The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging A Balanced Alternative to Deep Learning and Radiomics

被引:2
|
作者
Kaneko, Masatomo [1 ,2 ,3 ,4 ]
Magoulianitis, Vasileios [5 ]
Ramacciotti, Lorenzo Storino [1 ,2 ,3 ]
Raman, Alex [6 ]
Paralkar, Divyangi [1 ,2 ,3 ]
Chen, Andrew [1 ,2 ,3 ]
Chu, Timothy N. [1 ,2 ,3 ]
Yang, Yijing [5 ]
Xue, Jintang [5 ]
Yang, Jiaxin [5 ]
Liu, Jinyuan [5 ]
Jadvar, Donya S. [7 ]
Gill, Karanvir [1 ,2 ,3 ]
Cacciamani, Giovanni E. [1 ,2 ,3 ,8 ]
Nikias, Chrysostomos L. [5 ]
Duddalwar, Vinay [8 ]
Kuo, C-C. Jay [5 ]
Gill, Inderbir S. [1 ,2 ]
Abreu, Andre Luis [1 ,2 ,3 ,8 ,9 ]
机构
[1] Univ Southern Calif, USC Inst Urol, Los Angeles, CA USA
[2] Univ Southern Calif, Keck Sch Med, Catherine & Joseph Aresty Dept Urol, Los Angeles, CA USA
[3] USC Inst Urol, Focal Therapy & Artificial Intelligence Prostate C, Ctr Image Guided Surg, Los Angeles, CA USA
[4] Kyoto Prefectural Univ Med, Grad Sch Med Sci, Dept Urol, Kyoto, Japan
[5] Univ Southern Calif, Ming Hsieh Dept Elect & Comp Engn, Los Angeles, CA USA
[6] Western Univ Hlth Sci, Pomona, CA USA
[7] Univ Southern Calif, Dornsife Sch Letters & Sci, Los Angeles, CA USA
[8] Univ Southern Calif, Keck Sch Med, Dept Radiol, Los Angeles, CA USA
[9] 1441 Eastlake Ave, Suite 7416, Los Angeles, CA 90089 USA
关键词
Prostate cancer; Prostate biopsy; Magnetic resonance imaging; Artificial intelligence; Machine learning; Radiomics; Deep learning; Computer vision; U-NET; MRI; SEGMENTATION; ALGORITHMS;
D O I
10.1016/j.ucl.2023.08.001
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Prostate MRI is an area where the application of AI has shown promising results in recent years. Several AI systems have been developed to automatically analyze prostate MRI images for prostate segmentation, cancer detection, and region characterization, thereby assisting clinicians in their decision-making process. The current trend in PCa imaging AI is DL, but this approach suffers from the black box issue and excessive energy consumption. Therefore, next-generation non-DL AI models such as GL that can achieve high accuracy while still being explainable and sustainable are desired. To prepare for the coming AI era, physicians must be familiar with imaging AI for PCa diagnosis.
引用
收藏
页码:1 / 13
页数:13
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