3. Suspected Acute Colon Diverticulitis: Imaging with Low-Dose Unenhanced Multi–Detector Row CT
4. Contrast-to-Noise Ratio and Low-Contrast Object Resolution on Full- and Low-Dose MDCT: SAFIRE Versus Filtered Back Projection in a Low-Contrast Object Phantom and in the Liver
5. Noise-reducing algorithms do not necessarily provide superior dose optimisation for hepatic lesion detection with multidetector CT
Cited by 45 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. Peripheral liver metastases are more frequently missed than central metastases in contrast-enhanced CT: insights from a 25-reader performance study;Abdominal Radiology;2024-08-20
2. A Proposal for a Process from as Low as Reasonably Achievable to an Ultra-Low-Level Goal in Chest Computed Tomography;Journal of Clinical Medicine;2024-08-06
3. Development and validation of a noise insertion algorithm for photon‐counting‐detector CT;Medical Physics;2024-06-23
4. Deep learning-based enhancement of ultra-low-dose cone-beam CT image using simulated data;Medical Imaging 2024: Physics of Medical Imaging;2024-04-01
5. Image quality evaluation in deep‐learning‐based CT noise reduction using virtual imaging trial methods: Contrast‐dependent spatial resolution;Medical Physics;2024-03-31
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