Invited Commentary: The Power and Promise of Artificial Intelligence for Digital Breast Tomosynthesis.
Invited Commentary: The Power and Promise of Artificial Intelligence for Digital Breast Tomosynthesis.
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特邀评论：人工智能在数字乳腺断层合成中的力量和前景。
DOI：
10.1148/rg.220162
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Bahl,Manisha
中科院分区：
文献类型：
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作者：
Bahl,Manisha
1. MQSA国家统计数据。美国食品和药物管理局网站。https：//www. FDA. gov/radiation-emitting-products/mqsa-insights/mqsa-national-statistics。2022年6月15日访问。2. Hooley RJ，Durand MA，Philpotts LE.数字乳腺断层合成摄影的进展。AJR Am J Roentgenol 2017; 208（2）：256-266。3.放大图片Butler R，Conant EF，Philpotts L.数字乳腺断层合成摄影：我们学到了什么？J Breast Imaging 2019; 1（1）：9-22. 4. Dang PA，Freer PE，Humphrey KL，Halpern EF，Raffeine EA.在传统数字乳腺摄影中增加断层合成：对筛查检查图像判读时间的影响。放射学2014; 270（1）：49-56。5.奇卡曼合成乳腺X射线摄影：回顾临床使用的优点和缺点。乳腺成像杂志2022; 4（2）：124-134。6. Goldberg JE，Reig B，Lewin AA，et al. New horizons：artificial intelligence for digital breast tomosynthesis. RadioGraphics 2022; 43（1）：e220060。https：//doi. org/10.1148/rg. 220060.
1. MQSA national statistics. US Food and Drug Administration website. https://www. fda. gov/radiation-emitting-products/mqsa-insights/mqsa-national-statistics. Accessed June 15, 2022. 2. Hooley RJ, Durand MA, Philpotts LE. Advances in digital breast tomosynthesis. AJR Am J Roentgenol 2017; 208 (2): 256–266. 3. Butler R, Conant EF, Philpotts L. Digital breast tomosynthesis: what have we learned? J Breast Imaging 2019; 1 (1): 9–22. 4. Dang PA, Freer PE, Humphrey KL, Halpern EF, Rafferty EA. Addition of tomosynthesis to conventional digital mammography: effect on image interpretation time of screening examinations. Radiology 2014; 270 (1): 49–56. 5. Chikarmane S. Synthetic Mammography: review of benefits and drawbacks in clinical use. J Breast Imaging 2022; 4 (2): 124–134. 6. Goldberg JE, Reig B, Lewin AA, et al. New horizons: artificial intelligence for digital breast tomosynthesis. RadioGraphics 2022; 43 (1): e220060. https://doi. org/10.1148/rg. 220060.