Deep learning-based artificial intelligence applications in prostate MRI: brief summary

被引：26
|
作者：
Turkbey, Baris [1 ]
Haider, Masoom A. [2 ,3 ,4 ,5 ]
机构：
[1] NCI, Mol Imaging Branch, NIH, Bethesda, MD 20892 USA
[2] Sinai Hlth Syst, Lunenfeld Tanenbaum Res Inst, Toronto, ON, Canada
[3] Univ Hlth Network, Sinai Hlth Syst, Joint Dept Med Imaging, Toronto, ON, Canada
[4] Univ Toronto, Toronto, ON, Canada
[5] Ontario Inst Canc Res, Toronto, ON, Canada
来源：
BRITISH JOURNAL OF RADIOLOGY | 2022年 / 95卷 / 1131期
关键词：
SEGMENTATION; PERFORMANCE; SYSTEM; DIAGNOSIS; IMPROVES; QUALITY; CANCER;
D O I：
10.1259/bjr.20210563
中图分类号：
R8 [特种医学]; R445 [影像诊断学];
学科分类号：
1002 ; 100207 ; 1009 ;
摘要：
Prostate cancer (PCa) is the most common cancer type in males in the Western World. MRI has an established role in diagnosis of PCa through guiding biopsies. Due to multistep complex nature of the MRI-guided PCa diagnosis pathway, diagnostic performance has a big variation. Developing artificial intelligence (AI) models using machine learning, particularly deep learning, has an expanding role in radiology. Specifically, for prostate MRI, several AI approaches have been defined in the literature for prostate segmentation, lesion detection and classification with the aim of improving diagnostic performance and interobserver agreement. In this review article, we summarize the use of radiology applications of AI in prostate MRI.
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页数：6
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