Deep learning analysis of contrast-enhanced spectral mammography to determine histoprognostic factors of malignant breast tumours
Author:
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00330-022-08538-4.pdf
Reference39 articles.
1. Jochelson M (2014) Contrast-enhanced digital mammography. Radiol Clin North Am 52:609–616. https://doi.org/10.1016/j.rcl.2013.12.004
2. Lalji UC, Jeukens CRLPN, Houben I et al (2015) Evaluation of low-energy contrast-enhanced spectral mammography images by comparing them to full-field digital mammography using EUREF image quality criteria. Eur Radiol 25:2813–2820. https://doi.org/10.1007/s00330-015-3695-2
3. Dromain C, Balleyguier C, Adler G et al (2009) Contrast-enhanced digital mammography. Eur J Radiol 69:34–42. https://doi.org/10.1016/j.ejrad.2008.07.035
4. Cheung Y-C, Lin Y-C, Wan Y-L et al (2014) Diagnostic performance of dual-energy contrast-enhanced subtracted mammography in dense breasts compared to mammography alone: interobserver blind-reading analysis. Eur Radiol 24:2394–2403. https://doi.org/10.1007/s00330-014-3271-1
5. Jochelson MS, Dershaw DD, Sung JS et al (2013) Bilateral contrast-enhanced dual-energy digital mammography: feasibility and comparison with conventional digital mammography and MR imaging in women with known breast carcinoma. Radiology 266:743–751. https://doi.org/10.1148/radiol.12121084
Cited by 16 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. Lesion conspicuity and contrast kinetics as predictors to differentiate benign and malignant breast lesions in contrast-enhanced mammogram;Egyptian Journal of Radiology and Nuclear Medicine;2024-09-03
2. Simulated image-specific microcalcification clusters and associated mass enhancement to enhance training of a deep learning model for cancer detection in contrast-enhanced mammography;17th International Workshop on Breast Imaging (IWBI 2024);2024-05-29
3. Deep Learning for Contrast Enhanced Mammography - a Systematic Review;2024-05-13
4. Validation of artificial intelligence contrast mammography in diagnosis of breast cancer: Relationship to histopathological results;European Journal of Radiology;2024-04
5. Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer;Academic Radiology;2024-04
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