对比增强乳腺MRI中注射前对伪影的预判：人工智能再次助力 - Suppr

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超能文献

Pre-injection anticipation of artifacts in contrast-enhanced breast MRI: artificial intelligence harnessed for the aid once again.

作者信息

Nissan Noam

机构信息

Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel.

School of Medicine, Tel Aviv University, Tel Aviv, Israel.

出版信息

Eur Radiol. 2024 Jul;34(7):4750-4751. doi: 10.1007/s00330-023-10536-z. Epub 2023 Dec 20.

DOI:10.1007/s00330-023-10536-z

PMID:38117341

Abstract

摘要

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本文引用的文献

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MRI can accurately diagnose breast cancer during lactation.MRI 可准确诊断哺乳期乳腺癌。

Eur Radiol. 2023 Apr;33(4):2935-2944. doi: 10.1007/s00330-022-09234-z. Epub 2022 Nov 8.

Using deep learning to safely exclude lesions with only ultrafast breast MRI to shorten acquisition and reading time.利用深度学习仅通过超快乳腺 MRI 安全排除病变，从而缩短采集和阅读时间。

Eur Radiol. 2022 Dec;32(12):8706-8715. doi: 10.1007/s00330-022-08863-8. Epub 2022 May 26.

Automated artifact detection in abbreviated dynamic contrast-enhanced (DCE) MRI-derived maximum intensity projections (MIPs) of the breast.自动检测缩短动态对比增强磁共振成像（DCE-MRI）衍生乳腺最大强度投影（MIP）中的伪影。

Eur Radiol. 2022 Sep;32(9):5997-6007. doi: 10.1007/s00330-022-08626-5. Epub 2022 Apr 2.

An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions.基于最大密度投影磁共振图像的人工智能系统有助于非肿块样强化乳腺病变的分类。

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